AI for Customer Retention: The First Department We Automated
AI for customer retention was the first thing we automated at a home-services company where I ran operations. We built a membership program, automated the follow-ups, and in 2023 ran AI lead scoring on our customer database. Clean, verified data came first.
Why retention was the first department we automated
It was an emergency-services business, B2C. B2C changes every day: the weather, the stock market, people's mood. People call when something breaks. There was no retention: customers came once and didn't come back.
We compared every channel and funnel against each other: paid, organic and retention. For retention that meant how customers stick, how they come back, and what it costs to bring them back. Every month we decided which channel to push.
Returning customers paid more than new ones.
The retention department was the first one we automated with AI.
The membership program and the follow-ups
The base was a membership program. A member has a reason to call you again, and you have a reason to stay in touch.
Then we automated the follow-ups: retention emails and SMS with offers, sent automatically to the right people. Nobody on the team had to remember to send them.
Retention grew.
That's how I approach automation in any department. Ask your team which processes repeat. If they're not written down, write them as SOPs. The SOP is the foundation for automation. A good SOP covers the order of steps, where the data comes from and where it's saved, the KPIs to track, and an owner for each step.
Then pick the most repetitive, most time-consuming process and automate it together with the person who owns the outcome. Everyone agrees on how it should be done. What took them hours now takes minutes, and they'll be grateful.
Keep that responsible person. Give them the tools to add their own agents, but by the SOP. If a tool is clunky or eats their time, change it.
If you're not sure which of your processes qualify, start with which processes AI can take over now.
AI lead scoring on the whole database
In 2023 we were one of the first to put AI on retention. We ran AI-powered analytics on our customer database.
AI lead scoring found the best-fit clusters. Those clusters became the most profitable.
AI is great where you need a deterministic answer: repetitive tasks, predictable models, given good data. What stays human is decision-making and judgment. Sometimes it's just a gut feeling.
Given good data. That's the condition.
The part nobody skips: clean data
The key was clean, verified data first.
Management can give you beautiful reports, show you beautiful numbers, even tell you everything is great, and your gut is telling you: no, it's not.
Clean up your data. Check your sources. It's the most painful, hardest thing, and the one that opens your eyes. The root cause is always how correct and trustworthy your data is.
Before you put AI on your customer list, go check how that data gets recorded:
- Is it trustworthy?
- Is it updated?
- Is it usable?
- Is every department tracking?
Sorry, but I make everyone report. Without documented proof of what you do at work, I don't know how to manage you. I always need to see where your data comes from, so I can trust it.
It doesn't sound easy-peasy. But that's where you always start. I wrote more on that in clean your data before you touch AI.
Then keep measuring. Retention is a number you watch every week next to the others, so you know whether it's holding. These are the weekly KPIs I'd put in front of an owner.
Where to start
Retention came first for us. Your first department might be a different one. The order stays the same: clean data, a written process, a person who owns the outcome, then AI.
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