Simplify the life of your teams and multiply your performances

AI doesn't turn bad data into good decisions. In this Business Talk, Thomas Pinte (Netvigie), Nicolas Malo and Hugo Stepien (Optimal Ways) explain how to make your digital and e-commerce data reliable before entrusting them to AI.

Tracking governance is based on two actions: describing what should be collected, then verifying that this is the case.

“Agree with the governance of Tracking. But concretely, where do we start? ”

This is the question that comes up after each exchange on the subject. And it's a good question: a better maintained tagging plan, controls before and after production, reliable KPIs... all this remains theoretical until we see what it looks like on a Tuesday morning.

In the twenty years that Netvigie has been working with Digital, Data and QA teams, we have almost always found the same four situations: a tagging plan that has expired, a handmade recipe before each release, alerts that we cannot prioritize, and brands that are each drifting their own way.

Here is what they give on a daily basis and what we respond to them.

A KPI is moving. The conversion rate is falling. A campaign seems to be less efficient.

At Netvigie, after ten years of working on Data Quality issues, we learned something quite simple: an alert is only valuable if someone knows what to do with it.

The problem is that a dashboard can continue to show a perfectly normal figure even though the collection has deteriorated.

Maybe your dashboards are accurate.

However, the data that feeds them must also be fed.

Today, digital teams are investing in ever more efficient analysis tools. However, they continue to face tracking anomalies detected too late, alerts that are difficult to interpret, or incidents that go unnoticed until they impact business decisions.

The real challenge is therefore no longer just to measure the performance of a site or an application.

It is to be able to trust the data that is used to manage the activity.