Announcing Project Moneyball's Renewal Risk Score Calculator

Most Customer Success teams are expected to do something close to magic:

• Predict churn before it happens

• Prioritize the right accounts at the right time

• Catch silent risk signals early

• Prove value in a way that survives budgeting season

• Overcome internal politics that drive buying decisions in the wrong direction

And yet… many teams are doing it with a patchwork of spreadsheets, notes, inbox threads, and “I think this account is fine.”

Even teams with CS platforms often run into the same reality:

risk signals don’t always show up in one place, and tools don’t always agree.

So I built something simple, practical, and surprisingly powerful:

A Renewal Risk Score calculator you can run in G-Sheets or Excel (or mirror alongside your existing CS tools) to answer one question:

“Which accounts should we work first, and why?”

Who this is for

1) CSMs and AMs without a CS platform

If you’re operating without Gainsight / Totango / Planhat / ChurnZero / etc. (or you have them but they’re not fully implemented), you still need a reliable way to triage risk.

This calculator gives you a structured score using the tools you already have:

G-Sheets/Excel + the signals you can actually observe.

2) Teams that do have a CS platform - but want a “second opinion”

Even the best systems can miss nuance:

• stakeholder turnover

• silence despite “good health scores”

• adoption that looks fine but isn’t tied to outcomes

• support noise that isn’t actually renewal risk (or is)

Use this as a backup plan, a sanity check, or a validation mechanism alongside your existing tooling.

3) Leaders who want consistency

When CS teams scale, the biggest hidden risk is not churn. It’s inconsistency:

• One CSM flags risk early; another waits until renewal is 30 days away

• One AM is proactive; another is reactive

• Two accounts “feel the same”… but aren’t

A normalized model helps your team prioritize the same way - even when instincts differ.

Why I believe “renewal” starts long before renewal?

A renewal is the result of a long chain of tiny outcomes:

• Do they see progress toward their goals?

• Is usage growing in the right places?

• Are stakeholders expanding or shrinking?

• Is communication frequent… or suspiciously quiet?

• Are you proving value in a way that matters to the people who approve the spend?

Churn rarely happens at renewal. It happens months earlier, when the customer quietly starts questioning momentum - and nobody notices.

This calculator is designed to surface those early signals.

What the formula measures

The model combines seven categories into one risk score:

1. Days left to renewal Closer renewal = higher urgency and less room to recover momentum.

2. Customer goals met Outcomes, not effort. Are we helping the customer achieve their goals (not ours)?This input can be scored by the CSM/AM, or calculated as part of a structured business review process.

3. Product utilization / adoption Value is hard to defend without usage. Weak adoption usually means weak perceived ROI - especially at renewal.

4. Support health score Noise, friction, and unresolved pain. I recommend engineering a score based on your support motion, factoring in SLA adherence, ticket volume, severity, time-to-resolution, open vs. closed tickets, and escalation patterns. One nuance: “no tickets” is not automatically good news. Total silence can be a ticking-bomb effect. Ticket patterns often serve as a practical litmus test for customer engagement and product reality - when interpreted in context.

5. Communication score

   Are they engaging with you (calls, email, Slack), or going quiet? Silence is a measurable risk signal.

6. Stakeholder management score Are champions growing or disappearing? Are skeptics gaining influence? Stakeholder drift is one of the earliest predictors of renewal friction.

7. Feature requests / roadmap pull Healthy future intent. Meaningful requests often indicate the customer is investing in a shared future (as opposed to “nice-to-have” wish lists).

Each input is normalized and weighted to yield an Overall Risk Score between 0–100.

How to use it (in 3 minutes)

1. Fill in your account rows

2. Let the model compute the risk score (formulas can be provided if links are broken)

3. Prioritize your next steps accordingly

Let's explore three examples

Same three companies, three time horizons - used in all scenarios

• Acme Logistics

• Nimbus Health

• Orion FinTech

Legend: 0 = no risk, 100 = critical Green = Low risk Orange = Medium risk Red = Critical risk

What these three scenarios are really proving

This table shows the same three accounts (Acme, Globex, Initech) across three renewal horizons (A, B, C).

The point isn’t the math. The point is the pattern:

Renewal risk doesn’t come from one signal.

It comes from the constellation.

First: Renewal proximity creates pressure

Across each scenario, the “Renewal Risk” rises or falls mainly because of time:

• When renewal is close, even “good” accounts deserve attention.

• When renewal is far, you have runway - but early warning signs matter more than ever.

Think of it like this: Time-to-renewal tells you urgency. The other signals tell you reality.

Scenario A: Renewal is around the corner

This is the “pressure cooker” moment.

• Acme stays relatively safe because outcomes are being met and adoption is strong. Even if a few things aren’t perfect (like QBR attendance), the fundamentals are there.

• Globex becomes a “yellow account” - not collapsing, but too many areas are alerting: partial goals, middling usage, weak engagement. With renewal close, “average” becomes risky.

• Initech is the classic late discovery: low goals, weak adoption, noisy support, silence, shaky stakeholders. At this stage, it’s a firefight.

  
  

Lesson: When renewal is close, you don’t get credit for potential - only for momentum.

Scenario B: Same adoption, different support health

This scenario isolates a very common CS reality:

You can have similar adoption and similar goals, but one account becomes risky because support is burning.

• One account has heavy support pain → risk jumps.

• Another has clean support hygiene → risk drops.

• Everything else can look “fine” and the renewal can still be in danger.

Lesson: Adoption isn’t value if the customer is suffering while using it.

Scenario C: Renewal is far… but politics and silence start churn early

This is where teams get fooled.

All three companies can look reasonably “okay” on outcomes and usage - but:

• When communication drops

• When stakeholders shrink or turn skeptical

• When champions disappear…you’re watching churn form in slow motion.

Even with months left, these accounts deserve attention because the risk is not the date - it’s the trajectory.

Lesson: You don’t lose customers at renewal. You lose them when the customer stops believing the story internally.

The takeaway

Use the score to stop guessing.

• Time-to-renewal tells you how urgent it is.

• Goals + adoption + support + comms + stakeholders tell you what’s actually happening.

• The combination tells you who to work first - and why.

How the calculator is configured (so it fits your CS motion)

Under the three scenarios, you’ll notice the calculator behaves consistently: time-to-renewal increases urgency, while the other signals explain why an account is at risk. That behavior is controlled in the Config tab.

Weights

The calculator blends multiple inputs into one score using weights (higher weight = more influence). In the default configuration shown:

• Renewal timing = 0.3 (30% of the score)

• The remaining six categories are 0.1 each:

  • Goals met

  • Adoption

  • Support health

  • Communication / engagement

  • Stakeholder management

  • Feature requests / roadmap fit

  • EBR/QBR attendance

The Total weight = 1, which keeps the final score normalized.

How to think about weights (practical guidance):

• If your business is very renewal-date-driven (SMB / high volume / short cycles), increase Renewal timing.

• If your renewals are enterprise / multi-stakeholder / political, increase Stakeholder management and QBR/EBR.

• If you operate in a “product must be sticky” world, increase Adoption and Goals met.

• If operational friction is a known churn driver, increase Support health.

The Config tab is what makes this tool practical: it’s not a rigid scorecard. It’s a tunable risk model. Start with the default settings, run the three scenarios, and then adjust the weights to match your business reality.

That’s how you turn a generic “health score” into a scoring system your team actually trusts.

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Closing: use the score, but don’t outsource thinking

This model isn’t meant to replace judgment. It’s meant to standardize it, make it shareable, and trigger action earlier.

When your team aligns on a shared language of risk, you spend less time debating priorities - and more time changing outcomes.

That said, I want to acknowledge the obvious: there are excellent Customer Success platforms out there, many of them increasingly powered by AI. This calculator isn’t competing with them. It complements them.

Use it as a practical way to:

• recalibrate your existing health score,

• pressure-test what your tools are telling you,

• and create a reliable second opinion when the signals don’t match your instincts.

And if you’re operating without a native CS platform - whether you’re “bending Salesforce” into a CS cockpit or running on spreadsheets and best effort - this gives you a structured starting point. You can use it to build your risk-scoring environment over time, or simply run it as a standalone tool until your tooling catches up.

Either way, the goal is the same: less guesswork, earlier clarity, and better decisions. One last note: this calculator isn’t a one-off. It’s a working tool I’m including in my fourth book, scheduled to go live in early January 2026, alongside the broader system for thinking about renewals as a continuous motion - not a date on the calendar.

If you want the calculator, reply or DM me - I’ll send it over.