Gianluca Carrera
← The register

How deals are classified

Two tests, applied in order, always from the data owner’s seat.

Why the seat matters. The same deal reads differently from each side. A dataset sold into someone else’s product is a sell for the owner and a wrap for whoever embeds it. This register always classifies from the position of the party that owns the data.
Test 1

Who receives the value?

Internal — the asset makes the owner’s own operations or existing offer better, and no external party pays for it → improve. Stop here.
External — an external party pays → go to test 2.

Test 2

What is that party paying for?

The data, or an insight derived from it, is the deliverable — it is the line item → sell.
A product the data is inseparable from — the buyer cannot purchase the data without buying the product → wrap.

The cases that catch people out

The rake, and when it is “on loan”

The rake is the share of the value created that a data business keeps, deal after deal. It is owned where the owner does the enrichment. It is on loan where a partner does it: there is a rake, but it is contingent — if the partner walks, the value walks with them.

Where the buyer does the enrichment there is no downstream rake at all. The owner sold an input for a fee and the buyer keeps what it builds, permanently. A renewal in that arrangement re-prices the next licence; it does not recover the last one. The question worth asking there is whether the fee was under-priced — which is a sharper criticism, not a softer one.

Two kinds of non-answer

Unclear means there is a route but the public facts do not settle which. These entries are published anyway — a named deal marked unclear is more useful than a confident guess. No route means the event is not a monetisation event at all: a standards document, a capability acquisition. Those are reviewed and left out entirely.

What this register cannot show

Improve has no counterparty, so it produces no announcement. A register built from public disclosures structurally under-counts it. Nothing here is a complete picture of how data is monetised — only of how it is monetised in public.