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Article5 min read

Common Identity Resolution Mistakes to Avoid

Five mistakes that have nothing to do with the match itself: treating intent as a sales tool, starting in the middle, buying with no stack or operator, trusting a blended match rate, and never closing the loop.

By Gregory Kotovos

identity resolutionmistakesintent datamatch ratevendor evaluation

Identity resolution

Five mistakes are worth avoiding. None of them is a failure of the match itself. All of them are failures of what a company does around it.

1. Treating intent as a sales tool

People do not know how to use person-based intent yet, and the instinct is to make it a sales tool: a signal fires and a rep gets pinged. Intent should inform intelligence. It should not directly personalize or respond.

Take someone researching pricing for a solution. The wrong response is a message asking whether they found what they were looking for, or one thanking them for stopping by. Both announce that you were watching. The right response meets them where they are in the journey: work out what stage they are in, and give them content that moves them to the next one.

Feed the signal into the scoring or trigger methodology for the next stage of the buyer journey. The customer experience post walks through the sequence, and the intent data guide covers how the signal is scored.

2. Starting in the middle

Most of the value comes from starting at the beginning. Design the audience that fits the need. Build the total addressable market. Apply intent to see which companies and which people are in market. Then send emails and ads, put the audience on social, and close the loop.

Start at the pixel and skip the design, and you have data with no audience to point it at.

3. Buying without a stack or an operator

This is not a sales tool. It builds the whole conversation with your customers, and that conversation needs a MarTech stack to run in and a person to operate it. Without both, my advice is not to buy yet. The fit checklist has the full list.

4. Trusting a blended match rate

A match rate is only as useful as its denominator. Ask two questions. Is the percentage a share of all your traffic, or a share of the records the vendor chose to return? And does one deterministic source make the match, or does an algorithm choose between the answers of several providers?

A percentage of what comes back will always look better than a percentage of what came in. Deploy the pixel and read the rate in the interface against all of your own traffic. That is the test that cannot be argued with. The honest numbers and the RFI guide set out the questions in full.

5. Never closing the loop

Sending the emails and the ads is half the cycle. The other half is reading who responded, who did not, and who showed up through a different tactic, and then retargeting those people. What you learn feeds cross-sell, upsell, opportunity acceleration and advocacy.

A campaign that stops at delivery is the open loop you started with. What happens without identity resolution shows what a closed one looks like.

A quick check

  • Does a signal go into a stage-by-stage trigger, or into a rep alert?
  • Did you design the audience before you placed the pixel?
  • Do you have a stack and an operator?
  • Is your match rate measured on all of your traffic, by one deterministic source?
  • Can you name who responded and who did not?

What identity resolution is has the definitions behind all five.

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