Customer success (CS) teams have access to more data than ever: internal product data, usage metrics, sentiment, and a growing pile of external benchmarks.

The hard part is acting on it. With so much information coming in, it's difficult to know where to focus and which numbers move the needle for your customers.

I see this everywhere, regardless of industry or the type of SaaS product you support. Almost every CS team I've worked with or spoken to has the same issue: too much data and too little clarity on where to focus.

I've built and refined a framework for this over my career, first as a CSM, then managing CSM teams, and now leading operations and analytics at Mastercard Dynamic Yield. I've used it to build several health scores. It works whether you're an individual contributor managing a book of accounts or a CS leader helping your team prioritize.

It comes down to three steps:

  • Filter out the noise
  • Establish a data hierarchy
  • Translate what you're seeing into clear actions

A renewals scenario you'll recognize

You're on a call with a frustrated customer, and they're throwing everything at you at once:

  • "I don't see any ROI."
  • "We're only using one feature."
  • "Onboarding took way too long."
  • "We keep having technical issues."

It's an extreme scenario, but it happens. When it does, it's tempting to try to fix everything at once or to get defensive, especially when the person on the other end is more senior than you.

Take a deep breath, leave the emotion out, and look objectively at what's in front of you. Customers do this because it's human nature. Your job is to break the information down and decide what to tackle first.

Here's how I'd prioritize that list:

  1. Product reliability and usage. You can't generate value if the customer is dealing with technical issues or barely using the product, so these are your two areas of immediate focus.
  2. Value and ROI. This is one of the most important items on the list, and it depends on getting the first two right.
  3. Onboarding. It's already done, and you can't change the past. (If anyone has that superpower, I'd love to talk.) This one goes lower on the list.

I open with this example because the same logic applies to how you work with data every day. Filter out the noise, work out what matters most, and build a clear path to action.

Keep revenue retention as your main goal

Before anything else, be clear on the objective: renewing customers.

You can run the best QBR of your career and tell a compelling story about value and partnership. If the customer doesn't renew, none of it lands the way you needed it to. Revenue retention, whether you measure gross or net retention, is the outcome everything else works toward.

This matters because other people will push items onto your agenda that have nothing to do with renewal. Customers do it. Management does it too, and I say that as part of management. It's easy to get pulled into work that feels productive but doesn't bring you any closer to a renewal.

So keep coming back to one question: how does the data I'm looking at help me achieve this goal?

If you can't answer that clearly, it's probably noise.