Is Your CS Org Chasing the Wrong Goal?

[Un]Churned Chapter 020

Most CS orgs say they’re outcome-focused. Our recent [Un]Churned podcast guests built teams that actually are.

Here’s what’s been on our minds this week 🧠

🎯 The [Un]Churned Take: Build Your CS Org Around the Real Finish Line

Pradeep Raman, VP of Customer Success at Microsoft, and Rob Edmondson, CCO at Ironclad, lead CS teams in very different markets and at different scales. Still, both have built teams focused on when customers truly get value, not just when contracts are signed. “The Surprising Way Microsoft Does Customer Success at Scale” and “Ironclad’s CCO Reveals How AI Actually Predicts Churn”, are evidence of a structural shift already underway in how CS orgs define and measure success.

Pradeep shared, “No customer celebrates a victory when they sign an agreement with anyone. It’s only when they deploy projects [that] they actually realize the value.” That’s the load-bearing logic behind Microsoft’s decision to fund free deployment support for every Azure customer. Azure generates revenue when workloads run, not when contracts are signed, so getting customers deployed faster is critical.

At Ironclad, Rob’s team is also concentrating on value delivery. A contract lifecycle management software, their key milestone is when a customer puts contracts live in production. This event is the basis for their time-to-value metric, journey-stage framework, and CSM KPIs. Every action, warning sign, and quarterly goal is tied to this moment.

The Close Is Not the Win

The milestones and processes your CS org focuses on reveal what you really consider the finish line for customers. Rob shared that Ironclad’s CSM team is now measured not by QBR completion or the number of customer conversations, but by whether they move their accounts from one journey stage to the next each quarter. “It’s funnel analysis almost in some sense,” he said. This approach, treating post-sales like a funnel with clear stage progress, is a real shift from how most CS teams are measured.

Most organizations haven’t made this shift because defining “realized value” clearly enough to measure it is hard work. Once you commit to a concrete milestone, you also have to face how many customers aren’t reaching it on time. Vague health scores protect everyone from that conversation, but specific milestones don’t.

Pradeep made the same point from a different angle. His team doesn’t track how often Azure customers log in or how many features they use. His team uses the metric “Commit to consume,” which asks the question, “Did the customer actually complete the deployment they committed to, on time and at full scope?” Either they deployed or they didn’t. In other words, either the CS team delivered or it didn’t.

The Difference Between AI Activity and AI Outcomes

Organizations that have defined the real finish line are seeing the most success with AI because they have a clearer picture of what they want to improve.

Pradeep’s team built an intake agent and a technical architect agent to help more customers reach deployment milestones. They started by defining the metric, then built the tools. Rob’s team created a churn prediction model that led to some surprising findings: upmarket customers weren’t renewing based on daily usage, but on usage patterns that matched their business cycles. They only found this because their data model was detailed enough to ask the right questions.

Both teams now tie every AI investment to a specific OKR. As Rob put it, if they’re going to build an agent, it needs to make a real impact.

Here are the Full Episodes

There's a lot in both conversations beyond what we covered here. Listen out for these insights:

183. The Surprising Way Microsoft Does Customer Success at Scale ft. Pradeep Raman (Microsoft)

1. Commit-to-consume in practice: how it’s tracked weekly by country and workload, and what it took to build agentic AI around it.

2. The N-1 staffing philosophy: why running deliberately lean became the forcing function for Microsoft’s AI buildout.

184. Ironclad’s CCO Reveals How AI Actually Predicts Churn ft. Rob Edmondson (Ironclad)

1. The journey stages framework: four adoption stages, with CSM targets tied to moving customers through them, not completing QBRs.

2. What the churn prediction model actually revealed: the assumptions Ironclad thought predicted renewal weren’t the ones that did.

Listen on YouTube, Spotify, and on Gainsight.com.
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☕ What Else We’re Reading

The Feature Factory Problem - LinkedIn Post by Ann Miura-Ko

Ami spent a month visiting AI-native companies across the US and Asia to study how they actually operate. If you’re wondering what the future of work looks like in practice, not in theory, this is a rare firsthand look.

📅 Save the Date

Pulse 2026 — Retention is being rewritten in real time. AI, scale, and digital are changing how customers stay. Pulse 2026 is the #1 conference where CS, education, community, and revenue leaders go to figure it out together. Join us May 27-28 in Las Vegas and use code UNCHURNED for a special rate.

Register at gainsightpulse.com →

The New Rules of CS — Gainsight’s ongoing webinar series is tackling the questions CS leaders are wrestling with right now. Four sessions are already on demand, and two more are coming up on the new rules for renewals and expansion.

Catch up on the full series here →

Wrapping Up

Evolving from “we’re outcome-focused” to “we measure outcomes” is no longer optional. The ones making that shift are the ones winning on revenue.

See you next Wednesday 🧠