Why Doing More Made Things Worse
The instinct in most organizations when faced with declining signal quality is to respond with more: more personalization, more automation, more output, more speed. It is also, based on everything the data shows, making things worse.
• 40% percent of marketers report being buried in more work despite increased AI adoption.
• 18% percent use AI in any deep operational sense, with most using it to scale execution, not to improve the decisions underneath it.
Personalization was supposed to be the answer to all of this. If you could speak to each customer with the right message, via the right channel, at the right moment, the relevance problem would be solved. Beautiful premise, but the reality is that 64% percent of marketers now admit their personalization efforts are more about appearance than actual impact. Only two in five can articulate a coherent reason for why a specific message was sent to a specific person at a specific time.
Personalization has scaled (it has not gotten smarter), and teams are producing individualized outputs without a clear decision framework behind them. Messages go out, and they look right. But the reasoning doesn't hold up under scrutiny, which means there's no mechanism for improvement. Go ahead and try to optimize a decision you can't explain. Add to that the speed problem, compounding everything.
• 60% percent of marketing teams take two to four weeks to act on what they learn from a campaign.
• 70% avoid making changes to live programs because the downstream effects feel unpredictable.
So the system is increasingly difficult to change, and the customers it's trying to reach are increasingly fast to adapt. Those two curves moving in opposite directions is a problem of structure and not performance. This suggests we in marketing solved the wrong problem. The question most teams were asking was likely: how do we send more, to more people, faster? That's a production question with production answers, including better tooling, more automation, larger teams, and more campaigns. And to their credit, most marketing organizations answered it well.
•Output went up.
•Reach expanded.
•Velocity increased.
But the correct problem to solve was decision quality:
• How do you know what to send?
• How do you know when?
• How do you know whether the signal you're reading reflects genuine intent or learned behavior designed to extract a specific response?
Those questions get harder when you scale because the volume of decisions increases faster than the capacity to make them well, resulting in a system that is very active and not very wise. It fires constantly, adjusts slowly, and reinforces the patterns that consumers have already learned to exploit. 60% percent of consumers have left a brand over irrelevant content, which is a cost of a system optimized for output in an environment that now requires judgment.
More isn't better. Better is.