37 Ways to Use Lookalike Ads to Add $1m ARR in 30 days

In this article, you’ll discover how top software CEOs leverage “Lookalike Advertising” to acquire new users and scale revenue, complete with real-world examples and actionable strategies. We’ll explore how leaders of fast-growing companies turn their existing customer data into a powerful tool for finding new, high-intent audiences on platforms like Facebook and LinkedIn. You’ll get the 4-step playbook to launch your own Lookalike Advertising campaigns, drawn from the exact tactics used by CEOs who have built multi-million dollar companies.

These strategies are from top founders like Olin Hyde at LeadCrunch, who grew his customer base from 55 to over 400, and Stefan Smulders of Expandi, who scaled his company from $0 to $7M in just 20 months by creating hyper-targeted seed audiences. The insights shared here were collected directly from these leaders during keynotes at Founderpath events, offering a unique glimpse into their growth engines.

The 4-Step Playbook for High-ROI Lookalike Advertising

1. Build Your High-Value “Seed” Audience: This is the foundational list of your best customers, leads, or most engaged users. The goal is to identify a group whose characteristics you want to replicate. For example, Stefan Smulders at Expandi built his initial seed audience by scraping a competitor’s Facebook group to get a list of active, engaged users in his niche, which led to booking over 40 appointments every week.
2. Enrich and Segment Your Data: Once you have a raw list, the next step is to enrich it with additional data points to create a detailed profile of your ideal user. This helps advertising platforms find better matches. Olin Hyde, CEO of LeadCrunch, does this by taking a client’s list of best customers and analyzing it across half a million different dimensions to find the attributes that truly define a high-value prospect, helping him scale to a $20M run rate.
3. Create Lookalike Audiences in Your Ad Platform: Upload your segmented “seed” list (usually as a CSV file) to your chosen ad platform, like Facebook Ads or LinkedIn Ads. The platform’s algorithm then analyzes the characteristics of your list and finds millions of new users who share those same traits. Ramsey Nasar from Birdseye automates this by de-anonymizing website visitors and turning them into powerful, encrypted lookalike audiences that can be uploaded directly to ad networks, a strategy that helped him secure 80+ paying customers before his public launch.
4. Launch Targeted Campaigns with Resonant Messaging: With your new lookalike audience ready, the final step is to launch ad campaigns with messaging that speaks directly to their needs and pain points. Since these users are similar to your best customers, your messaging should be highly relevant. The team at 6sense excels at this by using the insights from their customer data platform to engage prospects with surgical precision, reducing wasted ad spend and tripling their revenue year-over-year.

40+ Examples of Lookalike Advertising in Action

• Olin Hyde of LeadCrunch described his B2B lookalike marketing platform as doing for businesses what Facebook does for consumers. By taking a client’s best customer list and analyzing it across 500,000 dimensions, his company grew from 55 to over 400 customers, hitting a $20 million run rate.
• The Expandi team kickstarted their growth by scraping a competitor’s Facebook group, converting the member list to LinkedIn profiles, and uploading it as a seed audience for an outreach campaign. This strategy achieved a 72% acceptance rate and booked over 40 appointments each week, scaling the company to $7 million in 20 months.
• Birdseye’s founder, Ramsey Nasar, built a platform that de-anonymizes anonymous web traffic and converts it into powerful lookalike audiences for retargeting. This tactic was key to signing up over 80 agency clients and hitting a $1.2 million run rate before the product was even open to the public.
• Jason Zintak at 6sense explained how his platform takes a company’s first-party CRM data and marries it with behavioral web data to build precise target audiences. This approach helped 6sense triple its bookings year-over-year and grow from 30 to over 150 enterprise customers.
• Brian Yam of Paragon detailed his highly strategic approach to LinkedIn ads, where he builds tiered account lists based on ideal customer profile attributes. By uploading these segmented lists, Paragon targets cold audiences with precision, a key factor in their 30x ARR growth over three years.
• Gatsby CEO Brett Bernstein helps brands discover which of their existing customers are micro-influencers. Brands then use this segmented list to build an army of advocates, creating a powerful, organic lookalike effect that turns loyal customers into a volunteer marketing team.
• Kevin Tan, co-founder of Eyeota, built a global audience data marketplace with 3.5 billion unique profiles from over 30,000 publishers. His company specializes in onboarding offline data records and matching them to digital signals, allowing marketers to create rich, targetable audiences for their campaigns.
• Andy Rossmeissl of Faraday.io helps consumer brands predict future customer behavior by assembling and analyzing their data. This allows brands to identify their most valuable customer segments, which can then be used to create effective lookalike audiences for lead generation campaigns, pushing the company toward a $6 million run rate.
• Richard Jones leads the Wayin platform, which enables enterprise brands like P&G to create interactive experiences that collect first-party data. This declared data is then used to build rich profiles for targeted advertising, helping the company grow its subscription revenue by 62% year-over-year and surpass $11 million in ARR.
• Nathan Latka, CEO of Founderpath, shared a strategy of using tools like Texau to scrape LinkedIn event attendee lists. This creates a highly relevant seed audience that can be used for targeted outreach or as a basis for lookalike campaigns to find similar professionals.
• Dominic Edmunds of SaleCycle leverages behavioral marketing by analyzing customer actions to identify high-intent segments. This data is invaluable for creating lookalike audiences of consumers who are likely to convert, helping SaleCycle grow 30% year-over-year and serve over 500 customers.
• David A. Dunn, CEO of Velocity, built a marketing intelligence platform that charges clients based on the number of data streams they integrate. This enriched data helps brands and agencies make smarter decisions and can be used as a seed for powerful lookalike campaigns to find new audiences.
• Toby Gabriner at AdRoll launched RollWorks, an account-based marketing solution that onboards a company’s CRM data and enriches it with a proprietary dataset of 1.2 billion digital profiles. This allows B2B marketers to execute precise campaigns, driving over $2 million in ARR in just four months.
• Sri Swaminathan of Factors.ai grew his company 6x by using signal-based sales and marketing, focusing on high-intent audiences for LinkedIn ads. He identifies companies visiting his website, enriches that data with tools like Apollo, and creates targeted lists for multi-channel outreach, a core principle of seed audience creation.
• Stephen Morell from AX Semantics generates leads by running highly targeted Facebook and Google ad campaigns. He then uses an SDR team to qualify these leads, creating a clean list of prospects that can be used to model lookalike audiences, fueling the company’s 60% year-over-year growth to $4.2 million.
• Jay Habegger, CEO of ownerIQ, created a platform for brands to exchange first-party data transparently. For example, a brand like Ugg can use purchase data from a retailer like Target to build lookalike audiences, a model that has scaled the company to a $70 million top-line.
• Raj Aggarwal of Localytics moved his company upmarket by focusing on enterprise clients. His platform uses analytics and engagement data to create highly segmented user profiles, perfect for building lookalike audiences that align with high-value customer behaviors, driving the company to over $30 million in ARR.
• Stefan Smulders of Expandi shared his “sniper targeting” strategy, which involves scraping the engagement from any LinkedIn post (including competitors’) to build a hyper-relevant audience list. This list can then be exported as a CSV for retargeting or lookalike campaigns, consistently achieving a 70%+ acceptance rate.
• Tim Hampson at SalesSeek explained that a key early step is getting a customer’s contact data into the system. This initial data upload is crucial, as it forms the basis for identifying high-value segments that can later be used for creating lookalike audiences to find new prospects.
• Andrei Breaz, CEO of Bant.io, generates B2B leads by using advanced data points beyond basic firmographics, such as the technologies a company uses or their ad spend. This enriched data creates a powerful seed list for lookalike modeling, helping him guarantee 10-15 hot leads per month for his clients.
• Amrpratit B, CEO of Frrole, provides consumer intelligence by analyzing public social data through partnerships with Facebook and Twitter. His algorithms build detailed profiles on consumer interests and behaviors, creating a rich dataset that is ideal for advertisers looking to build effective lookalike audiences.
• Arnaud Belinga used AI to build personalized outreach campaigns for his tool, Breakcold. He generates hyper-personalized first lines based on a prospect’s LinkedIn profile or website, creating a highly qualified list of engaged users that serves as a perfect seed audience for finding similar prospects.
• Nick Zeckets of Air Traffic Control uses machine learning to understand the subject matter that users engage with, enabling true human-specific personalization. By identifying these deep interests, brands can create seed audiences based on nuanced behaviors rather than just clicks, leading to more effective lookalike targeting.
• Neil Napier of KV Social pivoted his business to a recurring revenue model by bundling multiple marketing tools. His platform collects data across funnels, email marketing, and affiliate management, creating a centralized data source that can be segmented to identify top-performing users for lookalike campaigns.
• Matt V, CEO of Mention, described his platform as “Google Alerts on steroids.” It allows companies to track brand mentions in real-time. This data can be used to identify highly engaged users and build a seed audience of brand advocates for lookalike targeting.
• Benjamin Dell of Missinglettr grew his user base by pushing all customer data to Facebook daily to continually refine his lookalike lists. This constant feedback loop allowed the Facebook algorithm to get smarter over time, steadily improving the quality of new users acquired through lookalike campaigns.
• Francisco Cornejo of Storybook relies heavily on paid acquisition through Facebook and Instagram for his B2C app. By analyzing which users convert and have the highest LTV, he can create seed audiences of his best customers to build lookalike campaigns that profitably acquire new subscribers at scale, growing to over 10,000 paid users.
• Kyle Vamvouris of Vouris emphasized the importance of identifying your Ideal Customer Profile (ICP) by analyzing historical sales data. This data-driven ICP is the perfect starting point for building a seed list to create lookalike audiences that attract high-value prospects.
• Wouter F, CEO of LeadBoxer, calls his tool a customer data platform that collects online activities from email, web behavior, and social channels into unique profiles. This unified data allows sales and marketing teams to identify their best customers and use them as a model for lookalike targeting.
• Michael B, CEO of distillery, explained how his company creates high-performing audiences by ingesting a wide variety of data, including non-ad-supported behavioral data. This rich, clean dataset is then used to build custom and syndicated segments for clients, including lookalike models, processing over $25 million in ad spend.
• The team at 6sense, led by Jason Zintak, has mapped over 5.5 million companies worldwide to create a powerful identity graph. They combine a client’s first-party data with this graph to run “sniper-like” campaigns, a strategy that tripled revenue and grew their customer base to over 150 companies.
• Eris Veseli of Alfinder uses AI to conduct deep behavioral analysis on a brand’s end customers. By understanding their likes, hobbies, and interests, Alfinder helps marketing agencies generate hyper-targeted strategies and build seed audiences based on psychographics, not just demographics.
• The team at Datalyse uses browser notifications to help retailers and publishers retarget users. By identifying subscribers who opt-in, they create a list of engaged users that can be used for building powerful lookalike audiences to find new potential subscribers across the web, growing to over 400 customers.
• Drew D’Agostino, CEO of Crystal, built a massive free user base of 30,000-40,000 monthly sign-ups for his personality assessment tool. By analyzing this user data, his team identifies patterns in high-value users, which they use to create lookalike audiences for their enterprise sales motion, helping them reach a $4.2 million run rate.
• Paul Towers of Smartfeat helps brick-and-mortar retailers identify their customers by offering free Wi-Fi in exchange for a social media login. This allows them to build a database of in-store customers, which is a powerful and unique seed audience for creating lookalike campaigns to attract similar local shoppers.
• Jeremy Haynes of Megalodon Marketing described his “omnipresent advertising model,” where he creates hyper-contextual retargeting audiences based on content consumption. As soon as a lead shows interest in a topic, they are added to a specific audience and targeted across all social channels, a strategy he used to help Grant Cardone crack a million dollars a month in digital revenue.
• Mark Mader, CEO of Smartsheet, highlighted the importance of a partner ecosystem. By integrating with platforms like the Office 365 and Google G Suite marketplaces, Smartsheet gets in front of millions of users, creating a massive top-of-funnel that can be analyzed to identify ideal user profiles for lookalike targeting, helping them grow to an $80 million run rate.
• Jimmy M, founder of megaleads.com, built a business on providing clean, accurate B2B sales leads. His customers, often high-volume call centers, use these lists for direct outreach and can also upload their best conversions to create lookalike audiences for platforms like LinkedIn, helping him scale to over 1,000 customers.
• Matt Archer is building Mahana.io to help teams collaborate more effectively. His initial go-to-market strategy involves direct email outreach to professionals in agile user groups on LinkedIn, creating a focused list of ideal early adopters that he can later use to model lookalike audiences.
• Zach Hedges, CEO of Aimi Social, used a pre-launch Facebook group to build a community of over 1,000 interested users before his app went live. This highly engaged group served as the initial seed audience for lookalike campaigns and helped the company launch with over $20,000 in monthly recurring revenue from day one.

Conclusion

You’ve just learned how top SaaS founders use Lookalike Advertising to transform their growth trajectory, turning existing customer data into a predictable engine for acquiring new, high-value users. By building on a foundation of their best customers, these leaders create highly targeted campaigns that deliver exceptional ROI, scaling their companies to millions in revenue. Now it’s your turn to apply this 4-step playbook and the dozens of examples to your own business and unlock your next stage of growth. To get started and explore how to fund these new initiatives without dilution, see how Founderpath can help you grow.

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