Citric Sheep Data Commercialisation Program
Could AI agents turn your existing data into revenue?
Most companies are sitting on operational data that never reaches the P&L. The Hidden Data Asset Kit helps you work out whether your records, benchmarks, field data, pricing history, or research data could become a new revenue stream.
Free guide
The Hidden Data Asset Kit
A practical worksheet for business owners and new CDOs who suspect there may be value in the data they already collect.
- The 5-minute hidden data asset test
- Examples of data buyers and what they actually pay for
- A scoring framework for quality, uniqueness, commercial value, and readiness
- A worksheet for assessing one dataset before you build anything
- Red flags that should stop a data commercialisation project early
Why this matters
The hidden asset is different in every market.
It might be inspection history, customer demand patterns, equipment failures, school performance records, agricultural samples, pricing history, compliance outcomes, or a hard-to-repeat manual research dataset.
The first deliverable is not a product. It is clarity: what data you have, why it may be scarce, who might buy it, and whether the economics are worth pursuing.
Operational records your competitors cannot easily recreate
Pricing, demand, performance, risk, inspection, or benchmark history
Data collected over months or years as a byproduct of normal work
Records that help buyers make investment, pricing, underwriting, or market decisions
Who buys this data?
Data buyers pay for better decisions, not interesting spreadsheets.
The kit helps you connect the dataset to the business decisions buyers already care about.
Private equity and investors
Use niche datasets to assess markets, spot outperformers, and validate acquisition theses.
Consultancies
Buy benchmarks and evidence that make client strategy work sharper and faster.
Insurers and lenders
Pay for signals that improve risk, pricing, underwriting, and portfolio decisions.
Software and AI companies
Need proprietary data for product features, enrichment, training, and validation.
Proof point
Data commercialisation is already creating real revenue streams.
One education data example turned internal research and school-market records into commercial reports for buyers who needed better market intelligence.
- $800k/year projected from a commercialised education dataset
- $7.5k report pricing from packaged school market intelligence
- Multiple buyer categories from one underlying dataset
Results depend on data quality, buyer demand, rights, and execution. The kit is designed to test those assumptions before you over-invest.
How to use the kit
Score one dataset before building anything.
Identify the asset
List the data your business already creates through operations, service delivery, research, compliance, or customer workflows.
Score the opportunity
Check uniqueness, buyer value, rights, data quality, historical depth, refresh economics, and internal readiness.
Test buyer demand
Before building dashboards or APIs, define who might buy it and what decision the data helps them make.
Get the lead magnet
Download the Hidden Data Asset Kit.
Use it to assess whether your company already has data that could be packaged, licensed, or sold.
If the score looks promising, the next step is a short DCP assessment: what data exists, who might buy it, and whether buyer demand is strong enough to justify productising it.
This page is ready for the permanent form integration. For now, requests route to [email protected].