Free Tool · Total Cost of Ownership

TCO Calculator: What your data will really cost

Compare quotes from different data vendors to understand the true price per usable record.

Why this calculator exists

Price per record only measures the cost of an attempt

Almost every quote gets compared on “price per record”. That’s the number on the pricing page and in the spreadsheet, so it’s the number people anchor to. But price per record only measures the cost of an attempt. It says nothing about how much of what arrives is actually usable. And usable is really two questions, not one: did the crawler find the record at all (recall), and of the records it did return, how many are correct (accuracy). Missing data isn’t the same as wrong data, but both land in the same equation:

True price per usable record=PriceRecords × Accuracy × Recall

Here’s why splitting the figure matters. A vendor that finds 85% of records and is 85% accurate on the ones it found sounds fine in isolation. But 0.85 × 0.85 lands at roughly 72% usable data. Two reasonable-sounding numbers multiply into one uncomfortable one. And a record is only fully correct if every field is correct, so the gap widens with each field you add. That’s the whole game, and the calculator below shows it on your numbers.

01

Usable records

Recall × accuracy, compounded across every field in a record. The number that makes two quotes comparable, and rarely the one on the pricing page.

02

Your cleanup cost

The months your own QA team spends closing the cheaper vendor’s gap. People stuck cleaning data that was supposed to arrive clean.

03

Churn exposure

A wrong record doesn’t announce itself. Whatever your team doesn’t catch, your customers will. This is what a year of that costs, kept separate from the hard total.

How to use it
1

Drop in your quotesReplace the defaults with the two quotes you’re actually weighing. Every figure is editable.

2

Set your assumptionsRecall, accuracy, fields per record, what your QA team costs, and what a lost customer is worth.

3

Read the verdictThe numbers recalculate live as you type. Enter your business email to see the full breakdown.

The two quotes
Quality — recall & accuracy per field
Your in-house cleanup of the cheaper option
Your churn exposure due to unsatisfactory data quality — to calculate the true impact of data quality on your business
Usable data rate Recall × accuracy, compounded across fields
0%25%50%75%100%
Lower-quality vendor — usable records
Higher-quality vendor — usable records
Cost per usable record lower is better
$0$5$10+
Cost per usable record — lower-quality vendor
Cost per usable record — higher-quality vendor
Your cleanup cost (lower-quality vendor)
Your churn exposure
per year, from low-quality data
True total — lower-quality vendor
price + your cleanup cost
True total — higher-quality vendor
price for a fully managed data delivery
Adding churn to the equation
Total exposure, year one — lower-quality vendor
Price/record + cleanup + one year of churn from losing customers to low-quality data.
Model assumes ~21 working days/month, and treats the higher-quality vendor's downstream cleanup as negligible for illustration (adjust its recall/accuracy to test that). Review throughput varies widely by task — simple fields run faster, ambiguous ones much slower. Churn is an estimate; it is kept out of the hard True Total above and shown separately in a year-one Total Exposure figure (price + cleanup + one year of churn) so you can see its weight without it inflating the defensible number. These are planning figures, not a guarantee.
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Want the full math behind this model?

The calculator is the short version. The full article walks through the worked vendor comparison, the cost multipliers most quotes never mention, and the five-layer QA system behind our 95%+ accuracy.