Repricing to Create a Business

TL;DR

The Data API was priced like a side feature, not a business. I raised the base price ~50% and restructured a single flat plan into self-serve tiers plus usage-based add-ons, with a clear path up to enterprise. Result: 100+ logos in six months and unit economics that finally made sense.

Context

When I took over pricing for the Data API, the base plan was cheap enough that nobody upstairs treated the API as a real revenue line. It was a flat plan that lumped everyone together — the hobbyist running a few hundred lookups a month paid the same shape of bill as the agency pulling millions of rows. That meant we left money on the table from heavy users and signaled "cheap tool" to exactly the enterprise buyers we wanted.

Problem

• The base price was too low to fund the roadmap or signal enterprise-grade quality
• A single flat plan couldn't separate light users from heavy users — usage and price were disconnected
• No natural path from self-serve into a contract, so larger accounts had nowhere to grow
• Price didn't reflect the value heavy users were actually extracting from the data

The Insight

The usage data told the story: demand was concentrated, not evenly spread. A large tail of accounts barely touched the API while a small group hammered it — and that small group was where almost all the real value (and willingness to pay) lived. The flat plan was quietly subsidizing the heavy users with the light ones, and capping our upside on exactly the customers who'd have happily paid more.

That reframed the whole project. This wasn't a "bump the price" exercise — it was a packaging problem. The bet I made: raise the floor so the base price signals quality and filters out churn-prone bargain hunters, then let the heavy users self-select up through usage-based add-ons instead of forcing them into one-size-fits-all. Charge for value where value is actually consumed.

What I Did

1. Segmented by behavior, not by gut. Cut the customer base by usage, retention, and willingness to pay to find where revenue actually concentrated.
2. Benchmarked the category. Compared our packaging against comparable data APIs to set a credible floor.
3. Made credits the value metric. Tied price to credit consumption so the bill tracked the value a customer pulled from the data.
4. Designed tiers + add-ons. Built self-serve tiers with usage-based add-ons on top, so light users have a clean entry point and heavy users can scale without renegotiating.

Key Decisions

Raise the floor ~50%

I raised the base price roughly 50%. Counterintuitively it helped conversion: a higher floor signaled the product was serious, and it filtered out the price-sensitive accounts that churned fastest anyway.

Self-serve tiers + usage add-ons

I moved from one flat plan to a small set of self-serve tiers with usage-based add-ons. Light users get a clean, cheap entry point; heavy users buy more capacity as they grow — no sales call required until they genuinely need a contract.

A real path to enterprise

The top of the self-serve ladder hands off cleanly into an enterprise motion with dedicated support, so the accounts that outgrew self-serve had somewhere to go instead of hitting a wall.

Results

• Landed enterprise accounts on top of a self-serve base — sustainable unit economics across the board
• Higher-quality customers with better retention than the old flat plan attracted
• A clear upgrade path that turned the API from a flat fee into expansion revenue

Lessons Learned

1. Price signals value. Too-low pricing hurt us. Raising the floor attracted better customers, not fewer.
2. Charge where value is consumed. Usage-based add-ons meant heavy users paid for what they actually pulled — and stopped being subsidized by everyone else.
3. Repricing is really repackaging. The win wasn't a bigger number; it was a structure that let different customers self-select into the right plan.
4. Don't fear the increase. Existing customers accepted it, and new customers never knew the old price.