The Problem
Drip was an eight-year-old product Frankensteined together across multiple eras. Loved by some customers, frustrating others. A team of nine that contracted to six in a RIF. And a positioning problem nobody had solved.
Since 2018, Drip had positioned as "eCRM." But that race was over. Klaviyo won it the way gravity wins—integrate with Shopify and you're off and running. Drip was competing for ecommerce customers against a company that had already locked them up.
Revenue and NPS told the story. The company knew something was wrong. They didn't know what to do about it.
It was the first job in twenty years I didn't network my way into. Cold application. The title was Principal UX Designer; the actual job was figuring out what Drip should become.
The question: If you can't win the ecommerce race, what race should you be running?
The Insight
The answer was already in the data. Drip's research showed which customers succeeded with the platform—and they weren't the ecommerce sellers Klaviyo was courting. They were marketers with higher-priced goods and longer, high-touch sales cycles. Content creators. Event organizers. Businesses where the purchase requires nurturing, not just a discount code.
I'd seen this pattern before. At Mailchimp, I'd learned that customers who understood why to market—not just how to use the tool—were the ones who stuck. The ones who just learned which button to press churned the moment someone built a shinier button. The Hawke Method, a framework for actionable marketing strategy, backed it up with specific metrics: time to first purchase, customer lifetime value, journey stage indicators. Metrics that predict revenue instead of eulogizing it.
The customers Drip should be serving already think in intervention points. They just didn't have a platform that thought the same way.
I named the customer: The Nurture Marketer. Strategic marketers at B2C SMBs selling products with longer consideration cycles. People who market on time (the right message at the right moment) and over time (nurturing the relationship across the entire lifecycle).
The System
Every ESP answers the same question: "What happened?" I designed an intelligence layer that answers a different one: "Where should you intervene, and what should you do?"
The Intelligence Layer
Traditional ESPs say: "Here's your dashboard. Here are your segments. Here are your automations." Then wish you luck the way a car dealership wishes you luck after selling you an engine with no steering wheel.
The system I designed inverts this. It says:
- "You have 340 customers who purchased once 45+ days ago and haven't returned. This is your highest-leverage win-back opportunity."
- "Your time-to-first-purchase is 12 days. Customers who don't convert by day 8 rarely convert at all. Here's where to intervene."
- "This segment is entering churn risk. Here's a campaign type that works for this pattern."
The platform identifies the intervention point. The customer executes the campaign. And critically: this could be automated. Segment entry triggers the intervention. The system doesn't just surface insight—it acts on it.
The Prototype
I designed the system in Figma and used v0 to translate designs into working code—a prototype that could hit real customer data and calculate metrics across time periods. The goal was a live proof of concept, not a pitch deck.
Drip's data was closely guarded. I worked with the Data Science team to get access. And when we connected the prototype to real data, the system broke almost immediately.
What Killed It
The data was foul. One-third of the time, our calculations of time to first purchase returned negative days. The data had invented time travel. The data was wrong about time travel. A backfill had corrupted the underlying records. You can't build an intelligence layer on a foundation that tells you customers bought things before they existed.
Finding the corrupted data was the end of my belief that the product vision could ship. A system is only as good as the infrastructure underneath it. I'd designed something strategically right and operationally impossible—not because the idea was flawed, but because the data couldn't support it.
What Survived
The intelligence layer didn't ship. The strategic repositioning did.
My VP got it immediately. The C-level had been looking for a direction that wasn't eCRM, and the Nurture Marketing positioning fit with every piece of research showing which customers thrived on the platform and which churned.
I sold the vision up the chain. VP. C-level. Board (via the C-level). And finally, the entire company in an all-hands meeting that set the new direction.
The new company vision: "The world's most powerful Nurture Marketing Platform."
The mission: "Empowering B2C SMBs to convert long-sales-cycle prospects into lifelong buyers through marketing automations."
The vision survived the product. The product didn't survive the company.
Why It Still Matters
The insight stands: ESPs are competing on the wrong layer.
More automations, more integrations, more templates—these are commodity features. The defensible product is the one that tells customers what to do and when to do it. The one that turns data into decisions.
Klaviyo doesn't do this. Mailchimp doesn't do this. The entire category is stuck on "here's what happened" when the customer is asking "what should I do?"
The proof is in the customers who get it. OneCommune—a Drip customer—generates 95% of their revenue through the platform. 17% year-over-year growth. They're not using Drip as a broadcast tool. They're using it as a nurture engine, marketing on time and over time.
That's the future of the category. Drip won't build it. Someone else will.