Like any business function, the impact of your strategies is worthless without the proper means to measure your efforts, and customer success (CS) is no different. Metrics are what allow us to do this – but collecting and understanding them is only half the battle. The other half is communicating them effectively to the people around you.
And that’s often where things become difficult.
You might find yourself presenting a dashboard that seems clear to you but disengages half the room. Or reporting a number that feels important, only to get a follow-up DM asking for clarification.
Managing a team of customer success managers (CSMs) demands dual focus: on the one hand, you’ve got to ensure your team is concentrated on value realization several from your product/service, and on the other, you’re required to help them achieve their professional goals.
Management can present several challenges that may not have been apparent to you originally, but which require you to adapt quickly, not least when it comes to mixed levels of data literacy across your team, as well as others in your organization.
Leadership means equipping your CSMs to bridge that gap. In this article, we'll explore how to do that through simplification, storytelling, and a focus on business value.
1. Simplify your language
If your team’s experience levels are pretty varied, you may find their grasp of the more technical and financial elements of the role mirrors that breadth. To bridge the gap between technical and non-technical team members, it’s crucial to "speak the language of the business," rather than defaulting to siloed, function-specific metrics.
Julie Fox, currently Director of Digital and Scaled Customer Success at Hyland, learned this the hard way in a previous role, as revealed at Customer Success Summit Chicago 2024: "I got really wrapped up in the customer success metrics of my own little silo and world. And what happened was I would go to talk to other executives and they didn't care. They didn't understand it."
But the key isn’t to dumb things down – that’ll just come across as patronizing. The real differentiator here is finding the right translation. Instead of “our customer health score dropped three points quarter-on-quarter,” it becomes “more of our customers are at risk of leaving this quarter than last quarter – here’s why that matters and what we’re doing about it.”
What to do when you don’t fully understand the metric yourself
This is rarely discussed, but it’s oh-so common.
When starting at a new company in a previous role, Julie Fox realized she had moved from an annual recurring revenue (ARR) business to a monthly subscription model, which presented a challenge: the metrics she knew didn't carry over.
Rather than bluffing her way through, she went directly to her finance team:
"I actually asked them four times to say, ‘Hey, I don't understand this,’ [and] "my finance team [...] love talking about numbers. They commented on how few people ask." She then trickled that knowledge down to her CSMs using analogies and metaphors to make the concepts stick.
That behaviour is worth pausing on.
In teams with mixed data literacy, confidence often varies just as much as capability. Modelling curiosity – and being explicit about where metrics come from and how they’re calculated – builds trust. It’s well worth documenting metric definitions and aligning with teams like finance and product on a single source of truth, which can prevent confusion later down the road.
Grace Gupta
How to talk to the C-suite
The same principle applies when communicating upward. Rav Dhaliwal, Investor, Venture & Limited Partner at Crane Investments, puts it plainly: "Define what you do for the board, not for anyone else."
Framing metrics around revenue, speed, and efficiency – rather than CS-specific jargon – is what earns a seat at the table. For example:
- Instead of “product adoption,” talk about “how quickly customers reach first value and how deeply they use the product.”
- Instead of “NRR,” talk about “how much revenue grows from existing customers.”
For new hires or those unfamiliar with SaaS acronyms like NRR, TTV, or GRR, consider building a simple "crash course" into your onboarding to ensure everyone starts from the same baseline.
One practical approach is to create a one-page “CS metrics glossary” that explains each KPI in three lines: what it is, why it matters to the business, and what a CSM can do to influence it.
(FYI, we recorded a podcast episode with the brilliant Jess Galenski from Apryse, which goes into her 90-day framework for onboarding new CSMs and setting them up for long-term success. 👇)
2. Use storytelling to provide context
Data without context is just noise. Even the most compelling metrics can fall flat if they're presented as a wall of numbers with no narrative thread to pull people through them. When faced with a team member who doesn’t understand a particular metric they’re asked to report on, the solution is to reframe the metrics with storytelling.
"Stories reach people at a level no metric or status update ever could," says Gabriel Dizon, Director of Customer Success & Renewals at Litmos, during his talk at AI for Customer Success Summit 2025. "They stir emotion." For CSMs tasked with reporting wins and progress to stakeholders with varying levels of data literacy, that emotional hook is often what separates insight that gets acted on from insight that gets ignored.
To help standardize how those stories are told, Gabriel developed the “S.P.A.R.K. framework” – a five-step structure covering Situation, Problem, Approach, Resolution, and Key Outcomes.
The premise is straightforward: before leading with numbers, give your audience context. Where was the customer before? What pain were they experiencing? What did you do, and what did it produce? "It makes your CSMs' expertise crystal clear by highlighting the strategic approach and the final results – with no fluff," he says.
You can also use a similar pattern for internal metric reviews with your team:
- Situation: What’s happening in the business or segment?
- Problem: What do the metrics show is going wrong or changing?
- Action: What are we doing about it?
- Resolution: What changed as a result?
- Key Outcome: What impact did those actions have, and how will we know?
Visualization is another powerful lever.
For teams with mixed data literacy, start with very simple visuals: a trend line with one or two annotations, a traffic light view of account health, or a bar chart highlighting the top three churn reasons. Then allow more data-savvy team members to click into deeper tables or filters if they need the detail.
Finally, apply a simple gut-check to every metric you present: ask "so what?" If a data point doesn't solve a real challenge, tie back to a business outcome, or reveal something new, it probably doesn't need to be in the room. Push your team to complete the sentence: “This metric matters because…” and “As a result, we will…”
If they can’t, it’s probably noise.
3. Try to eliminate data overload and “noise”
More data doesn't always mean better decisions, and for team members with lower data literacy, an overwhelming volume of metrics can be just as unhelpful as having none at all. The challenge for CS leaders isn't collecting more; it's being ruthless about what actually matters.
Speaking on a panel at Customer Success Summit Amsterdam 2023, Rajat Jain, Senior Program Manager (Sales and Customer Success) at Philips, made the case for selectivity: "There's so much data available that we really need to be picky and choosy about what we use to inform our decision making."
Rajat’s approach is to start with the headline KPIs – retention rates, churn and ARR – before slicing deeper into customer-driven metrics like health scores that are more specific and actionable at the individual account level.
Rather than spreading attention across every available data point, identifying a handful of "beacon metrics" gives your team a clear and consistent lens through which to assess performance.
In practice, this could look like starting every team review with logo retention, NRR, and time to first value, for example, and then only dropping into secondary metrics when one of those beacons flashes red. Rajat echoes this, describing how his team boiled their customer survey program down to "one or two key questions with one beacon metric – something like NPS – and then we use that across the organization, rather than every team trying to collect multiple different data points."
A simple structure can help reinforce that focus. For example, a 30-minute metrics review might follow this pattern:
- 5 minutes: Review your beacon metrics
- 10 minutes: Deep dive into one area of concern
- 10 minutes: Share one customer example that brings the numbers to life
- 5 minutes: Agree on clear next steps and owners
Presentation matters too. Larry Raines, Head of Customer Success Management at JLL Technologies, used his session at Customer Success Summit New York 2023 to make the case for moving beyond spreadsheets altogether.
"We shifted to document-based requirements – detailed analysis, business-driven prioritization – and did we get a better outcome? We got way more of what the business wanted." For non-technical audiences, especially, a dense Excel sheet is rarely the most persuasive way to tell a story with data.
It’s also worth being aware of a few common pitfalls:
- Reporting metrics without tying them to decisions
- Leading with complexity rather than headlines
- Over-relying on lagging indicators like churn without discussing leading signals
- Changing metric definitions without clear alignment
Avoiding these can make a noticeable difference to how your data is received.
4. Align customer success metrics with values and outcomes
Metrics land differently when people can see a direct line between the numbers and the work they do every day. Abstract figures on a dashboard are easy to ignore, but data that reflects tangible impact is pretty hard to argue with.
Mark Kosoglow, Chief Revenue Officer at Docebo, frames this around a principle that's simple but easy to lose sight of: "In the SaaS world, there's only one rule when it comes to revenue – recurring revenue follows recurring impact. If you're not constantly creating value for your customer, they forget that you're creating value for them."
The implication for how CSMs report progress is significant. Rather than building toward one big moment of value that fades, Kosoglow advocates for smaller, more frequent demonstrations of impact – stair steps rather than a single plateau.
For your team, that means connecting each key metric to a customer outcome and a behaviour they can influence. For example:
- Time to first value: "How quickly did we get the first meaningful outcome for this customer?" This one lives in onboarding.
- Product usage depth: "How many teams and workflows rely on us day-to-day?" Focus here on adoption, training, and advocacy.
- Renewal and expansion: "Did we earn the right to keep and grow revenue?" This is where QBRs and ongoing value reviews do their work.
Tying metrics to ROI is one of the most effective ways to make that impact tangible.
Stijn Smet, Head of Customer Success at Whale, walked through exactly how he approached this at Customer Success Summit Amsterdam 2023. The starting point, he argued, is deceptively simple: "What is the problem that you're fixing for your customers? Start there."
From that foundation, Stijn benchmarked his product's performance against competitors and industry data, ultimately finding that a task that typically took over 30 minutes on tools like Google Drive or SharePoint took less than five minutes in his platform. Translating that 25-minute saving into an average US hourly rate – around $35 – and multiplying it across the volume of searches in the product gave him something concrete: "Actual tangible return on investment."
Underpinning all of this is the need for a shared framework – a common language that allows customer success, product, and sales teams to talk about value in the same way. Without it, even the most compelling metrics risk meaning different things to different people. A simple move is to agree, cross-functionally, on:
- A short list of value drivers (for example, “time saved,” “revenue generated,” “risk reduced”).
- Which CS metrics map to each driver.
- How you’ll evidence each one with customer stories and numbers.
Franca-Sofia Fehrenbach
5. Encourage collaboration and transparency
Even the most well-communicated metrics will struggle to gain traction if they're siloed within the CS team.
Making data visible across the organisation – through public Slack channels, all-hands meetings, or shared dashboards – ensures that wins are seen and understood by the people who need to see them. Linking metrics to specific customer outcomes, rather than reporting numbers in isolation, reinforces the story you've been telling all along.
Internally, regular cross-functional syncs around the book of business or sales forecasts help your CSMs understand where the numbers are coming from and how they're expected to trend. That broader context makes them sharper communicators when it comes to sharing data with their own stakeholders.
You can go a step further by treating data literacy as a shared skill to be built, not a fixed trait:
- Use recurring CS metric reviews to teach one small concept at a time anchored in live customer examples, e.g., “What does NRR actually include?” or “How do we read this cohort chart?”
- Encourage CSMs to ask “naive” questions about metrics without penalty and model that behaviour as a leader.
- Create simple, role-specific cheat sheets: what each metric means, what “good” looks like, and what levers each role has to move it.
Over time, this combination of translation, storytelling, focus, and shared learning turns metrics from something that only a few “numbers people” can use into a common language the whole team can speak.
Become a CSC Insider
Thank you for subscribing
Get exclusive insights, frameworks, and strategies from customer success leaders driving real business impact.
An email has been successfully sent to confirm your subscription.
Follow us on LinkedIn
