Customer Churn

Usage data alone won’t predict churn

By
Joel Passen
February 19, 2025
5 min read

I've seen a slew of new AI companies doubling down on analyzing usage data as the silver bullet for predicting churn. It’s an attractive idea—track how often customers log in and how many features they use, and you’ll magically, often with some proprietary algorithm, you'll know who’s at risk and who’s primed for expansion.

That’s not how reality works.

Usage data alone is riddled with false positives, often creating a distorted view of account "health." A customer heavily engaging with your product isn’t necessarily satisfied—they might be struggling and frustrated. A drop in product usage doesn’t automatically signal churn risk—perhaps the customer has completed implementation and is now deriving value without needing to log in frequently.

🚨 High Usage ≠ HappinessCustomers with high usage might actually be frustrated and, therefore, a risk. Why are they opening support tickets and emailing their CSMs?Are they engaging because they love the product—or because they can’t figure something out? What are they saying? What’s the context?

⚠️ Low Usage ≠ Churn RiskThe modern technology landscape isn’t about engagement for engagement’s sake—it’s about delivering value with minimal friction. ✔️If your product makes life easier, customers shouldn’t need to use it constantly.

✔️Instead of measuring time spent, measure outcomes.

✔️Instead of chasing logins, track behaviors.This requires context—something raw usage data doesn't provide.

📉 Usage ≠ RenewalsIn SaaS, high usage doesn’t guarantee a renewal.Renewals are driven by:

✔️ Perceived value (or lack thereof)

✔️ ROI & business impact

✔️ Alignment with evolving needs

To truly predict and drive retention, track the right contextual signals like:

✔️ Contract issues

✔️ Bi-directional responsiveness and closed-loop resolutions

✔️ Budget and procurement discussions

✔️ Expansion/contraction language

✔️Change order requests

Look for specific context beyond sentiment.

🔍 No Context, Limited InsightsUsage data doesn’t explain why something is happening. Why did usage drop?

⁉️ Did the customer stop needing what you sold them, or are they trialing a competitor?

⁉️ Have users given up on your solution and found a workaround?

⁉️ Is usage dropping in specific customer segments (e.g., corporate accounts)?

You won’t find these answers in product telemetry alone.

Companies that get this wrong focus heavily on usage metrics and then wonder why their churn predictions fail.

The ones that get it right combine usage data with contextual signals—the insights that explain the "why."

Real-world signals tell you how customers feel and what they need, not just which buttons they click and how often.

If your account management strategy is built purely on tracking usage and opinions, you’re looking at a puzzle with half the pieces missing.

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Customer Churn

The Most Dangerous Threat to CROs

Joel Passen
July 1, 2025
5 min read

The most dangerous threat to CROs doesn’t live in the opportunity pipeline.

It's churn.

  • It doesn’t scream like a missed quarterly pipeline goal.
  • It doesn’t show up in dashboards until it’s too late.
  • It's rarely caught by a generic 'health score'.
  • It's the board meeting killer.

Retaining and growing our customers is the only repeatable, compounding, capital-efficient growth lever left in B2B businesses.

📉 CAC is way up.

📉 Channels are saturated.

📉 Talent is expensive.

📉 Competition is fierce.

📉 Switching costs are low.

The path to $100M used to be “sell, sell, sell.”

Today? It’s “land, retain, expand.”

No matter how strong your sales motions are or how slick your product or service looks during the sales process, if your customers are churning, you’re stuck in a leaky bucket loop of doom.

Every net-new dollar you win is offset by dollars you lose. It's just math.

Yet most GTM orgs still operate like retention is someone else’s problem. "That's a CS thing."

  • The CS team might “own” the customer post-sale.
  • Account Management may own the renewal and growth number.
  • Support is in the foxhole on the front line.
  • RevOps might model churn with last quarter’s data.
  • Marketing might send an occasional newsletter via email.
  • Finance may be leaning in on the forecasting.
  • Product is building things that supposedly the customers want.

But in reality, churn is the CRO's problem. We wear it - or should.

If your go-to-market motion isn’t designed to protect and grow customers from Day 1, you’re not just leaving money on the table — you’re setting fire to it.

Retention and expansion aren’t back-end functions. They’re front-and-center revenue motions.

The most valuable work these days starts after the contract is signed — not before.

We need to stop treating post-live as a department and start treating it as the engine of durable growth.

Software

Have you heard this from your CEO?

Joel Passen
April 29, 2025
5 min read

"How are we using AI internally?"

The drumbeat is real. Boards are leaning in. Investors are leaning in. Yet, too many leaders hardly use it. Most CS teams? Still making excuses.

🤦🏼 "We’re not ready."Translation: We don't know where to start, so I'm waiting to run into someone who has done something with it.

🤦🏼 "We need cleaner data."Translation: We’re still hoping bad inputs from fractured processes will magically produce good outputs. Everyone's data is a sh*tshow. Trust me. 🤹🏼♂️ "We're playing with it."Translation: We have that one person messing with ChatGPT - experimenting.

😕 "Just don't have the resources right now."Translation: We're too overwhelmed manually building reports, wrangling renewals, and answering tickets forwarded by the support teams.

🫃🏼 "We've got too many tools."Translation: We’re overwhelmed by the tools we bought that created a bunch of silos and forced us into constant app-switching.

🤓 "Our IT team won't let us use AI."Translation: We’ve outsourced innovation to a risk-averse inbox.

It's time to put some cowboy under that hat 🤠 . No one’s asking you to rebuild the data warehouse or perform some sacred data ritual. You don’t need a PhD in AI.

You can start small.

Nearly every AI vendor has a way for you to try their wares without hiring a team of talking heads to perform unworldly 🧙🏼 acts of digital transformation.

Where to start.

✔️ Pick a use case that will give you a revenue boost or reveal something you didn't know about your customers.

✔️ Choose something that directs valuable work to the valuable people you've hired.

✔️ Pick something with outcomes that other teams can use.

Pro Tip: Your CEO doesn't care about chatbots, knowledgebase articles, or things that write emails to customers.

What do you have to lose? More customers? Your seat at the table?

CX Strategy

Talent gets you started. Infrastructure gets you scale.

Joel Passen
April 29, 2025
5 min read

We obsess over hiring A-players. But even the best GTM talent will flounder if the foundation isn’t there.

I’ve seen companies overpay for “rockstars” who quit in 6 months—not because they weren’t capable, but because they were dropped into chaos. No ICP. Bad data. No process. No enablement. No system to measure or coach.

Great GTM teams aren’t built on purple squirrels. They’re built on a strong foundation.

That foundation looks like this:

✅ A crisp, written ICP and buyer persona (not just tribal knowledge)

✅ Accurate prospect data to target the right ICP

✅ A playbook that outlines how you win—and how you lose

✅ A clear point-of-view that your team can rally around in every email, call, and deck

✅ Defined stages, handoffs, and accountability across marketing, sales, CS

✅ A baseline reporting system to see what’s working—and what’s not

When this exists, you can onboard faster, coach better, and scale smarter. It's not easy, and it’s not sexy, but it works.

Want to cut CAC and increase ramp speed? Start with your infrastructure. Hire into a structure.

How many customers will you have to lose before you try Sturdy?

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