Add-to-cart, checkout, and purchase events often fire with missing or wrong data, on Google Tag Manager, native app integrations, and shop systems alike. When that happens, Meta and Google optimize toward whatever they actually receive, and you pay for it.
Add-to-cart, checkout, and purchase each teach the algorithm something different — miss one, or send it wrong, and optimization suffers.
Meta, Google, and TikTok all optimize toward the events you send them. Send add-to-cart, checkout, or purchase with missing or wrong values, and they'll spend your budget chasing the wrong signal — no matter how the event was implemented.
Whether it's wired through Google Tag Manager, a native app, or your shop system, the same event can be configured well or poorly.
Many stores fire an add-to-cart event when a visitor views the cart page, not when they actually add a product. That single substitution can undercount real purchase intent by 40 to 50 percent, and Meta or Google never knows the difference, because from their side, the event fired exactly as configured.
Purchase events have their own common defect: sending the order total including tax and shipping instead of the product subtotal, which can inflate reported revenue by 10 percent or more and throws off value-based bidding. The setup itself also varies by platform, and by how it's configured. Shopify's native Meta integration can pair a browser pixel with matching server-side calls, but only when data sharing is set to the right level; at the default level, the server-side half is often limited or off, so what looks installed may be sending far less than it could. Native channels for other platforms differ again in how much they send server-side and how much is left for the merchant to switch on. WooCommerce has no native Meta integration; it depends on a third-party plugin, and caching plugins frequently break the server-side call silently.
We check whether add-to-cart, checkout, and purchase all fire with the right parameters, on the actual platform and integration you use, not just whether a dashboard shows a green checkmark.
We check the event against what a correct implementation looks like for that platform, not just whether it fired.
We classify what actually fires, and how much usable data it carries.
When deep signals are weak, the campaign keeps spending while the platform learns from the wrong thing.
A flagged event isn't the end of the check. It's the start of knowing where to look next.
A missing page-view event rarely changes what a campaign optimizes toward. A missing purchase event changes everything, because that's the signal the platform is actually trying to find more of. The same word, missing, means something completely different depending on where in the funnel it happens.
Teams that treat every gap the same way waste time chasing shallow events while a deep one, the kind that actually shapes optimization, sits unresolved for weeks.
Azulens flags gaps by how deep they sit in the funnel and how much they're likely shaping optimization, so the first thing a team sees is the signal most worth fixing.
Not every gap is equally urgent. Azulens ranks them by how deep in the funnel they sit, not just that they're missing.
Some events fire correctly. Others fire with the wrong data. A credible check tells you which.
Fixing a wrong value or a missing parameter needs access to your setup. From the outside, we flag exactly which event and platform need a closer look.
It works best connected to the whole journey: ad, page, and conversion, on every channel.
Tell us about one campaign or funnel. We'll start from a live journey and flag which tracking signals are firing and which aren't.
