The CS team was drowning in demands. “Get more customers to upsell, contract timing doesn’t matter!” “Retention rates need to improve!” “Implementations have to move faster!” “NDR is terrible. Fix it!”
Not only were they fielding customer complaints, but suddenly the company itself was turning on them. It wasn’t a great scene, and as a finance leader, I hadn’t done enough. I looked at the metrics and agreed. Rookie mistake, despite my implementation of rolling forecasts and management reviews.
Keeping customers happily paying for your product and wanting more is the lifeblood of your business. But it doesn’t rest solely on CS. It depends on solving the puzzle of: Selling to the right customers, delivering a good product that meets expectations, and providing strong support and engagement post-sale. These customers will be the engine for your growth, both through upsells and referrals.
To fix retention, you have to analyze the entire chain, not just CS performance.
In the last article, we covered GTM analysis. The next most important step is to evaluate customers through the CS team’s lens. This is especially important because CS isn’t always on the exec team. It typically falls under the CRO, whose focus is net-new revenue, meaning retention doesn’t get the attention it deserves. Finance can step in as a strategic partner, providing the metrics and insights CS needs to prove their impact or back up their problems.
And yes, this work is critical.
Client Segmentation | ARR | % | |||
Paying | Not paying | Total | Paying | Not paying | |
High Usage | 500,000 | 112,132 | 612,132 | 6% | 1% |
Medium Usage | 1,523,024 | 609,210 | 2,132,234 | 17% | 7% |
Low Usage | 3,829,233 | 1,148,770 | 4,978,003 | 43% | 13% |
Onboarding < 30 days | 283,223 | 198,256 | 481,479 | 3% | 2% |
Onboarding > 90 days | 424,835 | 297,384 | 722,219 | 5% | 3% |
Total | $6,560,315 | $2,365,752 | $8,926,066 | 73% | 27% |
% | 73% | 27% |
Cue ‘stat.’ McKinsey reports that existing customers drive one-third to one-half of total revenue growth, even at startups. Expansion revenue comes at a fraction of the cost of new sales. High retention fuels predictable ARR, strengthens cash flow, and boosts company valuations. So yes, the work you do across the customer journey will pay off significantly.
The Bullets
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Let’s get to work:
1. Establish your baseline metrics
As covered in the previous guides, establish a baseline as the first step. These are the metrics you’ll track to measure improvement. A deep dive into all of them compared to best practice will help you understand where the real issues are.
Net Dollar Retention (NDR). 100–120% is generally good; 120%+ is excellent.
Churn (logo and revenue). For enterprise-focused companies, under 5% annual churn is strong; for mid-market/SMBs, under 10% annually is acceptable.
Implementation backlog. Customer implementation should start within a week.
Implementation time. One to two months is a reasonable timeframe for customers to start seeing value while excitement is still high.
Customer health/usage. Less than 20% of customers should be in the lowest usage bucket, while at least 20% should be in high usage and prime for upsell.
Time to Value (TTV). Customers should reach their first meaningful value milestone within 30–60 days to capitalize on their initial excitement.
Time to Grow (TTG). By six months, customers should be comfortable enough to consider a larger commitment for the next year.
There’s no need to criticize where things stand. The goal isn’t to assign blame; it’s to understand the current state of your customer base so you can monitor improvements across the organization going forward.
Tip: Try to visualize the journey of a good, bad, and typical customer. What are the most critical stages and how smooth are it for customers to flow through them? (Hint: implementation is often the biggest factor.)
2. Zoom-Out: Understand the customer journey flow
We’ve covered this before, and ideally, your operational model already includes a strong report on customer retention and expansion. But when it comes to expansion, it’s worth diving into the numbers. Think of it as the ‘master’ sales funnel, and focus on onboarding+ in the CS review. As always make sure to include the relevant team, such as product, CS, or design-research:
Identify each stage in the journey. The typical journey includes awareness, interest, consideration, decision, onboarding, adoption, expansion, and renewal (or churn). Mapping these clearly helps define the flow of customer engagement.
List out drop-off points. Build a flowchart showing how customers move from one stage to the next. Where are they falling off? Are they churning before onboarding? Are they adopting but never expanding?
Estimate the financial impact. Not all drop-offs are equally damaging. Which ones are hitting revenue the hardest? Keep asking why to pinpoint the root causes.
Identify the owner. Oftentimes you have different owners of the customer journey (from sales to CS, to product teams). Make sure the owner has the resources they need to highlight and solve the challenges found.
Yes, this requires more visualizations and quantitative analysis, but having a clear mental model of the customer journey allows teams to prioritize the biggest chokepoints instead of spreading efforts too thin.
Last 3 Months | Awareness | Consideration | Evaluation | Purchase | Onboarding | Adoption | Renewal |
Actuals | 9,645 | 363 | 20% | 25 | 18 | 20% | 11% |
148,174 | 4% | 10% | 15,334 | 90% | 40% | 103% | |
85 | 7 | 36% | 109 | 86 | 40% | 10% | |
Definition | Website visits | MQLS | Demos booked | Win rate | Time to onboard | High | Churn rate |
Ad impressions | Email click rates | Free trials | Deal size | Completion rate | Medium | NRR | |
Cost per lead | Content downloads | SQL rate | Sales cycle | First-week usage | Low | Upsell | |
Range | ~10,000/month | ~300/month | ~30% of MQLs | ~20–30% | ~14–30 days | 20% | 5-10% |
~100,000/month | ~3–5% | ~15–20% of MQLs | TBD | ~80–90% | 70% | 110–125% | |
$100–$300 | ~5–10% of website | ~20–40% of MQLs | 30–90 days | ~70–85% active users | 80% | 20-30% |
Tip: When reviewing these numbers with CS, include Product and Sales. Retention and expansion are company-wide efforts, not just the responsibility of CS.
3. Implementation efficiency
Okay, now it’s time to dig into the trenches. Start with implementation. Not just whether it’s been completed, but whether it’s been done well. And yes, this is *before* you start implementing an overall health score because: these are the easiest to fix and they provide the quickest feedback on the recent sales you have made. To do so:
Implementation stages. Breaking the onboarding journey into well-defined phases each team agrees on.
Implementation success metrics. Track objective, quantifiable metrics to ensure that an “implemented” customer is actually achieving meaningful outcomes. Not a judgement call.
Time to Value. Identify the first action or milestone (e.g., first campaign launched, first project completed) that signals the customer is deriving real benefits.
Time to Growth. Measure how quickly existing customers expand their usage via upsells, cross-sells, new feature adoption, additional seats, etc. Compressing this timeline can drive higher Net Dollar Retention (NDR).
Key feature usage. Assess how effectively customers are adopting and utilizing core features. Early and deep engagement with key features often correlates with long-term retention and expansion.
Look for trends and patterns. Again, the goal of this is to know the overall status of the implementation backlog. Oftentimes, it's as simple as listing the companies that haven’t reached their time to value and understanding what the next step is to get these companies going.
Logo | Start Date | Implement? | Value? | Days Since | Next Step |
TechCorp | 9/23/24 | Yes | No | 188 | Schedule demo for unmet goals |
DataDrive | 6/24/24 | Yes | No | 279 | Discuss barriers to value realization |
CloudBase | 7/30/24 | Yes | No | 243 | Identify upsell opportunities |
SaaSWorks | 5/27/24 | Yes | No | 307 | Plan expansion strategy |
FinEdge | 6/3/24 | No | No | 300 | Introduce solution and identify pain points |
MarketView | 1/20/25 | Yes | No | 69 | Evaluate adoption challenges |
SwiftDash | 12/19/24 | Yes | No | 101 | Clarify next steps for implementation |
OmniCloud | 4/18/24 | Yes | No | 346 | Review ROI and customer feedback |
WaveSuite | 1/12/25 | Yes | No | 77 | Discuss potential feature enhancements |
InnoSoft | 2/17/25 | No | No | 41 | Assess fit and define objectives |
GrowthGen | 9/28/24 | Yes | No | 183 | Address pending issues affecting usage |
BioSys | 5/13/24 | No | No | 321 | Initial discovery and needs analysis |
PixelPro | 9/22/24 | No | No | 189 | Establish key stakeholders and priorities |
SparkLink | 9/17/24 | Yes | No | 194 | Analyze usage metrics for expansion |
NetCore | 11/21/24 | No | No | 129 | Determine business case and expectations |
Tip: Define a metric that objectively determines when a customer is fully implemented, outside of your internal implementation pipeline. This ensures success is measured by outcomes, not process milestones.
4. Churn and expansion analysis
Churn is one of the most damaging forces in a SaaS company. You’ve already invested significant resources in acquiring each customer, and in many cases, profitability doesn’t materialize until at least one renewal. To build a strong churn prevention strategy, analyze the following:
Typical churn analysis: Break down churned customers into categories using a pie chart or another segmentation method. Identify the primary reasons customers leave.
Dead-weight customers: What percentage of your customers are technically active but not meaningfully engaged?
Acquisition channels & patterns: Where did these customers come from? Are there specific acquisition channels that result in higher churn?
ICP vs. non-ICP: Many companies lose sight of ICP alignment post-sale. But it’s crucial to track whether churned customers that fit your ICP actually use the product better than non-ICP clients as a test of your assumption.
Cohort analysis: Analyze churn and expansion across different time-based cohorts (e.g., by signup date), geographic regions, and pricing tiers. Cut and slice to find insights.
This analysis will show you both what is realistic going forward and where major control issues could be hiding finance risk. This will also inform your health score modeling in the next section.
Hint: To get a full picture, you need both product usage data and Customer Success (CS) feedback. One without the other creates unexpected blind spots.
5. Customer Health Score Modeling
Now that you have a solid understanding of what makes a good or bad customer, it’s time to put that knowledge into action. One of the best ways to do this is by implementing a Customer Health Score to prioritize customer engagement. Since not everything is purely data-driven, the score should also allow for qualitative input. To build:
Segment customers into three buckets: These buckets should be based on whether they will churn, upsell, or simply renew rather than trying to fit the top 25%, bottom 25% etc.
Assign CS reps a fair share of buckets: Ensure each CSM handles a balanced proportion of “at-risk” and “neutral” accounts, preventing any single rep from being overloaded.
Make it transparent: Publish health scores on a shared dashboard so Sales, Support, and Product can see which customers need immediate engagement.
Assign follow-up tasks based on scores: At-risk customers get weekly check-ins, while healthy ones might only need quarterly reviews, ensuring resources match urgency.
Make it easy: Don’t overcomplicate the scoring system. Keep it simple and primarily focused on tracking the value you are adding.
This initiative will be led by Customer Success, but they’ll rely on your data expertise to help define the scoring model and track it on company-wide dashboards.
CS Rep by Health score | Great | Medium | Risk | |||
Logo | ARR | Logo | ARR | Logo | ARR | |
Alex Morgan | 4 | 46,324 | 16 | 212,944 | 30 | 402,570 |
Jordan Reed | 10 | 146,010 | 40 | 421,920 | 0 | 0 |
Casey Brooks | 6 | 60,324 | 12 | 161,256 | 32 | 363,328 |
Taylor Vaughn | 15 | 170,370 | 30 | 387,180 | 5 | 52,980 |
Riley Simmons | 12 | 163,128 | 12 | 157,320 | 26 | 326,794 |
Jamie Ellis | 5 | 51,935 | 10 | 116,990 | 35 | 356,160 |
Cameron Hayes | 2 | 27,846 | 8 | 118,624 | 40 | 419,560 |
Total | 54 | 665,937 | 128 | 1,576,234 | 168 | 1,921,392 |
16% | 38% | 46% |
Tip: It may seem logical to focus on the lowest-scoring customers, but often, it’s smarter to let those customers churn and instead prioritize upselling and expanding your strongest accounts.
6. Monitor the results
There are plenty of strategies to optimize this approach, and I’ll leave that to the CS experts. But as Finance, your role is to closely monitor the results and ensure they translate into measurable business impact. The easiest way to do this is to make sure your CS team is rewarded for their performance, in maintaining customers, in upselling customers, in driving revenue. To do so:
Switching CS to a bonus structure. Align bonuses with key retention and expansion metrics to drive proactive customer engagement. Think of this in terms of the sales team compensation that was discussed previously.
Data tracking. Set up KPIs within the systems CS teams use to track performance by rep. CS operates under constant pressure from urgent customer requests, shifting strategic priorities, and overwhelming data. Make it easier.
Showing the customer health score: Put this in your operational model, on your key KPIs, etc. It’s the lifeblood of your business. Transparency is key; don’t hide away from it.
Focusing on a few key metrics: Work with the CS team to identify and prioritize the most critical metrics for improvement, rather than trying to fix everything at once.
Make sure these metrics are actually helping the team prioritize, not distracting the team!
Tip: Embed a product team lead within the CS meetings. We will be talking about product metrics in an article later.
Conclusion
Your customers are your company. By focusing on their health, their expansion, you will grow your business. The best way to do this, as a finance professional, is to establish clear metrics, map the customer journey, and implement a straightforward health scoring model.
