And, being in Europe, you got great location, and smart SEOs spread around easy-to-travel countries near-by.

This is your last-minute fix if you are looking for one more event to use your company’s training budget, last-minute free time, or combine with some vacations to get over summer’s end blues 😊

Quick view on the SEO conferences

◆ ◆ ◆ ◆ SPONSORED ◆ ◆ ◆ ◆

This newsletter is proudly sponsored by SEO on Stage. An SEO conference like no other coming in Athens Greece.

The best part of it?

This is the one in the list I will be participating both as an attendee, speaker, and MC.

Book your place with 70% discount: SEO-On-Stage-NickMalekos70

P.S.: If upskilling is your goal this year, you will find no better place to learn by joining live experts and colleagues in the SEO industry, and the rising art of AEO/GEO – optimizing for AI search.

◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆

1. brightonSEO UK, October Edition

Date: 8 to 9 October 2026

Location: The Brighton Centre, Brighton, UK

Main speakers: Ross Simmonds (closing keynote), plus 190+ speakers across multiple stages

Ticket: Friend pass, £580 + VAT (two days) (24th of September is the last day for £430 tickets)

brightonSEO is one of the biggest search conference in the world. More than 4,500 marketers come from 70+ countries. This edition is also its 10th anniversary at the Brighton Centre.

Being at Brighton two years back, it’s an experience worth living.

My advice, register for the masterclasses, and be sure to network with fellow SEOs, that’s where most of the value lies.

Register at: brightonSEO October 2026

2. Masters of Search

Date: 22 October 2026

Location: von Greifswald, Berlin, Germany

Main speakers: Aleyda Solis (Orainti, SEOFOMO), Malte Landwehr (Peec AI), Fabrizio Ballarini (Revolut), Margus Veeber (Pipedrive), Jennifer Lapp (Brevo), Amir Bohnenkamp (Heyflow), Anita Kirkovska (Vellum)

Tickets starting at €499 Regular

Masters of Search sits at the other end from brightonSEO. It’s one day with 175 seats, all talks in English, and the focus is GEO and AI search.

For SaaS marketers, this is the most relevant agenda on the list.

Go if: you lead organic growth at a SaaS or tech company and want peer-level operators instead of vendors.

Masters of Search

3. SEO On Stage, Athens Edition

Date: Saturday, 24 October 2026

Location: Benaki Museum, Pireos 138, Athens, Greece

Main speakers: Arnout Hellemans, Malte Landwehr, Nick Malekos, Marco Giordano, Natalia Witczyk, Tom Winter, Helene Jelenc, Ivana Flynn, Darko Ivanoski, Darko Brzica, Sarah Pokorna

Tickets: €80 Standard,

70% off with code SEO-On-Stage-NickMalekos70

Full disclosure: I’m the MC for this one, and I also join a round table on the day. So yes, I’m biased.

SEO On Stage will be closer to a theatre production, with talks, music and conversation into the night, all inside a real theatre space at the Benaki Museum.

The speakers are practitioners you rarely see together in Southern Europe. Arnout Hellemans and Tom Winter bring technical and strategic depth. Malte Landwehr covers AI search visibility, since his company, Peec AI, tracks brand presence in LLMs. There are also panels and a fireside chat on where search goes next.

Expect more AI Search, and iGaming in the heart of Athens with SEOs from all over Europe.

SEO On Stage Athens Edition

P.S.: Athens is a city to experience, be careful where you book your stay and book some extra days for incredible food, museums, and cultural activities – also one of the European capitals for escape rooms 😉

4. SERP Conf. Vienna

Date: 3 to 4 November 2026

Location: Tech Gate Vienna, Austria

Main speakers: Barry Schwartz (RustyBrick), Martin Splitt (Google), Dan Petrovic (DEJAN Marketing), Jes Scholz, Chima Mmeje (Moz), Jairo Guerrero (Organic Hackers)

Tickets: €499 Conference Ticket (Day 1 conference, networking cocktail and Day 2 masterclasses) – early bird tickets end on September 30th

SERP Conf. sits where SEO, e-commerce and AI meet.

Dan Petrovic alone makes it worth considering. Few people have done more practical research on how LLMs select and cite content. Barry Schwartz brings the news desk view of what’s actually changing in Google.

There is also a Team Pass with two tickets for the price of one. If you’re sending two people from the same team, that’s the best value on the list after Athens.

Go if: you want structured learning and hands-on masterclasses, not just talks.

SERP Conf. Vienna

P.S.: Vienna is a beautiful visit, always book extra days.

5. MozCon London

Date: 13 November 2026

Location: Convene 22 Bishopsgate, London, UK

Main speakers: Dr. Pete Meyers and Tom Capper (Moz), Helen Pollitt (Getty Images), Miracle Inameti-Archibong (John Lewis), Mark Williams-Cook (Candour), Beatrice Gamba (WordLift), Chima Mmeje (Moz)

Tickets: £520 General Admission

MozCon was a Seattle institution for years. The London edition brings it to European audiences as a single, focused day.

The lineup leans toward enterprise in-house SEO.

Getty Images and John Lewis run search at a scale where small percentage gains are worth millions.

Beatrice Gamba from WordLift covers the entity and knowledge graph side, which matters more every month as AI systems decide which brands to trust.

Go if: you run in-house SEO at an enterprise brand, or you want data-led talks from the Moz research team.

MozCon London

6. SEOkomm

Date: 27 November 2026

Location: Salzburg Congress, Salzburg, Austria

Main speakers: Bastian Grimm (Peak Ace), Tobias Fox (VERDURE), Kai Spriestersbach, Michael Schilling, Thiago Pojda, Nina Roser (fischerAppelt)

Tickets start at €630 net (depends on the sales phase, standard €790 net plus 20% Austrian VAT)

SEOkomm is the most respected SEO conference in the DACH region. It’s also the last major in-person SEO event in Europe this year.

Talks are in German.

SEOkomm

How to choose the right SEO conference for you

For tight budgets

SEO On Stage Athens (€80 before the discount). The Search Central Deep Dive is free if you already have a place.

AI search, GEO and AEO

Masters of Search in Berlin. SEO On Stage and SERP Conf. also give it heavy coverage.

Enterprise in-house SEO

MozCon London.

Biggest networking crowd

brightonSEO.

DACH market

SEOkomm.

FAQ

What is the cheapest SEO conference in Europe in fall 2026?

SEO On Stage Athens is the cheapest paid option at €80 Standard, with 70% off using code SEO-On-Stage-NickMalekos70.

Are there SEO conferences in Europe in October 2026?

Yes. October is the busiest month of the fall season, with four events:

• brightonSEO UK is on 8 and 9 October in Brighton.
• Masters of Search is on 22 October in Berlin.
• SEO On Stage Athens Edition is on 24 October at the Benaki Museum in Athens.

Are there SEO conferences in Europe in November 2026?

Yes. November has three:

• SERP Conf. is on 3 and 4 November in Vienna, with a conference day followed by a masterclass day.
• MozCon London is on 13 November and focuses on enterprise and in-house SEO.
• SEOkomm is on 27 November in Salzburg. Its talks are in German.

SERP Conf. is the best value if you’re sending a team, because its Team Pass gives two tickets for the price of one.

Are there SEO conferences in Europe in December 2026?

No major in-person SEO conferences in Europe are scheduled for December 2026. SEOkomm in Salzburg on 27 November is the last big one of the year.

Which fall 2026 SEO conferences focus on AI search?

Masters of Search (Berlin), SEO On Stage (Athens) and SERP Conf. (Vienna) put AI search, GEO and AEO at the center of their agendas. At brightonSEO, the closing keynote covers brand visibility in LLMs.

Which conferences are in English?

All of them except SEOkomm, which runs in German.

Can I still book a Q4 SEO conference in 2026?

Yes. Six of the seven events on this list still sell tickets. Search Central Live Deep Dive needs registration through Google, and places are limited.

Final thought

You don’t need to go to every conference. This is a last-minute budget for a quick travel.

Choose something that is near, convenient, good priced, and will give the most value in a couple of days.

I always like to add a couple of days to explore the location and live the city 🙂

For me, it will be Athens for SEO on Stage, then Lisbon for a GTM event.

Where are you going?

The post Top SEO Conferences in Europe for Fall 2026 – Last-minute Picks appeared first on Marketing Experts Hub.

Now it is going away.

Shield is winding down.

Both Google and LinkedIn made it clear that we could not continue operating Shield as it was built. We decided not to fight it.

Since 2018, Shield has helped people understand the work they were doing on LinkedIn. Tens of thousands of creators, writers, founders, and operators used Shield to make sense of their words, their content. That mattered to us. We hope it mattered to you.

To all of you who trusted us, thank you.

Andreas & Alex
Co-founders, Shield

This article covers what happened, what current users need to do this week, and the best Shield alternatives in 2026, with honest pros, cons, and best use cases for each.

Why Is Shield Shutting Down?

The ShieldApp had it’s troubles with LinkedIn and their business page got blocked by the platform.

Their app was pulled from the Chrome Store, and they asked the users to manual download & update it.

The workarounds didn’t seem to work, as a few months layer they are announcing their “winding down”.

This is the same wall that hit Apollo and Seamless.AI. LinkedIn does not want third parties operating on top of its platform.

What Shield Users Should Do First: Export Your Data

Before you evaluate a single replacement: export your data while you still can.

Shield’s whole value was historical depth. Years of post history, engagement trends, audience breakdowns. That context does not exist anywhere else once the tool is gone, and you will not get it back from LinkedIn’s native analytics, which only look backward a limited window.

Pull everything. CSV exports, screenshots of the dashboards that matter, whatever the platform still allows. Do it today, not the week of the deadline.

How to Choose a Shield App Alternative

There is no clean one-to-one replacement, because Shield did one thing extremely well and nothing else. The honest answer depends on the job you actually need done.

Most people conflate three different jobs. Get this right before you pick a tool:

• Measuring your own performance … the actual Shield-shaped hole.
• Acting on buyer signals … finding who is in market, not how your post did.
• Capturing and organizing inputs … the swipe file and the people you track.

Here is every tool we are covering, by job, with pros, cons, and the use case each one actually fits.

The three all-in-one Shield alternatives compared side by side. Pricing verified May 2026.

All three advertise a low entry price that locks the feature most people actually want behind a higher tier, so the table shows both the headline price and the real one.

Pricing changes often. Confirm current plans on each tool’s site before subscribing.

Best Shield Alternatives for LinkedIn Analytics

1. DemandBird

DemandBird goes beyond LinkedIn only and adds multiple layers of social scheduling across multiple social media.

Tracking analytics for everything in one platform, using the official LinkedIn APIs to avoid getting the fate of ShiledApp.

Try DemandBird

Get 20% for 24 months currently on DemandBird with the coupon code: MALEKOS

DemandBird can be used by individual creators, but it’s multi-social and team management features are perfect for big companies and agencies handling many social accounts across multiple companies.

Pros

• 9 platforms including Substack
• Built for teams: approvals, workspaces, Company Pages
• Repurposing engine and content pillars
• MCP server and REST API for automation
• Official APIs, no cookie-based scraping and no ban risk

Cons

• Analytics only use the official API which might be limited
• Approvals & API are under the second tier
• Trial requires a card

Best for: B2B teams and agencies who publish on more than LinkedIn who need processes and approvals.

2. Taplio

The all-in-one play: analytics plus AI writing plus scheduling plus a lead database on the higher tier.

Try Taplio

Pros

• Consolidates Shield plus a separate scheduler into one tool.
• AI content generation speeds up drafting.
• Lead database prospecting on the Pro tier.

Cons

• Analytics are adequate, not a step up. If deep data is why you paid for Shield, this is a downgrade on that axis.
• Some automation features push against LinkedIn’s policies, which carries account risk.
• Pricier than single-purpose tools (starts around $39/month).

Best for: Solo creators and founders who want content, scheduling, and analytics in one place and are not running deep data analysis.

3. AuthoredUp

AuthoredUp is the most common landing spot for ex-Shield users. It does analytics, but the center of gravity is content creation: post editor, formatting, device preview, drafts, hooks, and a template library.

Pros

• Backfills your full historical post data instead of starting from install date.
• Does not collect your LinkedIn cookies, which it positions as a safety advantage.
• Combines measurement and writing in one tool, so you stop tab-switching.
• Works for company pages, not just personal profiles.

Cons

• Analytics are solid but not as deep as Shield’s data slicing.
• You pay partly for writing features even if you only want analytics.

Best for: Creators who post consistently and want one tool to write, format, preview, and measure. Pricing sits around $20/month.

4. Supergrow

Supergrow is the budget all-in-one.

Pros

• Cheapest all-in-one option (around $19/month).
• Voice-learning AI, scheduling, and analytics bundled.

Cons

• Analytics are less granular than Shield.
• AI content quality varies.

Best for: Budget-first creators who cannot justify a standalone analytics subscription and want a full package that is good enough across the board.

Extra Tool: Capturing and Organizing Inputs

The third job nobody mentions until they lose access. Not “how is my content doing,” but “how do I capture and organize the posts and people worth learning from.”

LibrarIn

Full disclosure: I built this one. It is a free Chrome extension that adds a tagging and categorization layer on top of the LinkedIn feed.

Pros

• Completely free. No tiers, no post limits, no category limits.
• Save posts into custom color-coded categories, search by keyword, filter by author.
• People You Follow lets you track specific profiles (competitors, ICPs, key prospects) regardless of what the algorithm surfaces that day.
• Privacy-first: no credentials collected, no browsing history tracked. Full CSV export, no lock-in.
• No scraping and no terms-of-service violation, so it does not share Shield’s structural fragility.

Cons

• No analytics. It does not track impressions, engagement, or follower growth.
• Chrome only.
• It does not replace Shield. It solves the capture problem that sits next to the measurement problem.

Best for: Creators building a swipe file, and marketers running competitive intelligence or ABM-style prospect tracking who cannot rely on the feed to surface the right content.

Frequently Asked Questions

Is Shield (ShieldApp) really shutting down?

Yes. The founders confirmed Shield is winding down, citing that Google and LinkedIn made it clear they could not continue operating it as built.

Will I lose my Shield analytics data?

Eventually, yes. Export everything now: CSV files and screenshots of the dashboards that matter. The historical depth does not exist anywhere else once access is gone.

What is the closest replacement for Shield?

For a pure dashboard, Inlytics or LinkedIn’s native analytics. For analytics plus a writing workflow, AuthoredUp is the most common switch.

Is there a free Shield alternative?

Yes. LinkedIn’s native analytics and Inlytics’ free tier cover the basics. LibrarIn is free for the separate job of capturing and organizing posts and people.

The post Shieldapp is Closing Down: What to do now? appeared first on Marketing Experts Hub.

But those placements are competitive. For any given query, multiple businesses are bidding for the same handful of spots.

SaaS PPC agencies know how ad platforms decide which businesses win those spots and they use that knowledge to help you get in. They do this through strategies like audience targeting, budget optimization, and landing page optimization.

Some of the top SaaS PPC agencies are:

Now that you have a brief overview, here’s a more detailed explanation of each agency.

Disclaimer: The information about these agencies is accurate as of 29th April, 2026.

1. AdConversion 

AdConversion is a B2B SaaS PPC agency that specializes in creating ad campaigns optimized for revenue (not clicks and low-quality leads).

Source: Adconversion.com

To achieve this, it digs into your CRM data to identify the lead types actually closing deals. It uses the data it finds to build multi-channel campaigns across Google, LinkedIn, Reddit, YouTube, Capterra, and Bing to attract more of those, not form-fills. Meanwhile, the in-house team designs ad creatives and landing pages using what they learn about your brand guidelines and product positioning.

Once campaigns are live, AdConversion’s internal automation platform continuously monitors performance and uses specific rules to optimize your ad campaign for revenue. For example, it can:

• Pause ads when the cost per SQL exceeds $1,000
• Flag creative fatigue when frequency exceeds 5 and CTR drops below 1%
• Limit LinkedIn spend to business hours only

The reporting reflects that same logic. The Revenue Dashboard pulls ad channel data (Google, LinkedIn, Meta) directly into your CRM. So, closed/won data flows back into the platforms, and they optimize toward actual revenue. 

Offline conversion tracking is also part of the setup, so Google and LinkedIn see which leads became customers, not just clickers. For teams on HubSpot or Salesforce, this closes the attribution loop most agencies leave open.

As for the management structure for each campaign, each client has a senior B2B performance marketer, backed by a dedicated creative, web development, and data team. 

That means, over time, they become knowledgeable about your company, enough to create ads that communicate its positioning clearly.

On the commercial side, AdConversion is transparent about pricing. Packages range from $4,000 per month (for teams that prefer to handle execution) to $18,200 per month. Regardless of the tier, there are no fixed contracts, no ad spend fees, and a 30-day money-back guarantee. 

In B2B PPC, where agencies typically hide pricing details and 6- to 12-month retainers are standard, that’s an unusual position to take. 

But it’s an offer an agency will only make when it’s absolutely sure its methodology will produce results that will prompt clients to extend their contracts. Which is why over 8,000 B2B marketers worldwide enroll in AdConversion’s paid media Academy to learn its winning methodology.

Now, let’s look at the services they use to implement their methodology.

Services:

AdConversion’s services include:

• Pay per click (PPC)
• LinkedIn ads
• Video ads
• Demand generation
• ABM (account-based marketing)
• Landing page design and optimization
• Data analytics and revenue dashboards

Take a deeper look at what each service entails:

Who is AdConversion for?

AdConversion is best for a B2B SaaS company that’s Series A or beyond, and is spending (or ready to do so) a minimum of $15,000 per month on paid ads. Within that group, the agency is usually a strong fit for:

• Lean marketing teams running campaigns on their own or with freelancers. They are getting some results with paid media, but lack an overarching strategy. 
• Growing companies already spending massively on paid ads ($5,000+) but not getting the required results.
• In-house marketing teams that need a specialist to own paid media execution, while collaborating with AdConversion’s team on the broader strategy.

Minimum project size (Based on Clutch): 

$5,000+

2. Camel Digital

Camel Digital is a SaaS PPC agency that works with PLG and self-serve SaaS companies.

In a self-serve model, people sign up and buy inside the product without speaking to sales. The agency focuses on getting more paid customers and growing MRR without letting acquisition costs get out of control.

Source: https://www.cameldigital.co/

The founder spent two years running growth inside a PLG SaaS company, Infogram at Prezi, before starting Camel Digital in 2020. That is where he learned how people find, try and buy software from the inside. After 10+ years in SaaS PPC and $8M+ in ad spend, the team has built tested playbooks for PLG based on performance data. 

Before scaling, they look at the numbers. LTV, conversion rates and payback show what CAC the product can support and whether paid acquisition can work in the first place. Product and revenue data is then connected back to the campaigns, so the team can see which traffic actually becomes paying customers.

From there, the team looks at where the demand is and which searches and audiences bring in users who actually pay. Campaigns and landing pages are built around those opportunities. The goal is to grow paid customers and MRR while keeping CAC at a level the customer LTV can support.

Services:

• PPC (Google Ads and Microsoft Ads)
• Paid social (LinkedIn and Meta)
• ChatGPT Ads
• PPC landing pages and CRO
• Product-level conversion tracking
• PLG paid acquisition strategy and PPC audits

Minimum project size:

Recommended minimum of $5,000/month in ad spend.

Who is Camel Digital for? 

Camel Digital is built for PLG and self-serve SaaS companies past product-market fit that want to grow paid users and MRR without CAC running ahead of them. Inside that group, the agency is usually a strong fit for:

• You have a PLG SaaS product
• You have a confirmed product market fit and want to scale
• You spend, or are ready to spend, at least $5,000/month on paid ads

Pricing: Starts at $3,889/month for paid media management. 

3. Bounty Hunter

Bounty Hunter is a SaaS marketing agency that also offers PPC services. It focuses on the various channels popular with B2B SaaS buyers: Google, Bing, LinkedIn, Facebook, and even software review platforms like G2 and Capterra.

Source: Bountyhunter.agency

The agency is the result of a merger with Impactable, a LinkedIn ads agency founded by Justin Rowe. The outcome is stronger cross-channel execution than most agencies of Bounty Hunter’s size, particularly on LinkedIn, where many B2B PPC agencies are weakest.

The agency’s coverage of review platforms also sets it apart, especially since most PPC agencies either don’t know how to run G2 and Capterra campaigns or treat them as an afterthought.

On the data side, it is a certified partner of Segment, Clearbit, Mixpanel, and Adalysis, so it can set up the full data pipeline from ad click to CRM record. 

Before setting up the CRM integration, every client is assigned a dedicated PPC strategist, account manager, and copywriter, all of whom are reachable directly via Slack. In practice, it means faster feedback loops and fewer of the miscommunication issues that cause campaigns to fail.

Pricing is published up front, which is worth noting in a category where most agencies make you sit through a discovery call before revealing a number:

Now, here’s a spectrum of services you can pay for:

Services:

• Paid ads management (Google, Bing, LinkedIn, Facebook, Capterra, G2, Quora)
• Conversion rate optimization (CRO)
• Landing page design and development
• Analytics and tracking setup
• Remarketing strategy
• A/B testing
• User onboarding optimization (Unicorn plan)

Who is Bounty Hunter for?

Bounty Hunter is a strong fit for high-growth B2B SaaS companies that have moved past the early stage and are ready to scale acquisition. That means you’ll find the agency a great fit if you:

• Already have a functioning sales process
• Spend (or are ready to spend) a minimum of $5,000 on ads
• Wouldn’t mind giving the agency access to your CRM

Check out a more detailed checklist of the type of clients the agency serves:

Minimum project size (Based on Clutch): 

$5,000+

4. TripleDart

TripleDart runs paid acquisition programs across Google Ads, LinkedIn, Meta, and Bing with full ownership of pipeline and revenue outcomes.

They have managed over $150 million in ad spend across 250+ SaaS companies, which means most SaaS verticals (fintech, security, HR tech, dev tools, enterprise) are familiar territory for us.

What makes their PPC practice different is our proprietary AI workflows.

They run 24/7 and handle things like real-time budget reallocation, anomaly detection on conversion rates and CPC spikes before they drain spend, and lead quality scoring that feeds directly back into platform bidding algorithms.

Their agents also predict creative performance before launch, so we’re not just A/B testing blindly.

TripleDart’s paid programs don’t operate in a silo. Every campaign syncs with clients SEO, content, and RevOps teams, so that attribution modeling, CRM data, and organic insights all inform paid strategy.


They also run ABM programs natively alongside PPC for accounts with high ACVs and long sales cycles to warm up buying committees before they ever hit a demo form.

Best For

B2B SaaS companies with $50K+ monthly ad budgets and 6-18 month sales cycles.

Strengths

AI workflows that automate budget reallocation, anomaly detection, and creative performance prediction in real time
Paid media execution integrated with RevOps infrastructure, so attribution runs from ad click to closed deal
Native ABM layering alongside PPC for enterprise and mid-market sales cycles

Notable Clientwork and Results
We work with companies like Payoneer,
VWO, CleverTap, and Airbase.

Pricing

Starts at $3500/month for Paid Media Operations.

Rating and Reviews

TripleDart is rated 4.8/5 on Trustpilot

5. Spear Growth

Spear Growth is a B2B SaaS PPC agency based in Bengaluru, India, working with SaaS companies, from Series A startups to unicorns. This means the agency has PPC playbooks for companies at different stages of growth.

Source: Speargrowth.com

Its channel coverage is one of the broadest on this list, cutting across the usual suspects (Google Search, LinkedIn, YouTube, and Meta) and extending to niche platforms such as:

• Reddit
• G2
• GitHub
• Salesforce AppExchange

Dev tools and RevOps SaaS businesses find the coverage of GitHub and AppExchange particularly valuable.

Spear Growth implements a five-week onboarding process to set up campaigns for success. 

Week one is dedicated to auditing your existing account, firstly to identify and cut 10–20% of wasted spend. By week three, new campaigns are running under the agency’s DCDG framework: Demand Capture for buyers already in-market, and Demand Generation for buyers who aren’t. Two weeks later, ad spend is reallocated to the best-performing ads by revenue.

The other thing that separates Spear Growth is how it treats unconverted traffic.

Most PPC engagements stop at the form-fill. So, if someone clicks but doesn’t convert, they’re gone forever. 

Spear Growth tracks intent signals from that traffic (ad engagement, pages visited, time on site) and passes that data to your sales team as a list of accounts that have already shown interest. Reps can then warm-call those leads.

On reporting, this agency goes further than most. 

Ad platform metrics connect to your CRM for SQL-level attribution, while an ETL layer on top enables slicing of pipeline data by segment, channel, and funnel stage.

That way, you get insight into which campaigns generated leads and which leads actually moved through the funnel.

Let’s see the services Spear Growth offers:

Services:

• Paid channel execution (LinkedIn, Google, Meta, Reddit, G2, GitHub, AppExchange, YouTube)
• Demo and free-trial funnel optimization
• Signal-based prospecting (signal-based sales)
• Landing page CRO
• Wider conversion journey optimization
• Reporting and attribution (CRM- and ETL-integrated)
• Copy and design production
• Demand generation and strategic ownership

Who is Spear Growth for?

Spear Growth serves unicorns and Series A to C funded B2B SaaS companies. This widens its target audience to early-stage startups and mature companies. The same broad audience coverage is also reflected in the industries the agency serves:

• HR tech
• Fintech
• Dev tech
• Martech
• Security tech
• RevOps tech

Minimum project size (Based on Clutch): 

$1,000+

6. SevenAtoms

SevenAtoms is a digital marketing agency, headquartered in San Francisco. While its client base spans various industries, it has more than a decade of experience running paid media for SaaS companies.

Source: Sevenatoms.com

SevenAtom’s paid media channel coverage is one of the broadest on this list. Google Search, Bing, LinkedIn, Meta, display, video, Performance Max, and shopping ads all feature in its paid media offering. On top of that, the agency manages ad placements on G2 and Capterra, where buyers are actively comparing vendors and shortlisting solutions.

To set up campaigns on those platforms, SevenAtoms follows a methodological approach:

• Strategy: This includes account audits, CRM audits, competitor analysis, keyword and audience research, and budget planning. 
• Setup: This includes landing page design, CRM integration, conversion tracking, ad copy, creatives, and negative keyword lists.
• Ongoing optimization: This includes A/B testing across ads and landing pages, bid management, audience refinement, and real-time ROI dashboards.

While ads run, the agency reports on revenue through the integration it has set up between the ad platform and your CRM.

Services:

• Google Ads management (search, display, video, Performance Max, shopping, remarketing)
• Facebook and Instagram Ads management
• LinkedIn Ads management
• Bing Ads management
• Landing page design and CRO
• Content marketing and SEO
• Review site placements (G2, Capterra)

Who is SevenAtoms for?

SevenAtoms is a great fit for B2B SaaS companies at various stages, from startups without a dedicated marketing team to established companies looking to scale their acquisition efforts. 

Below is the agency’s eligibility checklist.

Minimum project size (Based on Clutch): 

It’s not publicly disclosed. However, based on Clutch reviews, it ranges from $5,000 to $10,000.

7. GrowthSpree

GrowthSpree is an AI-native B2B SaaS marketing agency with offices in India and the US. The agency’s offerings primarily revolve around PPC, ABM, and RevOps.

Source: Growthspreeofficial.com

It describes itself as AI-native. But unlike those agencies that use the label after merely adding a few automation tools, AI is embedded in how GrowthSpree hires, builds campaigns, and measures performance. Three proprietary tools drive most of that automation:

• Zipeline: Consistently monitors your entire marketing engine 24/7 and ties ad spend to revenue. It also automatically reallocates your ad spend to revenue-generating campaigns.
• QLA (lead quality filter): Filters out low-quality leads from Google and Meta at the source, so your sales team isn’t wasting time on people who were never going to buy.
• GrowthSpree MCP: Tracks LinkedIn ad performance and surfaces specific performance metrics using natural language prompts.

That said, AI handles only the repetitive work, such as monitoring campaigns, reporting, and reallocating spend. The strategy and the final call on every major decision stay with the senior PPC specialists on your account.

This combination of human input and AI helps the agency iterate faster and detect what’s not working before it wastes your ad spend.

When it comes to CRM integrations, HubSpot is the primary platform. 

It offers a full HubSpot implementation and migration as a standalone service, including setup and ongoing management. The goal here is to connect your Google, LinkedIn, and Meta ad data directly to the HubSpot pipeline so revenue reporting reflects closed deals.

Services:

• Google Ads, LinkedIn Ads, Meta/Facebook Ads
• Demand generation
• Account-based marketing (ABM)
• Landing page design and optimization
• Content and messaging
• RevOps (HubSpot implementation and migration)

Take a look at what’s in each service offering:

Who is GrowthSpree for?

GrowthSpree works with B2B SaaS companies at two stages, and the engagement looks different for each. 

For early-stage companies, the focus is on building the demand gen foundation from scratch. For scale-ups, the agency prioritizes scaling what’s already working and fixing what isn’t.

Here’s a checklist you can use to determine if GrowthSpree is best positioned to meet your needs:

Minimum project size (Based on Clutch): 

$1,000+

8. Powered by Search

Powered by Search is a B2B SaaS marketing agency that has been working with SaaS companies for over a decade. It’s a certified Google Partner, Meta Business Partner, and Bing Ads Accredited agency.

Source: Poweredbysearch.com

Where other agencies focus purely on paid media, Powered by Search runs the entire marketing operation (paid ads, SEO, content, digital PR, ABM, and web design) under a single strategy. 

Its argument for offering such a broad scope of services is that paid, organic, and content channels compound over time when they work in tandem rather than in isolation. 

This concept forms the basis of the agency’s Predictable Growth Model, where each marketing initiative connects with others and builds on past results. 

So, a blog post is written with distribution in mind, paid campaigns reinforce the same positioning as organic content, and each channel builds on the results of the previous ones.

Here’s how this approach extends to the services the agency offers:

Services:

• Paid advertising across Google, Facebook, Instagram, and LinkedIn
• Search engine optimization (SEO)
• Account-based marketing (ABM)
• Content marketing and publishing
• Digital PR and link building
• Demand generation strategy
• HubSpot operations and revenue operations (RevOps)
• SaaS web design and development
• Marketing for startups
• Marketing to developers

Who is Powered by Search for?

Powered by Search works best with B2B SaaS companies that are ready to hand over demand generation entirely, including the overarching strategy. They’re not a good fit for teams that want an agency to execute a plan they’ve already built internally, or for companies that only need paid media managed without the broader marketing infrastructure.

Here’s a more detailed checklist with all the eligibility criteria:

Minimum project size (Based on Clutch): 

$5,000+

9. Right Left Agency

Right Left Agency is a growth-focused digital marketing agency that works with SaaS, B2B, fintech, and construction tech companies. Its paid advertising process covers the full campaign lifecycle across Google, Meta, LinkedIn, Bing, YouTube, and programmatic display.

Source: Rightleftagency.com

The name ‘Right Left’ reflects how the agency thinks about marketing; the left brain and right brain working together. 

The left side is the science: audience research, campaign structure, attribution, optimization. The right side is the creative: ad design, copy, branding, storytelling. 

The argument is that most agencies are good at one but not both. Either they’re data-driven, and the creative is forgettable, or the creative looks great, but the targeting is all over the place.

So, to bridge the gap, Right Left handles the creative (copy, design, and video editing) and web, as well as the data, in-house. That way, creative decisions are informed by performance data, and targeting decisions are informed by what the creative can actually support.

So, what services does the agency offer?

Services:

• Paid advertising
• SEO
• Email marketing
• Branding
• Creative design
• Web design and development

Who is the Right Left Agency for?

Right Left’s minimum recommended ad spend ($1,500–$3,000 per month) is significantly lower than most specialist agencies on this list. So, it’s a great option for early-stage companies that need real paid media expertise but can’t afford the $5,000–$ 15,000 minimums that larger agencies require.

You’ll have to look elsewhere, however, if you need CRM-connected revenue dashboards, deep RevOps integration, or ABM at scale. Those capabilities aren’t part of this agency’s core offering.

Here are its best- and worst-fit companies based on its service offerings and approach:

Minimum project size (Based on Clutch): 

$5,000

10. Directive Consulting

Directive Consulting is a B2B marketing agency founded in 2013, with offices in Orange County, Austin, New York, London, Toronto, and Mexico City. It works exclusively with companies in three verticals: technology, professional services, and industrial.

Source: Directiveconsulting.com

Its paid media stack covers Google Search, Bing, LinkedIn, Facebook, Google Display Network, and programmatic display and video. It also runs international campaigns across EMEA and APAC, which you’ll need if you’re expanding across markets.

The Directive Consulting framework, DiscoverabilityOS, is built around a single premise: MQLs and traffic are the wrong things to optimize for. 

Instead, every campaign decision is anchored to LTV:CAC, which relies on a single metric: is the cost of acquiring this customer justified by what that customer is actually worth over time?

To better track this metric, the agency built a proprietary AI-powered tool called Stratos. Strategists use the AI tool to:

• Pull together data from across the stack—Google Ads, LinkedIn, HubSpot, Salesforce, ZoomInfo, Gong, SEMrush, and more—into one place. Instead of waiting for end-of-month reports, strategists can immediately see trends and act on them.
• Automate repetitive work (keyword research, reporting, early-stage copy drafts) so the strategists spend more time on strategy than admin.
• Use natural language prompts to identify the shared characteristics of high-value customers and find others like them.
• Enrich known accounts with additional firmographic and behavioral data.

Over time, the platform has become sharper, fueled by the $2.2M Directive invests annually in marketing R&D.

Here are the service offerings this methodology powers:

Services:

• Paid search (Google and Bing) and social (LinkedIn and Facebook)
• Programmatic advertising
• Account-based marketing (ABM)
• Content marketing and SEO
• Revenue operations (RevOps)
• Lifecycle and influencer marketing
• Organic social media
• Public relations (PR)
• Performance reporting and analytics

Here’s a closer look at what each service entails:

Who is Directive Consulting for?

Directive Consulting operates on a scale far beyond that of most PPC agencies. Its client roster—which includes companies like Adobe, Cisco, Calendly, ZoomInfo, and Gong—gives you a clear picture of whom it’s built to serve. 

Its model is designed for companies with large budgets and market scope.

For that reason, it’s a great fit for teams running complex campaigns that cut across multiple markets. But a mismatch for lean teams that need tight, direct access to the people running the account.

Take a closer look at who the agency does and doesn’t serve:

Minimum project size (Based on Clutch): 

$5,000

11. PipeRocket Digital

PipeRocket Digital is a B2B SaaS marketing agency specializing in GTM strategy, SEO, performance marketing, marketing ops, and content marketing. Its paid media runs across Google Ads, LinkedIn Ads, Meta, and programmatic channels.

Source: Piperocket.digital

Praveen Ravi and Kamaraj Mathiarasan, PipeRocket’s co-founders, spent years on the client side of SaaS before starting the agency in 2023. That experience shapes how they work. 

Rather than running generic campaigns and reporting on traffic, PipeRocket builds its engagements around a three-stage process: 

• Understand the product, ICP, competitive landscape, and which channels your buyers actually use.
• Execute campaigns across the right channels, built around that research, not templated from a previous client.
• Continuously test and refine until the results are sustainable, not just present in month one.

Each step is treated as a prerequisite to the next, rather than as a box to be checked during onboarding. PipeRocket has applied this process across 50+ SaaS brands, managing over $5M in ad spend along the way.

For teams using HubSpot, Salesforce, or Marketo, the agency integrates your PPC ad platform directly with your CRM, to simplify revenue attribution.

PipeRocket deliberately limits new client intake to one or two per month. That sounds like a constraint but it actually signals that the agency would rather do fewer things well than overcommit and produce subpar results.

Services

PipeRocket’s services include:

• SaaS PPC (Google Ads, LinkedIn Ads, Meta Ads, programmatic)
• SaaS SEO
• Marketing operations (MarkOps)
• Content marketing
• Go-to-market (GTM) strategy

Here’s how each service matters for SaaS.

Who is PipeRocket for?

PipeRocket works with B2B SaaS companies at any stage, from early-growth to scaling. However, it is only a strong fit for teams that want PPC managed alongside SEO and marketing ops under one roof.

Minimum project size (based on Clutch): 

$5,000+

12. Team 4

Team 4 is a B2B SaaS marketing agency based in London, specializing in inbound. It works exclusively with startups and scale-ups in niche verticals such as AI, fintech, HR tech, edtech, climate tech, and legal tech. 

Source: Team4.agency

Although Team 4 runs PPC campaigns (Google Search, LinkedIn, and Meta), it always runs them alongside SEO, targeting the same keywords across both channels. 

The thinking behind this position is that making paid a major lead acquisition channel is unsustainable over time. Once the ad budget runs out, it stops working. 

So, before scaling spend, Team 4 uses SEO to identify which keywords and messaging actually convert and what an allowable cost per lead looks like. PPC then amplifies what’s already working, rather than funding guesswork at scale. 

That way, every dollar of ad spend goes toward what’s more likely to work, rather than failed experiments.

To keep iteration fast, the agency also offers fully managed landing pages as part of the service, built and hosted by its in-house team. When a page needs to change mid-campaign, the team handles it directly instead of waiting on a third party.

Let’s take a look at Team 4’s other services next.

Services:

• PPC and paid media (Google Search, LinkedIn Ads, Meta for retargeting)
• SEO and organic search
• Webflow design and development
• Inbound marketing
• LLM and AI search optimization
• Content marketing
• Digital marketing strategy

Who is Team 4 for?

Team 4 works primarily with B2B SaaS brands spending at least £3,000 (approximately $4,400 at current rates) per month on marketing. They typically fall into either of two groups:

• A startup or scale-up that doesn’t yet have a dedicated inbound team and needs to build one. 
• A marketing team with a large headcount, but without the specialist expertise to handle PPC.

Early-stage startups that haven’t yet validated product-market fit and larger enterprises that need a full-service agency are unlikely to be a good fit.

Below is a more detailed breakdown of Team 4’s eligibility criteria:

Minimum project size (Based on Clutch): 

Team 4 doesn’t publish pricing on Clutch, but its website states that it typically works with companies spending at least £3,000/month on marketing. Add a typical agency retainer on top of that, and the total monthly commitment is likely closer to £7,000–£8,000. 

However, it’s worth confirming this directly with the agency before coming to a conclusion.

How to Choose a PPC Agency

To choose a PPC marketing agency for your business, follow these steps:

• Match the agency to your stage: Early-stage companies and scaling companies have fundamentally different needs. Most agencies are better at one than the other. Before evaluating anyone, be honest about where you’re actually at, and confirm how they adjust their process to fit your current stage.
• Ask how they measure success: Almost every agency claims to track revenue, but few explain how. Find out by asking the right questions. Does the agency report on cost per SQL or cost per opportunity, not just cost per lead? Can it connect closed/won data from your CRM back into the ad platforms? How does it calculate the CAC payback period?
• Review SaaS-specific case studies: Ask for results from B2B SaaS clients, preferably in your category, at your price point, and with your sales motion (PLG vs. sales-led). Case studies that cite SQL volume, pipeline generated, and CAC improvement would be better, since those numbers are harder to fake.
• Check channel depth, not just channel breadth: It’s best to find an agency that handles the channels that matter most to your buyers specifically, instead of focusing on broad channel coverage. For example, to confirm an agency’s depth in Google Ads, you could ask it to walk you through how it structures a Google Search campaign for a B2B SaaS product specifically. How does it separate branded, non-branded, and competitor terms and handle match types?
• Understand the pricing model before the first call: Learn about the agency’s price structure and what that entails. You should also check for ad spend fees and what happens if there are no results. 
• Confirm the reporting and CRM attribution stack: Regardless of the channel it uses, the agency should be able to connect ad spend data to your CRM. Without this, your ad platforms will be optimizing toward form-fills and attribution will only cover vanity metrics such as clicks and impressions.

Wrapping Up

Every agency on this list runs paid media. What separates them is what they optimize for, how they measure it, and who they’re actually built to serve.

For example, if you’re Series A or beyond with a minimum of $15K/month in ad spend and want campaigns tied directly to revenue, AdConversion is worth the conversation. Whereas if you’re scaling across multiple markets, Directive Consulting might be worth a look.

The right agency for you shouldn’t only have a list of impressive clients and service offerings. Its operating methodology should match your growth stage, budget, and how buyers in your industry make decisions.

Frequently Asked Questions (FAQs)

Check out these answers to questions we get from most B2B SaaS brands looking for a PPC agency:

Are SaaS PPC agencies worth it?

Yes, if you have a clear ICP, a functioning sales process, and enough ad spend to justify the management fee. Without those in place, you’ll likely burn through budget without seeing meaningful returns, even if the agency is really good. Conversely, when they are in place, a great SaaS PPC agency simply comes in to scale what’s working and cut down what’s not.

How long until PPC works for SaaS?

In our experience, we use the first 30–60 days to gather sufficient data to learn what the algorithm rewards and continuously improve the campaign. Once that’s done, we typically start seeing results 30 days later (90 days or three months after we launched the campaign).

Which channels matter most for SaaS?

At the top of the list is Google Search; even with the advent of AI, buyers still search for SaaS companies on Google. LinkedIn is the next on the list for SaaS companies that already have an ICP with a clearly defined job title and company size, and a marketing budget to cover the higher CPCs. Lastly, G2, Reddit, and Capterra are great ways to reach buyers actively comparing vendors.

The post Best SaaS PPC Agencies: Top 12 Partners for Pipeline Growth in 2026 appeared first on Marketing Experts Hub.

However, some truths exist.

In this article, Antonis Dimitriou, Organic Growth Strategist at Omniscient Digital shares his tiered list, based on his experience working with SaaS and Enterprise clients. These beliefs are supported by various studies across the web.

The article was edited by Nick Malekos, the founder & editor of Marketing Experts Hub.

The Tiered List

S Tier

Tactics with strong evidence and effectiveness towards ranking of AI Search, and are the most important factors LLMs will use to surface citations and mentions.

• Building brand mentions with co-occurring terms
• Targeting queries plus modifiers
• Consistent brand positioning

A Tier

Tactics which strongly impact AI Search results.

• Link building
• Targeting fan-out queries
• Homepage messaging

B Tier

Often used for citations and influencing the AI Chatbot’s answer to a query, but not always effective.

• Reddit mentions
• YouTube videos

C Tier

Impactful up to a point, for specific cases.

• Schema

D Tier

Possibly impactful, there is evidence crawlers related to LLMs visit the pages, and sometimes mention them, but not as impactful.

• Creating an AI info page

F Tier

Often recommended by agencies, but with little evidence of impacting AI Search.

• llms.txt

S Tier

These tactics teach models what your brand is, in relation to what, for whom. This is what the systems reach for when they decide who to cite and who to show up in responses.

Building brand mentions with co-occurring terms

This is the single highest-leverage thing you can do, and most teams do a diluted version of it.

Models learn associations from the text around your brand name, not from the name in isolation. If your brand keeps appearing beside “SOC analyst training” or “sales engagement platform” across enough independent sources, that association becomes stronger, and LLMs learn to associate it with it.

Pick the three to five terms you need your brand welded to. Then create mentions which carry those terms in the same sentence or paragraph: podcast show notes, roundup contributions, expert quotes, partner pages, community answers, comparison posts on third-party sites.

Targeting queries plus modifiers

Buyers do not ask LLMs one-word questions. They ask long-tail ones. For example “Sales engagement tool with HubSpot integration and SSO for enterprise.”

Build your target list from modifiers, not keywords. Pull them from your own sales calls, your G2 category filters, your competitor comparison pages, and your Search Console long tail. Then create pages that answer the head term plus the modifier explicitly and completely, in the page’s own words, high on the page.

Consistent brand positioning

This a company-wide problem and usually sits under PMMs or Brand. Consistency of how the brand is represented creates stronger associations and assists retrieval for niche cases.

Vague and varied responses create confusion and your brand will get replaced with a competitor who was clearer.

Write one positioning line. Use the same text everywhere: site, review profiles, LinkedIn company page, partner directories, press boilerplate, podcast intros, guest bios.

Enforce consistency on a company-level.

A Tier

These strongly impact AI search results, and the evidence behind them is solid. They sit one step down because they work by improving the conditions for visibility rather than by directly teaching a model what you are.

Link building (Digital PR)

Links got rebranded to Digital PR and citations. Backlinks still matter, even if they are unglamorous by building the authority and connections required for discovery.

The essentially improve the conditions and chances, but do not directly impact HOW you are being mentioned.

Targeting fan-out queries

AI Mode and similar systems decompose a query into sub-queries, run searches based on them, and synthesise the results. Those sub-queries are called fan-out queries.

Fan-out tactics target the use-cases, niches, and different ways people may search, and are informed by the memory of the chat for you. You can’t easily “know” what fan-out queries are, but much research shows the structure they take and can be replicated when doing SEO research.

Homepage messaging

Your homepage is the highest-authority page telling models what you are. Treat it as a primary source document, not a conversion asset with a hero image and three adjectives.

If your H1 is a slogan and your subhead is a benefit statement, there is nothing concrete to extract. If it names the category, the buyer, the core capability and the differentiator in plain text, then LLMs understand what you actually do.

LLMs prefer usability over brand statements.

B Tier

Both of these show up in citations regularly and both may decide what content is being used in the decision-making process.

Reddit mentions

Reddit is heavily cited by several AI search systems.

Active participation is the best way to get Reddit mentions, while many SEOs tend to try manipulative and automated tactics.

Use it with caution.

YouTube videos

Very good for Google’s AI search surfaces.

Video assets get surfaced in AI Overviews and adjacent Google experiences, so if Google is your primary target, then it’s own video platform is the right source to train.

C Tier

Impactful up to a point, but may not work for all kinds of businesses and niches. Use when needed.

Schema

Structured data helps Google understand entities and can support your presence in Google’s AI surfaces. Product, Organization and FAQ markup are the best ones to use overall, and they help to get various rich results on Google, they may as well help with AI Overviews.

What it does not do is affect visibility in non-Google LLMs like Claude, ChatGPT, Perplexity etc.

D Tier

Possibly impactful, there is evidence crawlers related to LLMs visit the pages, and sometimes mention them, but not as impactful.

Creating an AI info page

There is something here, but pretty uncertain. The problem is that it’s probably not needed, but crawlers still visit the page with little evidence it works.

Editor’s note: I strongly believe that a well written Home, About, and Contact pages are more than enough for the purpose, an AI info page may not be a complete waste of time but it probably does little more than a blog post or a product page.

F Tier

Often recommended by agencies, but with little evidence of impacting AI Search.

llms.txt

Many SEOs, consultants, and agencies implement llms.txt, but as proven by cats.txt, a fun experiment by Mark Williams-Cook, even an irrelevant page will be crawled and cited.

No major AI search system has committed to consuming it as a ranking or retrieval input. It has not been adopted the way robots.txt or sitemaps were, and publishing one has no demonstrated effect on whether you appear in AI answers. It is a proposal with strong marketing behind it, and it survives mostly because it is easy to sell and easy to tick off.

How to sequence this

Tiers S to A are actions which must be in everyone’s to-do list, while actions B and C depend per case and resources.

The rest are pretty much optional.

But, each tactic can support a wholistic SEO / GEO / AEO strategy to rank for search and various AIs.

The post The Top AI Search Optimization Tactics Ranked in a Tier List appeared first on Marketing Experts Hub.

Back then, I was the founding marketer at LearnWorlds, and one of my main resposibilities was SEO who became my main focus and growth channel over the next few years.

For the next year, we built what was going to be our biggest inbound channel that quadrable results over the Covid time (2020-2021).

I actually included it in a speech earlier this year as well, you can view the whole growth-marketing story at LearnWorlds here.

Now, as the Head of Demand at Cyberbit, SEO is again my responsibility, and I have hired Minuttia again to run the new playbook of SEO.

What Is Minuttia?

Minuttia, led by George Chasiotis, is a content marketing and SEO agency for B2B SaaS companies.  

Image Source: minuttia.com 

When LearnWorlds signed on in 2019, our engagement focused on services designed to close our organic visibility gap and fix the underlying issues affecting our content performance.

The core services offered included:

• SEO strategy: Keyword research and audience mapping tied to our buyer’s journey 
• Content strategy: A full audit of our existing content to decide what to update, merge, or remove 
• Content optimization: Refining underperforming pages instead of only producing new ones 
• Link building: Earning backlinks from domains with real authority and topical relevance 
• Technical SEO guidance: Walking our team through fixes for indexation issues 
• Content operations: Establishing briefing processes and training our writers on new methodologies

Minuttia has since expanded its services to include AEO, GEO, and AI SEO. This is the work I am hiring them now to help with, along with traditional SEO.

Why Did LearnWorlds Hire Minuttia?

When we hired Minuttia, LearnWorlds focused on four growth levers – Organic SEO, Paid Social & Google, Email marketing, and affiliates.

Organic from Google was our best channel, followed by paid, but our budget was limited there. So, Google organic traffic seemed like a good bet and better ROI to focus, especially because I built a strong content team.

SEO was doing well, but we were hitting some walls on growth and passed through a period of flat growth. We needed a fresh approach and a new bet to grow to the next level.

Challenges LearnWorlds was facing

Before we hired Minuttia, our content team was split in multiple projects, and we were losing focus. We needed someone who would own and lead our strategy, kept us honest, and add additional analysis which I didn’t have enough time to do:

• Content calendar was there but lacking SEO depth: We were publishing and following SEO best practices, but not really documented or fully procesized.
• A competitive gap: Our strategy was focused too much on top and middle of the funnel, and little bottom of the funnel. Honestly, I needed an extra argument to convince a resistant management that competitive listicles were important.
• No content operations: There was no established process for briefing writers. This meant that our content quality and consistency depended on impulse decisions over a process.
• Technical issues: My technical SEO was not my strong point, so a few technical SEO errors crept in the way.
• Reporting was lacking: Reports were not convincing on results, I needed help in developing the right reports and explain the wins to the management.

These issues needed a result-driven SEO and content marketing agency that could diagnose the whole system, not just produce more articles. 

How LearnWorlds evaluated agencies

We didn’t sign with the first agency that pitched us. We reviewed a few local and a few international agencies, and came upon the one that seemed more trustworthy.

Minuttia, and specifically George was chosen because the pricing made sense and we saw a strong culture fit”

• Attention to detail
• Good people we could trust
• Hard-working mindset, going above & beyond to deliver (since the selection process, yes)

Since working with them in multiple projects side-projects, and hired them in two companies, their communication, processes, and work has improved. Delivering high-quality work, going above & beyond, and being professional along the way.

Second impressions of the Minuttia team

Here, I want to intercept the LearnWorlds story, to talk about the second hiring here at Cyberbit. As our AI Search budget was approved recently and I had to review 3 agencies before going with our top choice (again).

How the second time felt in 2026 was very different than 2019.

• More professional process
• Better pitch-deck with in-depth details on the plan
• Better understanding of tech, and cybersecurity
• Incredible onboarding*

*The process of asking the right access, brand collateral, and company tone of voice – they know how to work for bigger corporations & enterprise who are demanding.

To avoid any conflicts of interest, I reviewed and compared three agencies with great reviews. I will not be naming those, as they are great SEO Agencies and they came very close to winning the bid, it would not be fair to underplay the competition.

The decision was approved both by the CMO & our Content Lead after multiple rounds of talks and project discussion.

What Did Minuttia Do for LearnWorlds?

Once we signed on, Minuttia offered six connected strategies: 

• Audience research
• Content audit and optimization
• Content strategy and planning
• Link building strategy
• Technical SEO guidance
• Content workflows and team training

Here’s how they actually played out:

Audience research

Minuttia didn’t start with content, but with the people who’d eventually read it.

The team researched LearnWorlds’ target audience and identified the specific sources and topics that influenced potential customers before they ever reached our site. 

From there, they conducted keyword research and mapped every search opportunity to a stage in the buyer funnel, so we knew whether a keyword mattered to someone just discovering online course platforms or someone ready to compare software.

Each keyword also got an Opportunity Score, which allowed the team to prioritize based on real potential. That research turned directly into a practical content calendar we could execute against.

This is a collaborative effort, as my side of the equation (as an in-house marketer) is to pass industry knowledge and company-specific details to support the agency.

Minuttia built up on it to develop a more in-depth version only a dedicated specialist with access to more data can do.

Content audit and optimization

With the research in place, Minuttia turned its attention to the content we’d already published.

They reviewed our entire content inventory and came back with a specific recommendation for every page: update it, consolidate it with overlapping content, or remove it because it no longer served a purpose. 

The audit also flagged user experience issues affecting how visitors engaged with our existing pages, and it prioritized the pages with the greatest growth potential first.

Minuttia gave me the clarity and plan needed to focus. They “owned” organic, so I could work with the ten other open projects we were running at the same time. A trusted partner I could spend a few hours a week and delivered results, almost on auto-pilot (of course you need to be deeply involved to succeed, don’t get me wrong, it’s a two-part collaboration, always).

Content strategy and planning

The audience research and content audit fed directly into how Minuttia chose new topics to prioritize.

Topic selection balanced search demand against actual business relevance, so we weren’t chasing volume for its own sake. 

The resulting strategy covered multiple stages of the buyer journey, from early awareness content to pages built for people actively comparing platforms. All of it rolled into the content calendar, which gave our team a systematic plan.

The most important part though is working with most of our capacity on the bottom-funnel capturing demand from the market.

Link building

Once content strategy was underway, Minuttia moved into link building.

The focus stayed on relevant, authoritative domains rather than volume for its own sake. Interestingly, those links directly supported the broader organic strategy by helping close the domain rating gap we had against competitors. 

Over the engagement, that work produced 77 new backlinks from sites with real authority in our space.

Of course, we had a mix of tactics on link-building.

• ABC link-building handled-inhouse
• Targeted outreach (high valued links from relevant sites)
• Linkable assets – attracting links passively

Honestly, the best tactic for long-term businesses is linkable assets, but that produces results in 2-3 years, with the highest ROI. If you are building a resilient business, build assets, studies, and own-data pages people will link to.

Technical SEO guidance

Minuttia also identified the indexation issues that were limiting how much of our site Google could crawl and rank.

Recommendations came with clear, step-by-step guidance rather than a black-box fix. In addition, Minuttia worked directly with our internal team so we understood what was wrong and how to resolve it ourselves.

Errors we had for a while and could not figure out how to solve started to resolve with the help of Minuttia’s briefs.

The most difficult part was pitching it and adding it on our developers’ queue… but that’s another story!

Content workflows and team training

Minuttia helped us build a real content-briefing process where none had existed before, which created more consistent workflows across the whole team. 

They trained our internal content team directly and shared the methodologies behind their own work.

We saw a significant quality difference, and many lessons and SOPs stayed for years with us, only partially updated.

What Was It Like to Work with Minuttia?

Here’s what the actual working relationship looked like from our side:

Communication and responsiveness

Not sure if it’s the standard nowadays, but the best agencies I have worked with come with great communication practices.

A slack channel for updates / communications.

Email for the most important things.

Responsive team, and fast coordination.

There are always hiccups of course, the idea is to have an adaptive team who can take over and quickly return.

Professional, communicative, and strong project management is essential.

Expertise

Strategy only holds up if the people behind it actually understand the business they’re working on.

I take this as my responsibility. Minuttia knew SaaS, but EdTech was new to them, as is Cybersecurity now.

It took a short time ~3 months for them to get a strong hang of the industry and nuances.

Compared to my next “premium” agency, where their analysts after 1.5 years never got the nuances or my feedback…

Now, having worked and discussed multiple projects, I have to admit their expertise especially in tech companies, SaaS, and enterprise is much improved.

Back then, Minuttia was perfect for a SaaS startup.

Now, Minuttia is perfect for an enterprise company.

Transparency

Minuttia does not mince its words.

They are honest around expectations and what can be realistically achieved. I prefer an honest outlook, over over-promisers.

That realistic expectations paired with regular, honest reporting helped prove the results to management.

What Did LearnWorlds Get from the Cooperation with Minuttia?

Nine months into the engagement, the results showed up in numbers we could report directly to leadership.

Organic traffic grew by 123.7% month over month, driven by a combination of new content built off the audience research and updates to pages that had been losing ground before the audit.

Image Source: Ahrefs

I have said it many times. One of the reasons LearnWorlds grew fast around 2020, was because we had delivered 80% of the organic content plan we planned with Minuttia before it hit.

We covered most important commercial queries.

When e-learning surged in Covid, we were there, well-positioned to capture the traffic.

We were ready, at the right time.

Of course, many more things happened – the team was growing, the budget was growing, engineering delivered some important items. It was a team effort, but SEO captured the traffic.

The number of keywords we ranked for increased by 51.7%, spread across new and updated content in high positions in our target market. Updates were always a big part of LearnWorlds’ content strategy, as keeping up high with our top content has always been important.

Image Source: Ahrefs

The link building work added 77 new backlinks from authoritative, relevant domains, which helped close the domain rating gap that had been holding our content back from ranking as well as it should have. 

Image Source: Ahrefs

The traffic and keyword numbers show the big numbers, the reality was however the operational changes which impacted the long-term.

Our content briefs became more detailed and consistent, and production followed an actual process instead of ad hoc decisions made week to week. 

Writers produced first drafts faster, our internal team’s SEO knowledge grew, and we had a clearer system for prioritizing which content to tackle next.

Those changes outlasted the engagement itself. The traffic numbers reflect nine months of work. The processes and internal capability are still paying off today.

What Does Minuttia Offer Now? 

The agency I worked with in 2019 and 2020 focused almost entirely on traditional SEO, i.e., keyword research, content strategy, link building, and technical fixes aimed at ranking well in Google.

Minuttia’s services today cover more ground. Alongside Google search strategy, the agency now works on dominating AI search platforms like ChatGPT and Perplexity, human and AI-assisted content creation, digital PR, and even Reddit marketing as a way to influence how brands get mentioned in AI-generated answers. 

There’s also a reporting tool built specifically to track how AI systems discover and cite a company’s content, something that didn’t exist as a category when LearnWorlds signed on.

The core positioning hasn’t changed. What Minuttia does with it has expanded to match how people actually search now.

Why We Ended the Partnership

2020 was an incredibly busy year, and we were behind in our content plan.

For what we did, we had a queue for a whole year to cover in deliverables to be done from our internal team.

We paused Minuttia until we covered some ground.

Then, our Series A took place, and the VC dictated their own agency – which I was not happy with… but the money talks.

Starting the New Project

For 1.5 years I went freelancing, where we collaborated with Minuttia on a few side-projects.

And, now in my new company one of the most important agency “hires” is Minuttia, which we were budgeting since last year. Internal changes delayed the project, as we focused on migrations & fixing other channels.

Now, we are betting on SEO & AI Search to be the next ROI-positive channel.

Final Verdict

Last time, ROI from SEO was 10x-20x (depending on month & spend, it was quite variable). SEO was an easier channel, and we were well-positioned for it.

A few lucky moments helped with capturing traffic.

Minuttia delivered on what LearnWorlds needed most, and that’s a real strategy behind our content.

Over nine months, that translated into 123.7% growth in organic traffic, a 51.7% increase in ranking keywords, and 77 new backlinks from authoritative sites.

Just as important, our internal team came out of the engagement more capable, with processes and skills that outlasted the contract itself.

This isn’t a hands-off arrangement, and it isn’t the cheapest option available. But if you want an SEO and AEO agency that treats your business like theirs, Minuttia is worth a conversation.

I am paying a trusted partner.

I know my investment will have ROI.

And, I know their values align with my team’s values.

The post Minuttia Review: My Experience as a Client appeared first on Marketing Experts Hub.

It is not.

You copy a pattern, paste it into one filter, and GSC does work that used to mean exporting to Sheets.

You do not need to be technical. If a pattern needs tweaking, describe what you want to any current AI model and ask it for RE2 syntax that works in GSC.

Any model does this well now, so there is no need to pay for a specific one.

How to Use This Guide

There are two ways to use what follows.

1. Copy a pattern straight into GSC.
2. Or take one as a starting point and swap the words inside it.

Every pattern goes into the Performance report.

Open the report, add a filter, choose Query or Page.

Then pick the Custom (regex) option. Set it to Matches regex to keep what fits the pattern, or Doesn’t match regex to exclude it.

How Regex Actually Behaves in GSC

*Skip this section if you just want to copy-paste some Regex.

GSC runs on RE2, Google’s own regex engine. It behaves differently from the regex you copy off Stack Overflow. Five rules cover most of the pain.

• Query data is lowercase. Capitals in a query pattern match nothing. Prefix with (?i) out of habit and stop thinking about case.
• Matching is partial by default. Your pattern matches anywhere in the string unless you anchor it with ^ for the start or $ for the end. You rarely need .* wrappers.
• Use word boundaries. Without \b, the pattern can matches “scan”, “candle”, and “cancer”. Adding \b fixes it.
• No lookaheads, lookbehinds, or backreferences. RE2 does not support (?=...), (?<=...), or \1. Patterns that use them fail, usually with no error and no data. For “not this”, use the “Doesn’t match regex” option instead of a negative lookahead.
• An empty report usually means a broken pattern, not no data. Test in Regex101 with the flavor set to Golang, which uses RE2.

Brand vs Non-Brand

This is my favorite regex, and the one I reach for first. It splits your queries into branded and non-branded, so you can see brand lift from a launch or a seasonal dip without guessing.

Build one pattern that holds your brand, its spelling variants, and its common misspellings.

(?i)(yourbrand|your brand|yourbrnad|common misspelling)

Replace the placeholders with your actual terms. For a brand like Microsoft it might look like this:

(?i)(microsoft|micrsoft|mircosoft|microsft|msft)

The fastest way to build a complete version:

• Filter your queries to your homepage.
• Export the queries and sort by clicks.
• Pull out the branded terms and misspellings.
• Paste them into an AI model and ask for a GSC-ready RE2 pattern.

Then use it two ways.

Branded Queries: Set the filter to Matches regex to see branded demand.

Non-Branded Queries: Change to Doesn’t match regex to see everything else, which is your non-brand universe.

GSC Built-in Brand vs Non-Brand

Since last year, Google Search Console includes a Branded and Non-Branded queries functionality, but I have found it to be lacking sometimes.

Use regex when you want to include or exclude specific variations of branded terms.

Long-tail Questions for AI Search

Question queries are the most common query fan-outs for AI search. These are the queries where a direct, well-structured answer wins the citation.

(?i)^(who|what|where|when|why|how|which|can|do|does|is|are|will|should)\b

Short questions are hard to rank for. Narrow to the long-tail versions, eight words or more, where the intent is clearer and the competition thinner:

(?i)^(who|what|where|when|why|how|which|can|do|does|is|are)\b(\W+\w+){7,}

*Change the number at {7,} for questions with more or less words. For example, conversational strings that show how AI-era search behaves, ten words or more:

^(\w+\s){9,}\w+$

Change the 9 to test other lengths. Push it much higher to isolate the unusually long, structured queries that can point to AI-assisted or machine-generated searches:

^(\w+\s){31,}\w+$

\w skips apostrophes, so contractions nudge the word count. Treat it as a cue to investigate.

Short-Tail and Long-Tail Queries

Word count is a fast proxy for intent and difficulty. Short queries are broad and competitive. Long queries are specific and easier to win.

Short-tail, one to four words:

^(\w+\s){0,3}\w+$

Long-tail, eight words or more:

^(\w+\s){7,}\w+$

Change the numbers to move the threshold wherever you want to test.

Intent Filters

Group your queries by what the searcher wants to do. Each of these goes in the Query filter. Together they turn a flat query list into a funnel.

Commercial and comparison (people weighing options):

(?i)\b(best|top|alternative|alternatives|vs|versus|compare|comparison|review|reviews|cheapest)\b

You can see my commercial intent queries using the same regex in the example above.

Local intent (people looking nearby):

(?i)\b(near me|nearby|near by|closest|close to me|in my area|open now)\b

Price and buying intent (people close to a decision):

(?i)\b(price|pricing|cost|how much|cheap|cheapest|discount|coupon|promo|deal|free trial|buy|for sale)\b

Content format (the shape of answer they want):

(?i)\b(template|checklist|cheat ?sheet|pdf|download|spreadsheet|calculator|generator|tool|example|guide|tutorial)\b

Year and freshness (people who want current information, and your cue to refresh a page):

\b20\d{2}\b

Countries and Languages (International SEO)

If you run a large multi-regional site, you have several solutions of monitoring Search results. You may need to have separate GSCs per region / language (using subdomains or foldering).

But, if you have a single Google Search Console for an international site, Regex can save you while looking for specific countries.

Regex runs on the Query and Page filters only, never on the Country dimension. For where the searcher is located, use the built-in Country filter.

To use Regex, you will need to look at the URL – subdomains or foldering sections. An example targeting German visitors:

de.mysite.com

or

mysite.com/de

Per-market performance by URL section

If your site folders by country or language, a Page regex isolates each market. Page matching is case-sensitive, and dots need escaping.

Subfolders on one domain:

^https://yourdomain\.com/(es|fr|de|it|pt|nl|pl)/

Any locale folder, wherever it sits in the path:

/(es|fr|de|it|pt|pt-br|en-gb|en-us)/

Locale subdomains:

^https://(es|fr|de|it)\.yourdomain\.com

Use ISO alpha-2 codes to match your own structure. To compare one market against everything else, run the same pattern with Doesn’t match regex.

Ready-made geo groupings

Three groupings people reach for most, each as one Page filter. Codes are ISO alpha-2. Fold by country and these pull the whole region in a single view.

Europe (the EU plus the UK, Switzerland, and Norway):

/(at|be|bg|hr|cy|cz|dk|ee|fi|fr|de|gr|hu|ie|it|lv|lt|lu|mt|nl|pl|pt|ro|sk|si|es|se|gb|uk|ch|no)/

Tier 1 (the wealthiest, highest-CPC markets, straight from the Tier 1 countries list):

/(au|at|be|ca|dk|fi|fr|de|ie|it|lu|nl|nz|no|es|se|ch|gb|uk|us)/

APAC (major Asia-Pacific markets):

/(au|nz|jp|cn|hk|tw|kr|sg|my|id|th|ph|vn|in|pk|bd|lk)/

Anchor any of them to your domain, and for language-region folders like /en-us/ or /de-ch/, match the region on the end:

^https://yourdomain\.com/(au|at|be|ca|dk|fi|fr|de|ie|it|lu|nl|nz|no|es|se|ch|gb|uk|us)/
/[a-z]{2}-(au|at|be|ca|dk|fi|fr|de|ie|it|lu|nl|nz|no|es|se|ch|gb|uk|us)/

Three notes before you paste:

• gb is the ISO code for the United Kingdom, but many sites use /uk/, so both are in the patterns.
• Bare two-letter codes are greedy. /it/ catches Italy and an IT section, /in/ catches India and an “in” folder, /id/ catches Indonesia and an id folder. Test against your real URLs first.
• Want Tier 2 and Tier 3 as their own filters? Build them the same way off the full country tier list.

Geo-modified query intent

Different job. These catch searches where someone types a place into the box, like “crm software germany” or “melhor crm brasil”. Set the filter to Query and use (?i) because query data arrives lowercase. Include native spellings and unaccented variants, because people type both “españa” and “espana”. You can rebuild any of the three page groupings above as a query filter by swapping the ISO codes for country names.

North America:

(?i)\b(usa|u\.s\.a|united states|america|canada|mexico|méxico)\b

South America:

(?i)\b(brazil|brasil|argentina|colombia|chile|peru|perú|venezuela|ecuador|bolivia|paraguay|uruguay|guyana|suriname)\b

Spanish-speaking countries:

(?i)\b(espana|españa|mexico|méxico|argentina|colombia|chile|peru|perú|venezuela|ecuador|guatemala|cuba|bolivia|dominicana|honduras|paraguay|salvador|nicaragua|costa rica|panama|panamá|uruguay)\b

Portuguese-speaking countries:

(?i)\b(brasil|brazil|portugal|angola|mocambique|moçambique|cabo verde|guine|guiné)\b

One caveat, and it matters. Most local searches do not contain the country name. Someone in Spain searches “zapatos”, not “zapatos españa”. So this catches explicit geo-modified demand only, a slice, not the whole market. For true market performance, use the Country dropdown or the Page patterns above.

Product IDs and SKUs

For ecommerce, regex lets you track a series of products even when they sit across many URLs. Say your IDs look like A123, PR097, or ABC234. This pattern finds them:

^(A\d{3}|PR\d{3}|ABC\s?\d{3})$

Use it in the Page filter. Change the letter prefixes and digit counts to match your own SKU structure. The same idea groups any related set of pages: colors, clothing types, or content categories like guides and templates.

Misspellings

Misspellings work like the brand pattern, but for non-branded terms. Collect the variants you see in your query report, or ask an AI model for the common misspellings of a target word, then wrap them in one pattern.

(?i)(definately|definitely|seperate|separate|recieve|receive)

Swap in your own set. This surfaces demand you are quietly ranking for and shows where a corrected on-page mention could pick up easy impressions.

Make Some SEO Magic

These are a fraction of what regex can do inside Search Console. The point is not the patterns themselves. It is that a couple of minutes of setup replaces a routine you have been doing in Sheets. Branded versus non-branded, question demand, buying intent, and market-by-market performance are all one filter away.

A few of the patterns I used while updating the article were inspired by Amy Lynch‘s carousel, Head of SEO at Gravytrain.

The post Regex for SEO: A Guide for Non-Tech SEOs to Copy appeared first on Marketing Experts Hub.

The right alternative depends on what’s pushing you away: open-source engines like Meilisearch and Typesense for cost and self-hosting, Elasticsearch for raw scale, and Prefixbox for e-commerce merchandising.

Here’s how all 10 stack up, followed by a closer look at each.

Disclaimer: Digital Marketers World is an independent evaluation resource. The alternatives below are presented for informational comparison only. Verify current figures directly with each vendor before making a decision.

1. Meilisearch

Meilisearch is an open-source search engine written in Rust, built to match Algolia’s search speed and relevance without charging by the request. 

Self-hosting is completely free with the full feature set unlocked; there’s no gating between the open-source version and what you’d get on Meilisearch Cloud, including hybrid keyword-plus-vector search. 

Cloud is available for teams that want a managed option, with either simple usage-based tiers or resource-based billing for more granular control.

Image Source: meilisearch.com

Key functionality

• Hybrid search that blends keyword and vector search in a single query for semantic relevance
• Typo tolerance that works out of the box, with no configuration required
• Federated search across multiple indexes, merged into one ranked results list
• Faceted search, multi-tenant tokens for isolating customer data, and geosearch

Strengths

• Setup is genuinely fast; most teams get search running in a matter of hours, and integration with common frameworks tends to go smoothly without heavy customization
• Cost savings at scale are one of the most consistently cited reasons teams migrate over from Algolia, particularly once record counts or search volume grow
• Support response times are frequently described as fast and genuinely helpful, regardless of company size

Limitations

• The Cloud dashboard doesn’t currently integrate with tools like Datadog, so deeper performance monitoring may require external tooling
• Autocomplete isn’t generated automatically; building a dedicated suggestions index takes manual setup
• Recent pricing changes weigh index size more heavily than before, which can feel less favorable to teams with large catalogs but comparatively low search volume

Pricing

Self-hosted is free under the MIT license with the complete feature set. 

Cloud starts around $20/month generally, with a usage-based example running about $30/month for 100,000 documents and 50,000 searches, or a resource-based example around $23/month for a small (0.5 vCPU, 1GB RAM) instance; both scale via Meilisearch’s own cost estimator. Enterprise is custom-quoted and adds SAML SSO, SOC 2 compliance, up to 99.999% SLA, advanced analytics, personalization, dynamic search rules, and dedicated support.

Best for

Developers who want Algolia’s speed and simplicity without recurring per-search costs.

2. Typesense

Typesense is often described as the open-source alternative to Algolia and the comparison holds up. 

It mirrors much of Algolia’s developer experience (typo tolerance by default, fast indexing, an official adapter for Algolia’s InstantSearch UI components) while replacing per-search billing with resource-based pricing tied to cluster capacity (RAM and CPU). 

That means query volume never directly affects your bill, which is the main reason teams with spiky or unpredictable traffic tend to evaluate it over Algolia. 

Because the InstantSearch adapter exists, migrating teams can often keep their existing search bar, filters, and results screen exactly as users already know them, while swapping out the backend underneath.

Image Source: typesense.org

Key functionality

• Vector search alongside traditional keyword matching for hybrid relevance
• Query-time configuration that adjusts search, facet, and ranking fields via API parameters instead of requiring separate indexes
• Typo tolerance enabled by default, geo-search, and natural-language search that translates conversational queries into structured parameters using an LLM
• A search delivery network that routes queries to the nearest node for lower latency

Strengths

• Resource-based pricing means a properly sized cluster absorbs query volume without added charges, unlike Algolia’s per-request model
• Front-end integration tends to be smooth, especially for teams already using InstantSearch-style components
• Query-time configuration gives genuine control over ranking that Algolia’s fixed-index approach doesn’t offer

Limitations

• Built-in analytics are thinner than Algolia’s — there’s no native dashboard for search analytics, A/B testing, or click tracking, so you’d need to build your own or bolt on a separate tool
• Even on Typesense Cloud, you’re responsible for sizing RAM, vCPUs, and scaling configuration — Algolia’s fully managed model removes that decision entirely
• The surrounding ecosystem — pre-built integrations, third-party plugins, enterprise case studies — is smaller than Algolia’s, despite the InstantSearch adapter easing UI migration

Pricing

Self-hosting has no licensing cost beyond your own infrastructure. Typesense Cloud starts at roughly $7–$21.60/month for a small instance (0.5GB RAM, shared vCPU), scaling with additional RAM and dedicated vCPUs as the index grows. 

There’s no per-search or per-record charge, the inverse of Algolia’s model, though high-availability enterprise configurations can run past $1,000/month.

Best for

Teams with high or unpredictable query volume who want costs tied to infrastructure, not traffic.

3. Elasticsearch

Elasticsearch is the open-source engine most teams already know by reputation, and it solves problems Algolia simply isn’t built for: log analytics, multi-datacenter deployments, and complex aggregations across datasets running into the billions of documents. 

That power comes with real operational weight, though, someone on your team needs to manage cluster health, shard allocation, and version upgrades, which is a meaningfully different commitment than Algolia’s fully managed SaaS. 

Teams often compare it against Apache Solr or AWS-managed OpenSearch as well, since all three occupy similar territory for large-scale, self-managed full-text search.

Image Source: elastic.co/elasticsearch

Key functionality

• Distributed, horizontally scalable architecture designed for datasets that outgrow single-server search engines
• Deep aggregation and analytics capabilities well beyond faceted search, the same engine that powers much of the log-analytics and observability space
• Vector search and hybrid retrieval support, alongside traditional full-text search
• A vast plugin and integration ecosystem built over more than a decade of enterprise adoption

Strengths

• Handles scale that few alternatives on this list can match, from massive product catalogs to petabyte-scale log ingestion
• Highly customizable ranking and query logic, since you have direct access to the underlying engine rather than a fixed API surface
• A mature ecosystem of client libraries, visualization tools (like Kibana), and community knowledge accumulated over many years

Limitations

• Requires dedicated DevOps investment, cluster sizing, shard management, and upgrades aren’t optional maintenance; they’re ongoing operational work
• The learning curve is steeper than any of the other engines in this guide, particularly for teams without prior search or distributed-systems experience
• Cloud billing can become unpredictable at scale, since it’s driven by compute, storage, and data transfer rather than a flat rate

Pricing

Self-managed Elasticsearch is free and open source. Elastic Cloud runs on a pay-as-you-go model billed by the resources you consume, storage, compute, and data transfer, so actual monthly cost depends heavily on cluster size and region. 

It’s worth checking Elastic’s current calculator directly, since published rates shift by cloud provider and deployment tier.

Best for

Developer-heavy teams that need maximum customization, massive scale, and full control over infrastructure.

4. Manticore Search

Manticore Search is an open-source full-text and vector search database built in C++. 

If your stack already runs on MySQL, it feels less like adopting a new tool and more like extending what you already know, you query it with SQL instead of learning a proprietary API. 

Think of it as a self-hosted answer to Elasticsearch: similar performance characteristics, but you also take on the servers, maintenance, and control that come with owning your own infrastructure.

Image Source: manticoresearch.com

Key functionality

• Hybrid full-text and vector retrieval combined in a single query
• Support for both SQL and JSON query protocols
• Real-time indexing with no commit delay, and columnar storage for datasets too large to fit in RAM
• Multi-master replication for high availability, plus more than 20 full-text operators and ranking factors for fine-grained relevance tuning

Strengths

• Runs on minimal hardware, as little as one core and 1GB of RAM while still delivering solid performance, a sharp contrast to Algolia’s fully managed infrastructure you never actually see or control
• Has a long track record dating back to its SphinxSearch roots, with a reputation for balancing speed and simplicity in high-load, data-offloading, and CQRS-style systems
• Scales to genuinely large datasets, production deployments indexing around 100 million documents and 35TB of data have been reported while keeping the setup flexible

Limitations

• There’s no first-party managed cloud, so you’re either running your own infrastructure or relying on third-party hosting
• The surrounding ecosystem and plugin library are smaller than Algolia’s mature partner network, so some integrations may take custom work
• The AI/ML feature set is lighter than Algolia’s, vector search is capable, but it doesn’t match the depth of purpose-built commercial relevance tools like Algolia’s AI Ranking or dynamic re-ranking

Pricing

Manticore Search is free and open-source under the GPL-3.0 license with no usage-based charges, you pay only for your own infrastructure if you self-manage it. 

Third-party managed hosting (through providers like Elestio) starts around $11/month. Because GPL-3.0 carries different obligations than a standard commercial SaaS agreement, it’s worth a legal review before embedding Manticore in a commercial product.

Best for 

Teams already running MySQL-based infrastructure who want SQL-style access to their search layer.

5. SeekStorm

SeekStorm is a search-as-a-service API with an open-source core, built around one central question: how fast can search realistically go? 

The answer is a Rust-based engine that claims sub-millisecond query latency and real-time indexing with zero commit delay, a document becomes searchable the instant it’s added, not seconds or minutes later. 

You can run it as a hosted SaaS API (closer to how you’d use Algolia) or as a self-hosted open-source library if you want the code entirely in your own hands.

Image Source: seekstorm.com

Key functionality

• Real-time indexing with no commit or merge delay
• A built-in web crawler that turns any website into structured, searchable JSON documents automatically
• Faceted and geosearch, autocomplete with self-learning spell correction, and a multi-tenancy server for isolated customer instances
• Hybrid lexical-plus-vector search that runs as two dedicated engines fused via a query planner, rather than retrofitting one onto the other

Strengths

• Offers a genuine self-hosted, on-premises option, which Algolia’s SaaS-only design doesn’t provide
• Real-time indexing without a commit lag matters for content that changes constantly
• The built-in crawler removes an entire integration step, no separate crawling pipeline needed just to get content indexed

Limitations

• It’s a small, bootstrapped company, so the breadth of integrations, UI components, and enterprise case studies is limited compared to Algolia’s years of growth
• Its strongest benchmarks and roots are in lexical (keyword) search rather than vector search, hybrid search exists, but it’s less proven here than in Typesense or Manticore if vector search is your primary requirement

Pricing 

The open-source library is free to self-host under the Apache 2.0 license. 

Hosted SaaS starts at $19/month for 1 million documents and 1 million queries, scaling to $99/month (10 million/10 million) and $499/month (100 million/100 million), with custom pricing above that. 

A 14-day free trial is available with no credit card required.

Best for 

Teams that want Algolia-style hosted search at a fraction of the cost, with true real-time indexing.

6. Site Search 360

Site Search 360 is a no-code, hosted site search widget, a single line of JavaScript is genuinely all it takes to get search running. 

There’s no API to learn, no infrastructure to scale, and no vector database to configure; you paste a snippet, the crawler handles the rest, and you’re customizing colors and layout within minutes. 

It’s not a developer-first API the way Algolia is, and it isn’t trying to be, it’s built for teams that want search live today rather than a platform to architect around.

Image Source: www.sitesearch360.com

Key functionality

• A visual search designer for customizing colors, captions, and result layout without writing CSS
• Autocomplete and spellcheck, with built-in semantic dictionaries covering 19 languages and no manual synonym setup
• Faceted search, cross-domain search across multiple sites in one unified experience, and manual control to boost, reorder, or redirect specific results

Strengths

• Setup is genuinely fast, since there’s no schema to design or API integration to build before results appear
• Support tends to go beyond the basics, hands-on help with display fixes and migration is a recurring theme in feedback
• It operates independently of major third-party search engines, which appeals to privacy-conscious teams that don’t want customer search behavior harvested externally

Limitations

• There’s no image or visual search capability, which is a gap for catalogs that lean on visual discovery
• It’s crawler- and widget-first, so it doesn’t offer the granular, code-level control over ranking and querying that Algolia’s SDKs give developers

Pricing 

Four tiers are available. Free ($0/month) includes 150 indexed entries and 1,000 monthly searches with community support and visible branding. 

Columbo ($9/month) raises that to 1,500 entries and 2,000 searches with email support and reduced branding. 

Holmes ($49/month) adds priority support and extended analytics retention. 

Batman ($119/month) removes branding entirely and unlocks the highest allowances, plus e-commerce product feed integration.

Best for 

Teams that need working site search live today, without engineering resources.

7. AddSearch

AddSearch started as a hosted, no-code site search platform and has since repositioned itself around a full “search to discovery” experience, generative answers and multi-turn conversations layered on top of standard keyword search. 

That shift toward AI answers and conversations, rather than just ranked results, is what separates it most from being a straightforward Algolia substitute. 

You don’t need developers to launch it, a demo environment can be spun up directly from your data, though a full API is available if your engineering team wants deeper control.

Image Source: www.addsearch.com

Key functionality

• Faceted, scoped keyword search with ranking management and synonym handling
• AI answers that generate grounded, cited responses from your indexed content, and AI conversations that guide users through multi-step follow-up questions
• Instant indexing that makes new content searchable and GenAI-ready the moment it publishes
• Source governance controls and CMS-agnostic indexing that works with virtually any content platform

Strengths

• Search results are consistently described as fast and accurate, which shapes overall user experience and satisfaction
• Enterprise-grade features, SSO, audit logs, high-uptime SLAs, are available from the entry tier, well before Algolia’s top pricing bracket
• Vendor support tends to resolve real implementation problems rather than leaving teams to troubleshoot alone

Limitations

• It’s priced higher than most alternatives on this list, keyword search alone starts at $119/month, and AI Answers adds $700/month on top
• The admin panel isn’t always intuitive for non-technical users, and some advanced customization and filtering sits behind higher-tier plans
• It’s no longer a lightweight option, the platform is now built around full discovery, which can feel like more infrastructure than necessary if all you need is fast, Algolia-style keyword search

Pricing 

AddSearch prices each product separately rather than bundling them. Keyword Search starts at $119/month (billed annually). AI Answers starts at $700/month (billed annually). AI Conversations and the full combined AddSearch Experience are both custom-quoted.

Best for 

Teams that want AI-powered answers and conversational search layered on top of traditional keyword search.

8. Expertrec

Expertrec is a no-code, hosted search engine built specifically to fill the gap left when Google Custom Search gets shut down or becomes too costly once ads are switched off. 

It installs with a few lines of code, and from there, voice search, multilingual support, and content search all work without touching a backend.

Image Source: www.expertrec.com

Key functionality

• Voice search alongside traditional typed queries
• Indexing for content sitting behind logins, without exposing it publicly
• AI-powered autocomplete and faceted filtering by price, date, author, location, or content type
• Multilingual support across nearly 30 languages, plus file-format search across PDF, Excel, and Word documents

Strengths

• Packs a notably wide feature set into a relatively low-cost product, in contrast to platforms where advanced functionality requires moving up a pricing tier
• Support response times are consistently fast, which matters at this price point
• Visual customization is straightforward through CSS, without needing deep front-end expertise

Limitations

• There’s no autocorrect for typo-heavy queries, unlike Algolia’s built-in typo tolerance
• It’s a smaller company without the scale, integrations, or enterprise track record Algolia has built over the years, so features are less battle-tested at high volume

Pricing 

Four packages are available. Standard ($359/month) includes AI search, analytics, product pinning, real-time sync, and 50,000 search requests. 

Expert ($599/month) adds AI merchandising and advanced analytics at higher usage caps. 

Premium ($839/month) adds personalized AI search, chatbot integration, and AI summarization tools. Enterprise is custom-priced with unlimited usage and deeper GenAI integration.

Best for

Teams replacing a deprecated or increasingly expensive Google Custom Search setup.

9. Prefixbox

Prefixbox is an AI-powered e-commerce search, navigation, and merchandising platform built for retailers rather than general-purpose content search. 

It supports enterprise clients including Carrefour, Leroy Merlin, and Rossmann, and was the first search provider to earn Shopify’s “Built for Shopify” status. 

Its AI is designed to understand purchase intent even when a query doesn’t textually match a product, and its newest addition, a ChatGPT-style AI Agent for product discovery, signals it’s chasing a different frontier than Algolia’s core search API.

Image Source: prefixbox.com

Key functionality

• AI search that combines vector search and LLM-based intent understanding beyond exact text matches
• AI navigation that suggests related products, keywords, and categories to refine intent in one click
• AI-driven personalized recommendations, plus merchandising controls to override results, boost or hide products, and build promotional banners
• Built-in A/B testing and analytics to optimize search performance over time

Strengths

• Handles broad, imprecise queries well, letting shoppers describe what they want in general terms and still land on relevant products
• The AI Agent guides customers from a vague idea toward a specific product, which is useful when shoppers don’t know the exact name or category they need
• Reported results include click rates as high as 40% on AI-recommended products in chat interactions, along with meaningful support-cost savings for retailers using it for customer service

Limitations

• It’s built specifically for e-commerce, not general-purpose search, it’s not a fit for indexing documentation, blogs, or other non-retail content alongside products

Pricing 

Shopify Self-Service (all with a 14-day free trial) ranges from Free ($0/month, 500 searches) up to Pro ($849/month, 200,000 searches and unlimited synonyms/redirects). 

Managed Customers (Shopify Managed, Salesforce Commerce Cloud, headless, or custom front ends) are priced per product suite based on monthly API requests, AI Search starts at $1,430/month, with AI Navigation and AI Recommend available as $626/month add-ons.

Best for 

Mid-market to enterprise e-commerce stores that want AI merchandising alongside search, not just a raw search API.

10. Luigi’s Box

Luigi’s Box is an AI-powered e-commerce platform combining search, personalized recommendations, category page optimization, and analytics into one connected system. 

It’s built specifically for retail, with a particular strength in matching real-world search terms, slang, old product names, industry jargon, to the correct item in a catalog. 

Reported outcomes include a 35% increase in average cart conversion rate and a 20% increase in average order value for adopters.

Image Source: www.luigisbox.com

Key functionality

• AI search that automatically handles typos, synonyms, and industry-specific product naming
• Word decompounding that breaks down compound terms so search still matches relevant products
• A recommender engine for personalized suggestions across the shopping journey
• Search analytics tracking queries, zero-result searches, and conversion data, plus built-in A/B testing

Strengths

• The interface is clean and modern, and results come back relevant and fast, a combination that shapes how customers perceive the broader shopping experience
• Search and recommendations perform well together, particularly through integrations that pair the recommender engine with existing storefronts
• It handles vague, industry-specific product names accurately, including in specialized categories like medical or eco-friendly products, even with typos or unfamiliar terminology

Limitations

• Pricing tends to run higher for smaller businesses, and the unit-based model takes some familiarity before ROI becomes clear
• UI and UX customization isn’t fully self-service, interface changes currently require a request to the support team rather than direct dashboard control
• Performance depends on a well-maintained product feed, so the quality of your own catalog data directly affects results

Pricing 

Luigi’s Box structures pricing around integration type rather than fixed usage tiers, and publishes no numeric pricing, every plan requires a quote based on site usage and catalog size. 

Self-Integration suits small-to-medium businesses with no-code setup and a 30-day free trial. 

Custom Integration and Enterprise tiers add expert-led setup and a dedicated success manager for larger deployments.

Best for

Catalogs with complex, jargon-heavy, or industry-specific product naming that customers rarely search for directly.

How to Choose the Best Algolia Alternative for Your Business

Thirteen strong options still leave you with one decision, and the right answer depends entirely on what’s actually driving you away from Algolia in the first place. Weigh these factors against your specific situation before committing to a tool:

• Budget model: Decide whether you want a free, self-hosted engine with your own infrastructure costs, a SaaS tool with flat pricing, or a SaaS tool with usage-based pricing that scales with traffic.
• Technical resources: Self-hosted engines like Meilisearch, Typesense, Manticore, and Elasticsearch need someone to deploy and maintain them. No-code tools like Site Search 360 and Expertrec don’t.
• Content type: General-purpose search engines handle mixed content (docs, blogs, product pages) well, while e-commerce-specific platforms like Prefixbox is built specifically around product catalogs.
• Scale and system complexity: If you’re searching across a single website or app, most tools on this list will work.
• Compliance requirements: If data sovereignty or on-premise hosting is non-negotiable, that immediately rules out every SaaS-only option here.

None of these factors matter equally to every team, so rank them before you start testing tools rather than after.

Wrapping Up

Algolia built its reputation on speed and simplicity, but that reputation only goes so far once cost, self-hosting, or system complexity enter the picture. Each alternative in this guide fills a different gap Algolia leaves open.

Meilisearch and Typesense give you Algolia’s developer experience without the per-request bill. Elasticsearch and Manticore hand you full infrastructure control if you’re ready to own the operational overhead. 

Site Search 360, AddSearch, and Expertrec strip away engineering effort entirely for teams that just need search live. Prefixbox, and Luigi’s Box go beyond search into merchandising and personalization built for e-commerce.

No tool here is a universal replacement for Algolia. 

Each one solves a different piece of what Algolia gets wrong for a specific kind of team. Match your constraints to the right option, and you’ll spend less time fighting your search platform and more time building on top of it.

Frequently Asked Questions (FAQs)

Q1. Which Algolia alternative is best for e-commerce? 

Prefixbox and Luigi’s Box are all built specifically for e-commerce. They bundle search with merchandising, personalized recommendations, and AI-driven intent matching, rather than offering search as a standalone API the way Algolia does.

Q2. Which Algolia alternative is best for site search? 

Site Search 360 is built specifically for content-heavy site search. It runs as a no-code, crawler-based widget, so you’re live within minutes without writing an API integration.

Q3. Which Algolia alternative is best for developers? 

Typesense is the closest match for developer workflows, it offers an official adapter for Algolia’s InstantSearch UI components, so you can migrate the backend without rebuilding the frontend, and it gives full control over ranking through query-time configuration.

Q4. What is the best open-source alternative to Algolia? 

Meilisearch is the strongest open-source pick for teams that want Algolia’s speed and developer experience without per-search billing. Typesense and Manticore Search are also fully open-source, Typesense suits high query volume better, while Manticore suits teams already running SQL-based infrastructure. Elasticsearch is the choice when scale and customization matter more than simplicity.

Q5. Which Algolia alternative is best for self-hosting? 

Meilisearch, Typesense, Manticore Search, Elasticsearch, and SeekStorm’s open-source core all support self-hosting with full features unlocked and no gating between free and paid versions. Manticore has no first-party managed cloud at all, so it’s built entirely to run on your own infrastructure.

Q6. Which Algolia alternative is easiest to set up? 

Site Search 360 and Expertrec are the easiest to set up. Both are low-code, crawler-based tools that launch from a small code snippet, with no API integration or infrastructure sizing required.

Q7. Which Algolia alternatives can handle large product catalogs?

Elasticsearch and Manticore Search are built for large-scale data, with production deployments reportedly indexing around 100 million documents. Typesense and Meilisearch also scale well but need more infrastructure planning as catalog size grows. For e-commerce catalogs specifically, Luigi’s Box and Prefixbox are built to handle complex, high-SKU inventories with AI-driven product matching.

Q8. Which Algolia alternative has the best API? 

Typesense has the most developer-friendly API, with query-time configuration that lets you adjust search, facet, and ranking fields without maintaining separate indexes. Manticore Search stands out too, offering both a JSON API and native SQL support for teams that prefer familiar query syntax.

Q9. How does Algolia’s pricing model compare to its alternatives? 

Algolia charges per search request and per record, which is what drives cost up as traffic or catalog size grows. Most alternatives on this list avoid that model entirely — Typesense and Meilisearch charge for infrastructure resources instead of usage, Manticore and Elasticsearch are free to self-host.

The post Top 10 Algolia Alternatives in 2026 appeared first on Marketing Experts Hub.

This guide takes a different angle: 8 software tools mapped to the business models they actually fit, with verified pricing, real review quotes, and honest trade-offs for each.

The goal is to leave you with a two-or three-tool shortlist worth trialing.

Start with the comparison table below, then jump to the section that matches your use case.

Disclaimer: The information on these platforms is valid as of June 2026. Software offerings, pricing, and features change; verify current details directly with each vendor before making a decision.

Now, let’s review each platform in detail.

1. Viral Loops

Viral Loops is a referral marketing platform built for growth teams that need to launch referral, waitlist, and giveaway campaigns without writing custom code or waiting weeks for engineering bandwidth.

The platform takes a templates-first approach to building a referral program. Templates cover the most common viral mechanics, with examples documented on the Viral Loops site referencing programs from Dropbox, Mailchimp, Harry’s, and Uber as inspiration.

Source: viral-loops.com

Teams without a website ready to host a campaign can use Viral Loops Pages, a hosted landing page builder included with the platform.

Teams with a site can install a JavaScript widget, deploy via an AI-driven installer that wires custom forms into the campaign, or build directly against the API and SDK for in-product placements.

Two things differentiate Viral Loops from purpose-built B2B SaaS or DTC ecommerce tools.

The first is the breadth of campaign types under one roof: milestone referrals, waitlists, sweepstakes and giveaways, leaderboards, refer-a-friend flows, and an affiliate program tier for promoting top referrers all run on the same engine.

The second is the reward stack: a native Stripe Connect integration handles cash payouts, and an official Tremendous partnership covers gift card distribution.

The Viral Loops customer support team is a recurring theme across G2 and Capterra reviews, both for fast response times and for the program-design input they offer alongside technical help.

Key features

• Pre-built campaign templates modeled on proven viral programs (milestone referrals, waitlists, leaderboards, sweepstakes, refer-a-friend flows).
• AI-powered campaign installer for no-code deployment, including custom form integration and platform-agnostic widgets.
• Landing page builder for hosting referral campaigns without a separate site builder.
• Real-time analytics dashboard for tracking shares, conversions, and reward fulfillment by channel.
• Hands-on customer support with rapid response times and strategic campaign guidance.

Pricing

Viral Loops uses tiered pricing based on campaign participants and business size.

Yearly billing saves 30%:

• Start-up: $49/month ($35/month billed annually, up to 1,000 participants)
• Plus: $139/month (up to 5,000 participants)
• Growing: $229/month
• Power: $399/month (priority support, white-label widgets)

Enterprise plans, concierge services, and custom feature development are available on demand.

A 14-day free trial is available across all plans (capped at 8 participants).

Integrations

Stripe and Tremendous for reward fulfillment, Shopify for ecommerce, HubSpot for CRM sync, Mailchimp and Klaviyo for email, Mixpanel for behavioral analytics, plus WordPress, Zapier, AWeber, Mailjet, Instapage, and webhooks.

Pros

• Exceptional customer service: “When I did encounter a challenge […] the Viral Loops team jumped on it […] and did a thorough job investigating and getting it sorted. That alone has made me want to stay with them.”
• Powerful product with time-saving features: “The platform provides pre-built templates for different use cases, […] which save a lot of time. The integration with tools like Shopify and email marketing platforms is seamless, and the analytics dashboard is intuitive, helping us track campaign performance in real time.”
• Simple interface: “What I like best about Viral Loops is how easy it makes creating referral and viral marketing campaigns. The setup process is straightforward, and the automation helps grow audiences and engagement.”

Cons

• Limited customization freedom: Customization options can feel limited for bespoke campaigns, and advanced setups sometimes require workarounds or indirect integrations.
• Restricted multilingual customization: Editing campaigns in non-English languages without support can be inconsistent, with some users reporting issues with language switching between campaigns.

Best for

• Startups and tech companies
• Fintech companies
• E-commerce businesses
• Newsletter creators and content publishers
• Customer referral programs

2. ReferralCandy

ReferralCandy is one of the most established referral platforms purpose-built for ecommerce.

The product includes post-purchase popups, embedded widgets on product and account pages, and automated invitation emails triggered after an order ships.

Source: referralcandy.com

What makes ReferralCandy distinct in this list is its commercial model.

Most platforms charge by participant count or a flat subscription; ReferralCandy adds a percentage commission on referred revenue on top of a lower base fee.

The result is favorable economics for stores still testing whether referrals are a viable channel and steadily worse economics for stores running a high-volume program.

On the operational side, the platform automates the parts of referral that usually leak time: it pushes rewards to customers as store credit, discount codes, or cash payouts; flags duplicate sign-ups, suspicious IPs, and self-referral patterns for review; and lets brands customize the landing page, invitation emails, and on-site banners without leaving the dashboard.

Key features

• On-site signup widgets that embed referral invitations into product pages, post-purchase flows, and account pages.
• FlexiTiers reward system that incentivizes higher-volume referrers with escalating rewards.
• Automated reward fulfillment for cash payouts, store credit, and discount coupons.
• Built-in fraud detection flagging suspicious patterns for manual review.
• Custom branding with editable landing pages, emails, and banners.

Pricing

• Basic: $39/month + 10.5% success fee
• Grow: $79/month + 3.5% success fee
• Scale: $249/month + 1.5% success fee
• Enterprise: $799/month + 0.25% success fee

A 7-day free trial is available.

Integrations

Shopify, WooCommerce, BigCommerce, Magento, ReCharge, Klaviyo, Mailchimp, Google Ads, and Meta Ads.

Pros

• Easy setup: Retail brands consistently flag how user-friendly the setup is for non-technical teams.
• Responsive support: Users highlight quick response times when issues come up.
• Solid analytics dashboard that surfaces referral revenue, share counts, and reward fulfillment at a glance.

Cons

• Performance lag inside Shopify: Some users report the app can slow down the Shopify admin, particularly when pinned to the dropdown menu.
• Limited theme and email customization: Granular control over email templates and notification logic is more restricted than on developer-first platforms.

Best for

• Shopify and BigCommerce merchants who want a referral channel without engineering involvement.
• DTC brands testing referral marketing for the first time and willing to pay a success fee on referred sales.
• E-commerce stores that need automated reward fulfillment integrated directly into their payment stack.

3. Referral Rock

Referral Rock is one of the few platforms built for various service businesses (agencies, financial advisors, home services, professional services) and supports both customer referral programs and partner/affiliate programs in the same workspace.

Source: referralrock.com

Teams can structure rewards as one-sided, two-sided, tiered, or multi-step (where the referrer earns smaller rewards along the funnel before a full payout on close), which fits how B2B referral economics actually work.

The HubSpot and Salesforce integrations are where the product earns its keep for B2B buyers.

Referrals push into the CRM as leads, and attribution flows through to deals and revenue reporting.

Key features

• Multi-step and tiered referral workflows that match B2B and service-business sales cycles.
• Offline referral tracking via codes, QR mechanisms, or manual entry from the sales team.
• Deep HubSpot, Salesforce, and Pipedrive integrations that push referrals into the CRM as leads.
• Concierge onboarding with a dedicated specialist mapping workflows during setup.
• Combined customer-and-partner program management in a single workspace.

Pricing

Referral Rock offers two plans:

• Professional: $175/month
• Professional+: $350/month

They also offer dedicated packages for e-commerce and enterprise.

You can also get concierge services, such as a done-with-you onboarding for everyone, coming as a $400 one-time fee. 

Integrations

HubSpot, Salesforce, Pipedrive, Zoho, Mailchimp, Stripe, PayPal, Shopify, BigCommerce, WooCommerce, plus Zapier.

Pros

• Versatile across business models. Works for B2B, services, and hybrid models that don’t fit ecommerce or SaaS templates.
• Strong CRM attribution that flows referral data directly into pipeline reporting.
• Hands-on onboarding that helps non-technical teams get programs live.

Cons

• Higher price point for small businesses compared with self-serve tools.
• UI feels less modern than newer platforms, per reviewer feedback on G2 and Capterra.

Best for

• Service businesses (agencies, consultancies, financial advisors, home services) running referral programs alongside their existing sales motion
• B2B companies that want a single tool for both customer referrals and partner referrals
• Mid-market teams that need white-glove onboarding to launch a complex program

4. GrowSurf

GrowSurf is built for product-led SaaS, with embeddable UI components that engineers can drop into an existing application, e.g., in-product referral dashboards, share prompts, and leaderboards.

Source: growsurf.com

That positioning shows up everywhere in the product.

Key features

• Viral coefficient (K-factor) is a primary metric in the analytics dashboard, alongside cohort conversion data.
• Reward logic understands subscription mechanics, so trial extensions, plan upgrades, and feature unlocks can be triggered by referral events without custom code.
• Webhooks fire on every significant moment in the funnel, which lets product teams stitch referrals into the same event stream powering analytics and email automation.
• The trade-off is engineering involvement: GrowSurf requires developer time to integrate, which most no-code platforms in this list don’t.
• GDPR and SOC 2 documentation come standard, which matters for fintech and any B2B SaaS selling into regulated buyers.

Pricing

Paid plans start at $125/month (billed annually) and scale up significantly for higher participant counts. Monthly pricing is also available.

Source: growsurf.com

Some premium features (white-labeling, advanced analytics) are gated to higher-tier plans.

Integrations

Stripe, HubSpot, Salesforce, Segment, Intercom, plus webhook and Zapier support for custom workflows.

Pros

• Clean developer experience with thorough API documentation.
• Strong B2B SaaS fit. The metrics, participant flows, and reward logic all assume a subscription product.
• Compliance posture meets the bar for fintech and other regulated categories.

Cons

• Higher technical lift than no-code platforms. Integration requires developer involvement.
• Premium features cost extra, including removing the “Powered by GrowSurf” branding that competitors include in lower tiers.

Best for

• Product-led SaaS teams building referral into the application UI, not a separate landing page
• Regulated B2B SaaS where SOC 2 and GDPR documentation is a procurement requirement
• Growth teams that need viral coefficient as a tracked metric, not just total referrals

5. Referral Factory

Referral Factory has built a reputation in the no-code corner of the category by treating the campaign editor itself as the product.

The template library runs into the thousands, drag-and-drop covers nearly every element a marketing team would otherwise need a developer to touch, and an AI-assisted generator can produce a fully branded campaign from a short prompt.

Source: referral-factory.com

The standalone-hosted-page model means brands without a developer-accessible CMS, or agencies running programs for multiple clients, can run a referral program without touching their primary website.

Multilingual support across 25+ languages and white-label hosting on higher tiers reinforce the international and agency use cases.

The reward stack covers vouchers, PayPal cash payouts, Stripe credits, digital gift cards, donations, and custom rewards through API and webhook hooks.

The enterprise security posture (GDPR, SOC 2, ISO 27001, optional self-hosting) clears procurement bars that most platforms in this price range can’t.

The trade-off shows up for teams that want referral mechanics deeply embedded inside a product experience: the standalone-page model is a strength for marketing-led launches and a limitation for product-led ones.

Key features

• Thousands of pre-built templates and an AI-powered campaign generator for fast launches.
• Standalone hosted pages that don’t require integration with the primary website.
• Multilingual campaigns across 25+ languages with localized landing pages.
• 200+ reward types including PayPal payouts, gift cards, Stripe credits, and custom payouts.
• Enterprise security posture (GDPR, SOC 2, ISO 27001) with optional on-premise hosting.

Pricing

• Basic: $200/month ($160/mo billed annually)
• Pro: $400/month
• Enterprise: $1,000/month and up

A free trial is available across plans, and annual billing saves 20%.

The Enterprise plan adds SSO, on-premise hosting, custom HTML/email uploads, and dedicated account management.

Integrations

HubSpot, Salesforce, Pipedrive, Intercom, 3,000+ tools via Zapier and Make, plus API, webhooks, and Tremendous for payouts.

Pros

• Easy setup and customization: Reviewers consistently mention how quickly the platform gets a program live, often within days.
• No-code-first approach that suits non-technical teams and agencies running programs for clients.
• Strong compliance posture that satisfies enterprise procurement.

Cons

• Standalone page approach may feel disconnected from a core product experience for teams that want deep in-app referral flows.
• Higher entry price than the bottom of the category for very small programs.

Best for

• Small and mid-market businesses without dedicated engineering resources
• Service companies and agencies running referral programs for themselves or clients
• International programs that need multilingual referral pages out of the box

6. Friendbuy

Friendbuy is built for mid-market and enterprise DTC brands with the referral volume to run meaningful A/B tests on reward structures, creative placement, and behavioral triggers.

Source: friendbuy.com

The testing engine covers reward structures, creative variations, and behavioral triggers, with significance reporting built in.

Key features

• Native A/B testing engine for reward variants, creative placement, and behavioral triggers with significance reporting.
• Behavioral trigger library spanning post-purchase, post-delivery, and post-repeat-purchase moments.
• Bundled loyalty program module for brands consolidating referrals and retention with one vendor.
• Deep Klaviyo, Attentive, and Iterable integrations for lifecycle email and SMS stitching.
• Headless and custom storefront support via a documented API.

Pricing

Friendbuy is quote-only.

Integrations

Shopify, BigCommerce, Salesforce Commerce Cloud, Klaviyo, Iterable, Attentive, Segment, GA4, plus REST API and webhooks.

Pros

• Sophisticated experimentation that scales with program volume.
• Strong analytics depth for cohort and segment analysis.
• Mature lifecycle integration with the standard DTC email and SMS stack.

Cons

• Pricing is gated behind a sales call, which slows down evaluation for teams that prefer self-serve discovery.
• The depth of the testing engine is overkill for stores below mid-six-figure annual referred revenue, where simpler tools deliver more of the value at a fraction of the cost.

Best for

• DTC brands with the referral volume to A/B test program variables
• Klaviyo or Attentive-driven lifecycle programs wanting referral stitched into the same trigger logic
• Ecommerce teams treating referrals as a measured acquisition channel

7. Genius Referrals

Genius Referrals sits at the developer-friendly end of the category.

Agencies running programs for multiple clients can use it as backend infrastructure, and engineering teams can use the API to build in-product referral flows.

Source: geniusreferrals.com

White-label capabilities cover landing pages, advocate dashboards, and email notifications without Genius Referrals branding.

Key features

• API-first engine with thorough documentation for engineering-led builds.
• Full white-label experience across landing pages, dashboards, and notifications.
• Multi-program account structure that fits agency and multi-brand use cases.
• 200+ reward types with automation via Tremendous, Zapier, Make, and webhooks.
• Real-time program ROI analytics with custom event tracking.

Pricing

Here’s an overview of Genius Referrals’ pricing plans:

• Starter: $89/month ($63/month billed annually)
• Silver: $199/month
• Gold: $399/month
• Platinum: $799/month
• Custom: Available for enterprise needs

A 14-day free trial is also available, and they offer 20% on annual plans.

Integrations

HubSpot, Salesforce, Mailchimp, Stripe, PayPal, Tremendous, Zapier, Make, plus webhooks and a REST API.

Pros

• Feature-rich and flexible: Reviewers highlight the breadth of customization and program-type support.
• Strong API documentation for teams building custom flows.
• $89/month entry tier that’s lower than most API-first competitors.

Cons

• Steep learning curve that some users find overwhelming without onboarding assistance.
• Higher-tier features locked behind add-ons that increase total cost beyond the headline plan price.

Best for

• Agencies and platforms building custom referral experiences for clients
• Tech companies with engineering resources to build on top of a referral API
• Multi-program businesses managing several distinct referral campaigns simultaneously

8. Referral Hero

Referral Hero focuses on newsletter creators, indie makers, and pre-launch startups, with built-in support for the mechanics common in that audience: leaderboards, milestone-based rewards that unlock at specific referral counts, and share-to-unlock flows.

Source: referralhero.com

SMS-based reward delivery (pay-as-you-go) is a notable touch for newsletter operators who want to push milestone alerts to subscribers without setting up a full SMS marketing stack.

Key features

• Waitlist and pre-launch templates with milestone-unlock mechanics built in.
• Leaderboard view that gamifies the top of the referrer list.
• Standalone landing page builder for creators without a separate site.
• SMS reward delivery on a pay-as-you-go basis for milestone alerts.
• Creator-economy integrations with ConvertKit, Mailchimp, and Beehiiv-friendly Zapier flows.

Pricing

Plans start at $249/month and scale up to $399/month based on subscriber count, with custom enterprise packages available above that.

A free starter tier (up to 25 subscribers with Referral Hero branding) is available for testing the platform.

Integrations

Mailchimp, ConvertKit, Zapier, Stripe, Segment, plus webhook support.

Pros

• Strong fit for the use cases it targets (waitlists, newsletters, pre-launch campaigns).
• Cleaner, more modern UI than older platforms in the category.
• Predictable pricing without success fees or per-referral charges.

Cons

• Less robust for post-launch, ongoing referral programs at scale.
• Smaller integration footprint than enterprise-focused tools.

Best for

• Newsletter operators and content publishers running referral programs to grow subscribers
• Pre-launch startups capturing waitlist demand before a product opens up
• Creators who want a narrower, simpler tool

How to Choose the Right Customer Referral Software

The questions below are worth asking before shortlisting.

What is the primary use case?

The single biggest filter, since the shape of the program drives every downstream decision. For a customer-to-customer referral program inside a subscription product, the shortlist is GrowSurf, or Viral Loops. For brands building structured advocacy programs around brand ambassadors and high-volume sharers, Friendbuy carries the deepest segmentation. For post-purchase referrals at a DTC brand, the shortlist is ReferralCandy, Friendbuy, or InviteReferrals. For a pre-launch waitlist or newsletter referral program, Viral Loops or Referral Hero. For a partner-and-customer hybrid program in a service business, Referral Rock For agencies running multiple programs or building custom referral experiences, Genius Referrals or Referral Factory. This question alone will eliminate six or seven tools.

Do you need no-code setup or API-first flexibility?

Most marketing teams don’t have engineering bandwidth to spare. For those teams, the priority is referral software with mature no-code installation (Viral Loops, Referral Factory, ReferralCandy) and a templated campaign builder. For teams with dedicated product engineering that want referral logic embedded inside their application, GrowSurf, or Genius Referrals are stronger fits.

What integrations do you need?

Make a short list of must-have integrations: CRM (HubSpot, Salesforce, Pipedrive), ecommerce platform (Shopify, BigCommerce, Magento), email tool (Klaviyo, Mailchimp, ConvertKit), payment processor (Stripe, Paddle, PayPal), and analytics stack (GA4, Mixpanel, Segment). Disqualify any tool that requires a Zapier workaround for an integration used daily.

What reward types do you need?

Cash payouts via Stripe Connect or PayPal?

Gift cards through Tremendous, Tango, or Giftbit?

Store credit native to Shopify?

Account credits inside a SaaS product?

Custom physical rewards?

Reward fulfillment is where most referral programs leak operational time, and the right platform should automate it end-to-end and integrate cleanly with the marketing channels teams already use.

Teams that pick tools based on a feature checklist and then spend ten hours a week manually issuing PayPal payouts have made the wrong choice.

What’s your total budget, including reward costs?

Software subscription is usually the smaller piece. A double-sided $20 reward paid across 500 monthly referrals comes to $20,000 monthly on rewards alone, which is multiples of what any platform on this list charges in software fees. Build a total program cost model before signing anything: software fees plus reward fulfillment plus internal management time.

Wrapping up

Most referral marketing software evaluations get stuck in the same place: trying to find the platform that wins on every dimension.

That platform doesn’t exist.

The buyers who launch fastest usually decide which one or two dimensions matter most for their business (no-code speed, in-product integration, multi-program scale, fraud control, total cost) and let those choices eliminate the rest.

Two practical moves shorten the timeline.

The first is to shortlist two platforms, not five. Three or more trials in parallel rarely get a fair test, and the comparison fatigue tends to defer the actual launch by weeks.

The second is to pick a real campaign goal before opening the trial: a refer-a-friend flow, a waitlist, a milestone newsletter program, or a post-purchase prompt.

Configuring the same campaign across two platforms makes the trade-offs visible faster than reading feature lists ever does.

Trials reveal setup speed, integration depth, and dashboard usability.

They don’t reveal fraud resilience, support quality once a program scales, or how the platform handles edge-case payouts at volume.

For higher-stakes programs, ask each vendor for a reference call with a customer running a similar use case before signing an annual contract.

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