The Industry's Uncomfortable Truth About Ads, and Analytics Testing

When we implement analytics, before deploying any instrumentation, we test it.  Initial testing covers the basic functionality like "does a tag fire at the right time?", and "does ixt contain the right data?"

With unit testing tags out of the way, the testing enters a different phase – calibration.  When we calibrate the analytics, we match the desired output to the known input.

If a user enters the site from an organic search, and clicks through 5 pages, you'd expect to see this represented accurately in the reports.

We've automated this process to test the report data at a reasonable scale without taking too long, or costing too much.  It’s actually done in a few minutes and it’s pretty much free to execute.

But there’s a problem with some tags.  GA tags can be calibrated like this but Google Ads, Meta, TikTok, Pinterest, Snap, pretty much any paid advertising platform you care to mention doesn’t lend itself to calibration.

To legitimately test paid ads tagging end to end, you have to test against a live campaign. And that costs money. And that requires careful methodology to forensically test and analyse the data exhaust against the input.

Alternatively you could proxy the data via another tag, but that’s only confirming the trigger works, not the end to end data collection, and processing.

Uncomfortable truth incoming: Who, in their right mind, spends significant time and money on an ads campaign, without calibrating the reporting, and trusts the data being presented by the ads vendor?  BRACE, BRACE: Pretty much everybody.

It’s a rare occurrence for Agencies to sacrifice margin to fund these calibration campaigns.

Perhaps the best ads vendors could/can/will provide transparent calibration tool sets for this purpose? Limited with good reason to prevent abuse. Data will not be used in optimisation or model training - very much ring-fenced to confirm correctness before executing a live campaign. Yes?

Sandbox environments exist for API development and testing but do they have calibration equivalents - I'm all ears...

Agentic testing is actually a good employment of AI. Describe the test input, and have an agent execute the process and even assess the output. Perhaps ads vendors are preparing such an interface given the acceleration of agentic shopping? When humans aren’t your customers, you’ll want to have fine control over investment in attracting agents to your store.

Here’s the uncomfortable part to swallow: There is no easy solution to this hard problem.

What do you think? How do you manage this challenge? 

What’s your approach to building trust in the data without calibrating?

Answers on. a postcard sent to the usual address please.