How we 3×'d MRR pipeline for with SEO and AI Search

People searching "quiz funnel examples" or "how to build a lead funnel for recruiting" aren't just looking for inspiration, they're picturing a solution they can actually use. If the article shows them working examples built in Heyflow, they arrive at the product already half-convinced, or at minimum pre-qualified.

We built a set of editorial pieces that worked exactly this way: real examples, real use cases, real walkthroughs, never a generic listicle. The content piece about quiz funnel examples became one of the top traffic pages on the site. Buyers arrive already knowing what they want to build, and the distance to a trial collapses.

Most agencies will tell you good SEO content takes weeks to produce and months to index. That is true when you do it one page at a time. We built and published entire clusters in days, at quality. Speed was a strategic choice, grounded in the shared goal of moving pipeline numbers fast.

By now we launched 5 programmatic clusters across a full range of high-intent topics: tracking and analytics, integrations, form types built for specific target groups, and competitor alternative pages. Each page targets a different entry point, but shares two things: low competition and high buyer intent.

Each cluster page was built from a foundation of real knowledge: Help Center documentation, product specifications, and expert input from the Heyflow team. The content answers a specific job to be done, then connects it back to the product. Heyflow now has programmatic depth across topics most competitors haven't identified as an opportunity.

The Help Center had real depth, product accuracy, step-by-step instructions, correct feature names, but it wasn't structured to be found or cited. We ran a systematic pass across five major levers: title rewrites, heading structure, use-case sections, feature-name precision, meta data. Each article sits at the intersection of product accuracy, user intent, and LLM readability, and getting all four right at once takes real work.

Help Center articles started appearing as cited sources in AI answers. They also began ranking in Google organic results, not just AI surfaces.

Want to see it yourself? Type "how to connect Heyflow" into Google and see which results come up.

Being the best source on your own domain is not enough. AI engines triangulate across the web, and the sources they trust most are often not the brand's own pages. The right approach is to identify which channels move the needle first, build there, and layer outward.

On Reddit we identified high-traffic threads where buyers were asking funnel builder comparison questions. Amir started engaging directly with his own account, because a founder-level voice in a relevant thread reads differently than a marketing comment, and it compounds if the thread stays in rotation as an AI source. That was one of many initiatives: LinkedIn Pulse articles Amir posted under his own profile, and work to strengthen Heyflow's presence on review platforms, are a couple more. Each works on its own, but bundled together they compound.

We cross-referenced Heyflow's existing YouTube library (under 1,000 subscribers, zero AI citations) against the tracked prompt set, then rewrote titles and descriptions on 20 matched videos. Within three months, 22 videos were regularly cited, the top one retrieved 110 times in a single month, and several started showing up natively embedded inside Google AI Overviews, thumbnail and all.

There's a lot more to say about what made this work, so we wrote the full breakdown. Check it out.

SEO, AI Search, and content run as one loop at Radyant. The Heyflow case shows what's possible when you treat them that way. The strategy was built against Heyflow's specific goals, product, and buyer journey. The Radyant team stayed in close, weekly exchange with Amir and the Heyflow team throughout, sharing data and adjusting priorities.

Speed was a deliberate choice, and the timeline shows it: kickoff was December 1, YouTube optimization started December 9, Help Center work began December 12, and the first visibility gains were already showing before the month was out. When something was working, we moved fast and scaled it. When something wasn't, we flagged it.

That same closeness shapes how we approach the work itself. Every client is different, every product and every audience is different, and what works at scale for one brand doesn't transplant blindly into another. The patterns we've built across other clients still inform the approach, we know what kinds of content get cited, which cluster types convert, how to read the signal, but the application is always specific to the product and the moment.

Not every agency works this way, and we're not saying it's the only path to results. But it's our philosophy: close, proactive, with real stake in the outcome. In Heyflow's case, it's what made the difference.