How much is your business data worth?

What changes the estimate?

Useful volume matters more than a large file count. Repeated messages, empty records and duplicates do not necessarily add value. Buyers need enough context to understand the work.

History matters when it shows a process over time. A complete customer-support conversation or a sales opportunity from first question to result can reveal more than an isolated row.

Structure and connections matter. Dates, links between replies and clear stages help explain what happened. If records lose that context during export, the apparent volume may overstate their usefulness.

The agreed scope matters. Excluding a system, time period or sensitive category changes what can be licensed. A large company with a small usable scope may have less to offer than its headcount suggests.

Rights and restrictions matter. You need to establish what your company is allowed to license. Buyer exclusions and permitted uses belong in the agreement, not in assumptions made from a calculator.

Demand matters. A buyer may want a particular workflow, language, industry or level of detail. A useful dataset still needs a suitable buyer.

An example without an invented price

Consider two companies with 100 employees. One has a long support history with questions, replies and recorded outcomes. The other has duplicate files and short notes with no result recorded. Headcount does not make those datasets equivalent. This is an illustrative comparison, not a customer case study.

From estimate to a buyer deal

First, describe the systems and history in an assessment. Next, verify the counts using screenshots from your systems. Agree what is included and excluded. Your records stay in your systems during onboarding; data moves only after a buyer deal is agreed. A buyer's interest and the agreed terms determine the commercial outcome.

When would we get paid?

The agreement sets acceptance conditions, payment timing and your share of a completed sale. Do not budget against the calculator as if it were an invoice. Ask what triggers payment, what could delay acceptance and what happens if no buyer proceeds.

Can the same data earn more than once?

A dataset may be licensed to more than one buyer if the agreement permits it. Repeat sales are possible, not promised. Check exclusivity, future licensing rights and how payments are calculated before signing.

How do we compare two offers fairly?

Compare offers on a like-for-like basis. Write the exact records, permitted uses, duration, exclusivity and future-update obligations beside each payment. One offer could cover a defined export; another could include several years of updates. These are different commitments, even when the amounts look similar.

What will the offer cost us to deliver?

Ask your team to estimate the work needed to verify counts, review rights, apply exclusions and supply the agreed records. Identify external review costs and any continuing commitments. Ask which costs are your responsibility. Use that information to compare the expected return rather than relying only on the largest headline figure.

What evidence makes an offer worth taking seriously?

Separate an indicative calculator range from a written proposal with a defined scope and acceptance conditions. Ask what the buyer has evaluated, what remains subject to review and what could change the amount. Keep estimates, agreements and money received separate in your planning. Ask Maryah to walk through the assumptions before you commit.

Get a more useful estimate

Have your systems, approximate counts, years of history and exclusions ready. The detailed assessment helps scope the conversation. It does not require a raw-data upload.