Steal This Idea: Customer Offboarding as a Service

Most companies spend a lot of time thinking about onboarding.

How do we get customers activated faster?

How do we get them to the “aha” moment?

How do we increase retention?

How do we make the first 30 days better?

But when a customer leaves, the process is often:

Sorry to see you go. Why are you cancelling?

Then a dropdown with six options nobody trusts.

That’s potentially a huge missed opportunity.

Because churn isn’t just a metric.

It’s people deciding that whatever you’re selling is no longer worth paying for.

And understanding why is incredibly valuable.

So here’s the idea:

Become extremely good at understanding why a company’s customers leave.

Not necessarily as software.

At least not initially.

The idea

A company gives you access to its recently churned customers.

You contact them.

You interview them.

You figure out what actually happened.

Then you turn those conversations into something the company can act on.

For example:

31% of customers who churned this quarter didn’t leave because of price. They signed up expecting feature X to work in a way it doesn’t.

Or:

Customers aren’t cancelling because onboarding is difficult. They’re cancelling three months later because only one person inside the company uses the product and they can’t justify renewing it internally.

Or:

Your cancellation survey says “too expensive,” but when we interviewed those customers, the real problem was that they weren’t seeing enough value to defend the cost.

That distinction could be worth a lot of money.

The product isn’t:

We conduct exit interviews.

The thing being sold is:

We figure out why you’re losing customers and tell you what to fix.

Why cancellation surveys aren’t enough

Most churn analysis is surprisingly shallow.

Someone cancels.

You ask:

Why are you leaving?

They select:

• Too expensive
• Missing features
• No longer needed
• Switched to competitor
• Other

Now you have a lovely dashboard saying 37% of churn is caused by price.

But what does that actually mean?

“Too expensive” can mean:

Your product is genuinely outside my budget.

It can also mean:

I don’t use this enough.

My boss doesn’t understand why we’re paying for it.

Your competitor charges the same amount but solves another problem too.

I never managed to get the product working properly.

The employee who championed this internally left.

We expected something different when we signed up.

Those are completely different problems.

And they require completely different solutions.

A good interviewer can keep asking why until the actual reason appears.

Why I think there could be a business here

Churn is expensive.

If you run a business doing €100,000 a month in recurring revenue and lose 3% of your customers every month, even a small improvement in retention can compound into a lot of money.

Companies already spend heavily trying to acquire customers.

They buy ads.

Hire salespeople.

Pay affiliates.

Write content.

Run webinars.

Attend conferences.

And then some percentage of those customers quietly disappear.

If someone can reliably tell you why they’re disappearing, that should have value.

The interesting question is whether companies already know the answer.

Some probably do.

Others almost certainly think they do.

That’s the assumption I’d test first.

I would not build churn-analysis software

This is exactly the kind of idea where it would be easy to get distracted by software.

Connect Stripe.

Connect HubSpot.

Connect Intercom.

Analyze cancellation reasons with AI.

Create a churn dashboard.

Generate beautiful charts.

Congratulations.

You now have another analytics product.

But the hard part might not be analyzing the data.

The hard part might be talking to people.

A customer’s real reason for leaving might not exist anywhere in the company’s data.

You might only discover it by asking:

What did you originally hope this product would do for you?

Then:

When did you first realize it wasn’t doing that?

Then:

Why didn’t you cancel at that point?

Then:

What finally made you cancel?

That conversation is much harder to automate well.

Which is why I’d start there.

The first product could simply be a service

Something like:

We’ll interview 20 customers who recently cancelled and tell you why you’re losing them.

That’s it.

You might charge €2,000.

Or €5,000.

Or €10,000.

I don’t know.

The price should depend on who you’re selling to and how valuable reducing churn is to them.

A company doing €10,000/month probably isn’t the customer.

A company doing several million a year in recurring revenue might happily spend €10,000 if the work identifies a retention problem worth €200,000.

How I’d test it

I would begin with companies that:

• have recurring revenue;
• have enough customers to generate regular churn;
• have relatively high customer values;
• don’t already have a sophisticated customer research team.

Probably B2B SaaS first.

Then I’d speak to founders, heads of customer success and product leaders.

But I wouldn’t ask:

Would you pay someone to analyze your churn?

I’d ask about the last customers who left.

• Who were they?
• Why did they leave?
• How do you know?
• Did anyone speak to them?
• What did they say?
• Does someone review churn every month?
• What happens with that information?
• Have you ever discovered that customers were leaving for a reason you hadn’t expected?
• What’s your current churn worth in revenue?

The interesting question is:

How confident are you that you actually understand why customers leave?

If the answer is:

We have a cancellation dropdown in Stripe.

That’s interesting.

Then I’d offer to do the work

No software.

No dashboard.

No AI churn prediction.

Just:

Give me the customers who cancelled over the last 90 days. I’ll try to speak to 20 of them and come back with the patterns I find.

The first few projects would mostly be about learning the craft.

How do you actually convince churned customers to talk?

Do you pay them?

Does the company contact them first?

How many agree?

What questions produce useful answers?

How do you distinguish one angry customer from a genuine recurring problem?

At what point do patterns become strong enough to act on?

Those are much more important questions than which database to use.

The hard part: getting former customers to talk

This may be where the entire idea falls apart.

People who cancelled something may have very little interest in giving that company another 30 minutes of their life.

Especially if they left because they were unhappy.

You may need incentives.

For example:

We’ll give you a €50 Amazon voucher for a 20-minute conversation.

That immediately changes the economics.

Twenty interviews now cost €1,000 in incentives before you’ve done any work.

Maybe that’s fine for a company with high-value customers.

Maybe it’s completely uneconomical for a €29/month SaaS.

This is exactly why I’d test the business manually.

The market will tell you which customers can support the process.

You might need to specialize

“Churn consulting” is probably too vague.

You could specialize around a type of company where customers are particularly valuable.

For example:

B2B SaaS with €5k–€50k annual contracts

Losing five customers might mean hundreds of thousands in ARR.

Or:

Agencies

Why do clients leave after 12 months?

Or:

Membership businesses

Why do people stop renewing?

Or:

Vertical SaaS

What makes dental practices, gyms, restaurants or contractors switch providers?

The narrower the customer, the easier it might become to recognize patterns.

And once you’ve interviewed hundreds of churned customers in the same industry, something interesting happens.

You start becoming an expert.

The moat might be expertise, not software

Imagine you’ve interviewed 1,000 churned customers from B2B SaaS companies.

You’ve probably seen the same patterns repeatedly.

You may know that:

• “Too expensive” usually means something else.
• Certain onboarding failures predict churn three months later.
• Champion turnover is a major hidden driver of B2B cancellations.
• Certain complaints sound important but rarely cause actual churn.
• Certain warning signs appear long before cancellation.

Now you’re not merely conducting interviews.

You’re bringing a benchmark.

You can tell a customer:

This issue appears in 42% of the churn interviews we’ve conducted with companies at your stage.

That’s much more valuable.

And potentially much harder to reproduce.

The data accumulated from doing the service could eventually become the product.

Could AI help?

Eventually, yes.

Suppose every interview is recorded and transcribed.

Now you can automatically:

• tag churn reasons;
• cluster recurring complaints;
• identify competitors mentioned;
• extract feature requests;
• detect changes over time;
• compare customer segments;
• connect reasons with account data;
• generate monthly churn reports.

But I would be careful.

If you start with:

AI-powered churn intelligence platform

you’re competing with a giant pile of software.

If you start with:

We will personally talk to the customers you’re losing and explain why they’re leaving

the offer is much easier to understand.

AI can make the operation more efficient later.

It doesn’t need to be the product.

Distribution

This feels like a founder-led sales business initially.

I’d target companies where you can see evidence of meaningful recurring revenue.

Reach out directly to:

• founders;
• CEOs;
• heads of customer success;
• heads of product;
• growth leaders.

And I’d make the outreach extremely specific.

Not:

We help SaaS companies optimize churn with actionable customer insights.

Nobody cares.

Something closer to:

When someone cancels, how do you currently figure out why they actually left?

Or:

I noticed you have around 100 employees. Do you have someone systematically interviewing churned customers, or are you mostly relying on cancellation surveys?

The conversation itself qualifies the customer.

Content could work very well too

Every engagement produces anonymized lessons.

That could become extremely good content.

For example:

We interviewed 50 customers who cancelled SaaS products. Here’s why “too expensive” usually wasn’t the real reason.

Or:

The 7 reasons customers churn that never appear in cancellation surveys.

Or:

Why customers keep paying for three months after they’ve already decided your product isn’t useful.

If the insights are genuinely good, founders will read them because the subject is directly connected to revenue.

That can become inbound distribution.

There may also be a partner channel

Who already works with SaaS companies and cares about retention?

• SaaS consultants
• growth agencies
• customer-success consultants
• fractional CPOs
• VCs
• private-equity operating teams

Imagine a private-equity firm buys a SaaS company.

One of the first things it wants to understand is:

Why do customers leave?

You could conduct churn research across every company in the portfolio.

That’s a much more valuable customer than finding individual €99/month SaaS founders.

The biggest concern I have with this idea

It might simply be consulting.

And complicated consulting at that.

Every customer could have different data.

Different customers.

Different sales processes.

Different reasons for leaving.

Different incentives.

Different expectations.

You might discover that producing genuinely useful answers requires a very experienced researcher spending a lot of time on every account.

That limits scalability.

But I wouldn’t reject the idea because of that.

A difficult-to-automate service can still be a very good business.

And sometimes the complicated manual work is exactly where you discover the software opportunity.

Maybe after 30 projects you realize that 70% of the process is the same every time.

Great.

Automate that 70%.

Or maybe it stays a consultancy charging €20,000 per research project.

Also fine.

The goal isn’t to force every idea into SaaS.

It’s to find something people value enough to pay for.

The market test I’d run

If I wanted to test this next week, I’d do this:

1. Find 50 B2B SaaS companies with enough revenue that churn matters.
2. Contact founders or customer-success leaders.
3. Ask how they currently understand why customers leave.
4. Have five to ten conversations.
5. Look specifically for companies relying mostly on surveys and assumptions.
6. Offer one company a fixed-price churn research project.
7. Interview 10–20 of their recently churned customers.
8. Produce a concise report with the recurring reasons, quotes, patterns and recommendations.
9. Ask what the report was worth to them.
10. See if they want you to do it again next quarter.

The critical signal isn’t:

This was really interesting.

It’s:

Can you do another 20?

Even better:

Can you do this every month?

Now you might have a business.

What I’d want to prove before going further

I would need evidence for four things:

1. Companies don’t already understand their churn well enough.

If they already know exactly why customers leave, there’s no problem.

2. Churned customers will actually talk.

If nobody responds, the methodology breaks.

3. Interviews uncover information that changes decisions.

Interesting anecdotes aren’t enough.

The company should change onboarding, pricing, product, positioning or customer-success processes because of what you discover.

4. Someone will repeatedly pay for the work.

A one-off research project can be useful.

A recurring service is much more interesting.

The bigger version

If all of that works, I can imagine this evolving into something like:

An outsourced churn intelligence team.

Every month:

1. New churned customers automatically enter the system.
2. They receive an invitation to speak.
3. Researchers conduct interviews.
4. Calls are transcribed and analyzed.
5. Patterns are combined with account data.
6. Product and customer-success teams receive a monthly churn intelligence report.
7. Major changes trigger alerts.

Instead of asking:

Why did churn increase last month?

the company already knows.

Eventually the software might support the researchers.

Eventually AI might conduct some of the interviews.

Eventually you might build benchmarking across companies.

But all of that comes later.

Start with a phone call.

Why I like this idea

The best thing about it is that the customer’s problem is extremely close to money.

You’re not promising vague productivity improvements.

You’re asking:

Why are people who used to give you money deciding to stop?

If you can answer that question better than the company can answer it themselves, there’s probably something worth paying for.

The thing I’m less certain about is whether it can become a simple, scalable product.

It may be operationally messy.

It may require genuinely good researchers.

It may only make economic sense for companies with relatively high-value customers.

But those aren’t reasons to spend three months debating it.

Find a SaaS company.

Ask how they understand churn.

Offer to interview ten former customers.

See what you learn.

Then let reality decide.