How much is bad data costing you right now?

See what failed deliveries, email bounces and wasted SMS cost you each year, and an estimate of how much validation could recover. No sign-up needed.

average cost of a failed US deliveryLast Mile Consortium
$17.20
of US delivery failures trace back to bad addressesUS Census Bureau
22%
of mobile numbers go stale every yearNeustar 2024
30%
Start with your industry

The numbers below are starting points for e-commerce, not measurements of your data. Replace them with your own.

$62K a yearlost to bad data today
10,000
$5K a yearlost to bad data today
50,000
$346 a yearlost to bad data today
20,000
Estimated recoverable cost$59K

Your yearly cost × assumed catch rates of 87% (address), 90% (email) and 85% (phone). Assumptions, not guarantees. How it's calculated

  • Failed deliveries (address)$54K
  • Email platform spend$5K
  • Wasted texts (phone)$294
Revenue opportunity$10K

New sign-ups only: 2,592 invalid emails a year caught at sign-up (assumed 90%), at your conversion rate and average order value. Old bad emails on your list aren't counted.

Estimated yearly total Before the cost of DQVerify credits. See credit prices$68K
Book a demo

How this calculator works.

It estimates your yearly cost of bad contact data and how much of it validation could recover, using only the numbers you enter or the defaults for the industry you pick. Change any input to match your own data.

Failed deliveries (address)

Yearly shipments or mailings are multiplied by your bad-address rate to estimate failed deliveries. Each one costs your re-ship, return, or re-routing cost. The model assumes validation prevents 87% of that waste.

monthly shipments × 12 × bad-address % × cost per failure × 87%

Wasted email spend

Invalid addresses in your list still cost money each month in email platform fees, which are usually priced per contact. The model assumes validation removes 90% of those invalid contacts.

list size × invalid % × monthly cost per contact × 12 × 90%

Wasted SMS (phone)

Texts sent to invalid or unreachable numbers are charged by your SMS provider but never delivered. The model assumes validation stops 85% of those sends.

monthly SMS × 12 × invalid-number % × cost per SMS × 85%

Revenue opportunity

New sign-ups who enter an invalid email (a typo or a mistyped domain) never get your messages. The model assumes validation at sign-up catches 90% of them and applies your conversion rate and average order value. Old invalid emails already on your list are not counted, because they cannot be recovered. This is the most speculative part of the estimate.

new sign-ups per month × 12 × invalid % × 90% × conversion rate × average order value

What the estimate leaves out

  • Results are gross savings before the cost of DQVerify credits. Compare them with the pricing calculator to see net return.
  • Industry defaults are starting points for a typical business in that sector, not measurements of your data. Replace them with your own figures for a realistic result.
  • Catch rates are assumptions, not guarantees. Actual results depend on how your data was collected and how old it is.
  • Harder-to-measure costs are not included: support time, sender-reputation damage, compliance risk, and customers lost after a failed delivery.

Now check your own records.

The calculator gives an estimate. Run a sample of your real list with 1,000 free credits to see the actual numbers. No sales call, no contract.

Book a demo
1,000 free credits for 14 days. No credit card. Business email required. Offer ends Nov 30.