How to detect non-obvious Churn Risks

Hi, Markus here. Welcome to a premium edition of the Customer-Value-Led-Growth Newsletter.

Every week, I share strategies, guides, and frameworks to help you create exceptional value for your customers and company.

If you are not a paid subscriber, here’s what you might have missed:

• 5 highly effective Tools every CS Team needs to use

• The not-so-Secret to high Product Adoption

• How to build a Customer Success Metric System that rocks

• Customer Onboarding that drives Growth

• How to build a dedicated Customer Success Plan

Preventing churn depends on your ability to apply proper countermeasures.

But they might be futile if the risk is not detected early enough.

There’s maybe a 1% chance to save an account within 30 days after 11 months of customers failing to receive value from your product.

If your customers are on monthly plans or paying per usage you’ve got even less time.

95% of SaaS companies don’t have effective risk detection processes in place.

It’s not difficult to spot potential churn risks when customers

• give you low NPS or CSAT

• barely use your product

• stopped using your product

• are non-responsive

• have deep red health scores

But here’s the problem: That’s not everything where churn comes from.

• Customers that appear as Net Promoters churn

• Customers using your product night and day churn

• Customers with all green health scores churn

You can’t miss them telling your C-suite that you could not stop churn because your standard metrics didn’t give you a warning is not an option.

In today’s episode, I’ll show you an effective way to detect non-obvious risks.

Why your customers are here

If you are following my content you’ve likely heard me say it a 1000 times. Your customers are not purchasing your product for its features and functions.

They buy it because they want to

• increase revenue

• reduce costs

• improve productivity

• …

If this is the reason why they are here, then also the reason why they will leave becomes quite simple:

They leave because they did not get what they came for.

Zooming in, there are only 4 potential scenarios:

1. Customers have overachieved their desired outcomes (no risk)

2. Customers have achieved their desired outcomes (low risk)

3. Customers have not achieved their desired outcomes (at risk)

4. Customers where you don’t know whether they have achieved their desired outcomes (at risk)

Operationalizing Risks

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