AI analytics
Building the frontend, strategy, and ranking engine that won NetRanks its first clients.
NetRanks tracks how AI models mention a brand across ChatGPT, Perplexity, and Gemini. They needed to go from idea to a client-ready product, with a frontend, a clear strategy, and a ranking system credible enough to sell.
netranks.comA client-ready product, first paying clients, and stronger 30-day retention.
The challenge
NetRanks had a strong idea but no product to sell. They needed a frontend, a clear position in the market, and a ranking system that could stand up to scrutiny from technical buyers.
Without those pieces working together, they could not show value to a first set of customers or start real conversations.
The loop they ran
Each move keeps its source, shipped work, and measure attached.
- 01
Capture
Captured the founder vision, target buyers, and what first customers needed to see.
- 02
Rank
Ranked the build so the product and ranking system could win early clients fastest.
- 03
Spec
Specced the frontend, positioning, and ranking engine into clear work.
- 04
Ship
Built and shipped the frontend, strategy, and ranking system.
- 05
Measure
Measured against client readiness and real first customer conversations.
What this work shows
NetRanks
A first-clients and retention story: make the product credible enough to sell, then keep improving what customers value.
- Shape positioning that is legible to technical and marketing buyers.
- Turn a demoable product and ranking workflow into first paying-client conversations.
- Use measured 30-day retention to decide what the next message or product experiment should improve.
What changed
The result is only as useful as the evidence attached to it.
- 30-day retention measured in PostHog+19%
- reached a client-ready product and won early customers1st clients
- full product experience built from scratch0 to 1
- positioning and scoring system that supports salesRanking engine