The Best Creative in the World Can't Fix Bad Data

AI just made your bad data problem a lot more expensive.

This is the first part of a two-part series. Part two: Customers Know When Their Data Is Not Respected

Spray and pray. It's the unofficial strategy of more marketing teams than anyone would like to admit. Shoot wide, hope something sticks, and when the results disappoint, blame the creative. Or the algorithm. Or the agency. Rarely the data.

It makes sense why data gets ignored. It's not sexy. Nobody frames a dashboard and hangs it on the wall. Marketing directors want to talk about brand identity, visual direction and campaign concepts. Fair enough, that stuff matters. But when the foundation underneath all of it is shaky, even the best creative work is flying blind.

Bad data isn't just an efficiency problem. It's a reputation problem.

Think about the last time you got an SMS from a shop you visited once in 2019. Or an email congratulating you on a product you never bought. Or a retargeting ad for a holiday spot you already went to. You weren't impressed. You were annoyed. And that annoyance sticks to the brand, not to the system that sent the message.

Bad data doesn't just cost money in wasted ad spend. It costs trust. And trust is expensive to buy back.

Then came AI and made all of this ten times more important.

AI is extremely good at doing exactly what you ask it to do, based on whatever you give it to work with. Give it good data, good questions and clear goals, and it delivers. Give it a mess, and it will optimise your mess at record speed and at massive scale.

Google describes it well: think of your AI as an eager and talented student. It learns exactly what you teach it. If you feed it data that doesn't distinguish between a customer spending NOK 500 and one spending NOK 5,000, it's going to get very, very good at finding you… average customers. Great.

There's an old saying in IT: Garbage in, garbage out. It was coined in 1957. It has never been more relevant than it is today.

So what does this actually mean in practice?

Data literacy is the ability to understand, question and quality-check your data. It is no longer something you can hand off to the IT department or the one analyst sitting in the corner. It is a marketing skill. It is a leadership skill. And right now, with AI taking on a bigger role in how we reach and understand customers, it might just be the most important skill in the room.

Get the data right first. Then let the creatives do their thing. That order matters more than most people think.

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