Churnly.ai

Adam's journey to building Churnly.ai came from pattern recognition across multiple roles. After leading user-generated content at The Guardian and previously building Blotter—a company that championed user-generated content with machine learning authentication—he transitioned into angel investing. In every boardroom meeting and investor discussion, the same problem surfaced: churn. "Every company, so both companies I've had with churn customers, and as a SaaS business, it's very painful," he explains. "And as I've kind of evolved my career, and I've become more of an investor in other companies in kind of early-stage businesses, churn is a big problem. Every boardroom and every meeting I sit in, it's all about how we reduce churn, how we understand churn better."

Adam spent 12 months in deep engineering mode before officially launching in June 2018, investing approximately $300K of his own money from previous exits. The high cost revealed an early challenge: churn models aren't inherently scalable. "What we discovered very early on is that churn models aren't very scalable," he says. "So, we started out with a bunch of a group of customers, five or six customers that gave us their data, all very different customers, all SaaS, but all very different markets, and very different definitions of churn and kind of triggers of churn." Building a model that worked across verticals required bringing in outside experts and expanding the team to four software engineers and seven data scientists.

Adam's first customers came from free trials—the initial five or six customers who helped refine the model converted to paid once the product proved valuable. Before monetizing, he had used a Squarespace landing page shared in Facebook groups and Cora, generating 270 signups for a waiting list. The company systematically worked through that list while simultaneously investing in SEO, hiring an external agency at $400/month. That investment paid off: "We find that currently through SEO, we're getting about six leads a week coming through," he notes. The company also attended SaaStoff, picking up 75 leads and closing one deal nearly a year later. Today, Churnly ranks on page one for "customer churn software" queries, particularly in Brazil where they've acquired four customers.

Organic growth through SEO proved the most effective channel, generating six qualified leads per week at minimal cost. Conference sponsorships showed promise but required the founder's in-person presence. Paid channels were never explored—Adam focused on product-market fit before scaling sales. "At the moment, we're not spending anything really, to be honest. Apart from our own internal resources," he explains. The pricing model evolved through iteration: the company tested percentage-of-revenue and customer-count models before landing on $700–$1,200/month (averaging $900) based on lost customers and existing customer base. Onboarding remained high-touch, with custom integrations and dashboards built for each customer.

With 20 paying customers generating ~$18K/month in revenue, Churnly is still pre-product-market-fit but demonstrating clear product-customer fit for specific segments. The team has grown to 12 people, primarily engineers and data scientists. Adam continues as the sole commercial person, deliberately holding back on scaling sales until he's learned the motion deeply and hit certain metrics that would justify raising capital. "My goal is to kind of... We've got a couple of metrics that we really want to hit that I think we need to hit to be able to go out and raise some cash," he says. The company is burning $40K/month—a burn rate Adam can sustain from previous exits but wants to eliminate by growing revenue and improving unit economics. "This is all about product," he concludes. "We have to nail products. And it's a really complex problem to solve. If we get it right and scale, I think we've got an amazing business here."