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Hey friends, Happy Monday!
For years, growth was easiest to understand as a funnel. You acquire users, activate them, convert them, retain them, and eventually expand them.
It was a clean model, and for a long time, it worked. Each stage had an owner. Marketing brought people in. Product helped them reach value. Sales converted the right accounts. Customer success tried to keep them. Lifecycle teams filled the gaps with emails, nudges, and campaigns.
But the more I look at how AI is changing growth, the more I think the funnel is no longer enough. Not because it is wrong. Because it is incomplete.
Customers do not move through neat stages anymore. They search, compare, sign up, disappear, return, ask questions, hit friction, talk to support, try features, ignore emails, show churn signals, and sometimes expand before the company fully understands what changed.
Growth is becoming messier. But it is also becoming more learnable. That is where AI changes the model. The old growth stack helped companies run campaigns and measure what happened.
The new AI growth stack helps companies understand what is happening, predict what may happen next, decide what action to take, personalize the experience, and learn from the result.
The question is shifting from to ‘what campaign should we launch next? to ‘what does this customer need next, and how quickly can our system respond?’
That is a much bigger shift than it sounds. In today’s edition, we’ll explore:
Why growth is moving from a funnel to a feedback loop
How AI changes acquisition, activation, retention, and expansion
Why better decisioning matters more than more content
The five layers of the AI Growth Stack
How to build a full-lifecycle growth system that learns over time
— Naseema Perveen
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