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Product strategy and delivery

From feature backlog to
a clear monetisation roadmap

A commodity market data platform had a long feature list but no pricing model. We turned the backlog into a business model and then built it.

Marktdaten-Plattform, München

3 tiers

Freemium model

100 %

Packages with fixed price and acceptance criteria

The case

Where we started.

Situation

The platform delivered reliable commodity market data and had a growing user base. The missing piece was an answer to what customers should actually pay for. The backlog was a collection of good ideas without prioritisation, and every roadmap discussion ended with gut feeling.

Brief

The question was not "please build these features." It was: which features justify a price, which belong in the free tier, and in what order do we build?

Approach

What we did.

Freemium strategy developed

We sorted the features by what draws users into the platform and what moves them to pay. The result was a three-tier model with a clear boundary between the free entry point and the paid core.

Usage analytics and sales signals designed

Account health score and buying-signal notifications, so sales does not have to guess which account is ready for a conversation but can read it from usage behaviour.

Give-to-get benchmark as a differentiator

Users contribute their own data and receive an anonymised market comparison in return. That creates a data advantage competitors cannot simply buy.

Packageable delivery structure

The roadmap was cut into packages with fixed prices, timelines, and acceptance criteria. Decision-ready, not estimate-ready.
Results

What we delivered.

  • An unprioritised backlog became a monetisation roadmap
  • Three-tier freemium model with a clear value boundary
  • All delivery packages ready to commission with fixed prices and acceptance criteria
  • Sales working from usage signals rather than gut feeling
We expected someone to build our features. What we got first was the answer to which ones would actually earn money, and then the build.
Management · Market data platform, Munich
Technology used
  • Next.js
  • TypeScript
  • PostgreSQL
  • Analytics-Pipeline

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