Three weeks. One prototype. A $1M contract.

The situation

Conviva's analytics were built by data scientists, for data scientists, in the vocabulary of buffer ratios and bitrate. The platform reads more than five trillion events a day, and for years the people reading the output spoke the same language as the data.

Then the platform expanded from streaming into new verticals: retail, ecommerce, travel. The new buyers are product managers who carry revenue responsibility, have thirty minutes between meetings, and have zero tolerance for cognitive overload. They do not need more data or more filters. They need answers. The legacy design, repurposed, did not resonate.

A Fortune 500 retail account brought it to a head. The technology passed every test. The experience was the dealbreaker, and the evaluation came down to the experience layer. I'd been advising the CEO and CPO on exactly this for months. They asked me to build the reimagining. Solo, three weeks.

The reframe

Everyone saw an analytics product that needed to look friendlier for a new audience. I saw Tesler's Law of the Conservation of Complexity. Every application has an irreducible amount of complexity, and the only real question is who has to deal with it. The legacy interface put that complexity on the user, because it was built by people who spoke the language of the data for people who spoke the same language. The new buyer does not, and should not have to.

So my answer, across every decision, was the same. The complexity of analyzing five trillion events a day belongs to the system, not the user. Not the user, not anymore.

The work

I built the prototype myself, in three weeks, as a working system rather than a set of screens. The premise was insight-first. The system proactively surfaces what matters, prioritized by revenue impact, in plain language. Intelligence is the starting point, not the reward for hours of analysis.

Navigation followed intent, not tool categories. It organized around three things a user actually comes to do: Monitor, Investigate, Optimize. And it used progressive disclosure to keep the complexity where it belonged. Answers first, evidence on demand, raw data only if you want it. The north star for the overview was a person seeing a good day or a bad day in ten seconds.

The structural artifact was a three-tier investigation model. Tier 1 is proactive intelligence: Monitor, answering “what needs my attention?” Tier 2 is assisted investigation: Investigate, answering “why is this happening?”, conversational, run with the product's AI assistant. Tier 3 is manual exploration: Analyze, full control for power users, for validation and edge cases. The principle governs the whole thing. Most users should get their answer at Tier 1 or 2. If the majority need Tier 3 to do their jobs, the AI has failed. Every tier traces back to Tesler's Law, because at each one the complexity of reading five trillion events a day has already shifted from the person to the system.

Working solo was a method, not a constraint. One person holding vision, interaction, and the running build meant no handoff, no interpretation gap, and a new answer to the client's reaction inside a day instead of a sprint. I have argued in How to Lead Design in the AI Era that a prototype should be the argument a design leader makes. The book introduced the idea. This proved it, in production conditions, against a real contract, on a three-week clock.

The outcome

A stakeholder at the account gave the verdict in two words.

“10x better.”

Within days the account signed a $1M year-over-year contract, a starter deal expected to grow. The prototype did not close an existing deal. It created one.

And it did something the company had never done. For the first time in Conviva's history, sales and marketing began pitching the user experience as a competitive advantage. The sales kickoff, the decks, the demos pivoted to the interface. Design went from invisible infrastructure to a revenue driver.