Many SaaS teams know which customers pay the most and which log in most often. Far fewer have a shared, consistent view of which accounts matter most right now when it comes to attention, risk, and opportunities.
A useful way to bring structure to this is a simple 2×2: Revenue × Health. It is not a forecasting model or a black-box score; it is a way to see which high-revenue accounts are truly healthy, spot expansion opportunities, and identify revenue at risk before it’s too late.
This article explains the matrix and how a tool like SaaS Tracker implements it with organization-level analytics. For more on the product, see the product page and pricing.
Why SaaS teams struggle to prioritize customers
Customer success often has long lists of accounts but no clear ordering. Sales tends to focus on whichever names are most familiar. Product and finance, meanwhile, have different views of what makes a “good customer”. The reasons are familiar: revenue data and usage data live in separate systems, health definitions are inconsistent or change often, and dashboards are built for aggregate reporting rather than prioritization.
The Revenue × Health matrix is a way to put revenue and engagement on the same axis and create a shared language — “champions”, “revenue at risk”, “expansion candidates” — so that teams can agree on where to focus.
The two key variables
The matrix relies on two dimensions: revenue (how much the account is worth) and product engagement / health (how strongly the account is using the product). You can use more granular scales in your implementation, but the conceptual model is easiest to explain as high vs. low on each axis.
Revenue
Revenue is usually measured as MRR or ARR, contract value or plan tier, and sometimes “strategic importance” in addition to pure € value. For the matrix, the key is to define what counts as “high” vs. “low” for your context — for example, high revenue might mean the top 25% of accounts by MRR and low revenue everyone else. The exact cutoff matters less than having a definition that is understood and applied consistently.
Product engagement
Product engagement or health reflects how frequently the account uses the product, whether they use the core features tied to value, and how usage is trending over time (stable, increasing, declining). In practice, this often boils down to an organization-level health score or a small set of signals: active days per month, core actions per week, and the presence or absence of key workflows. The important constraint is that the measurement should be reproducible and explainable, not a black-box.
The 2×2 matrix
Once you have a way to label accounts as high vs. low revenue and high vs. low engagement/health, you can place them into a simple 2×2: health or engagement on the x-axis (low → high), revenue on the y-axis (low → high). This yields four segments:
- Champions — high revenue, high engagement
- Expansion — low revenue, high engagement
- Revenue at risk — high revenue, low engagement
- Low value (or watchlist) — low revenue, low engagement
The power of the matrix comes from building specific playbooks for each segment, not from the diagram alone.
Champions: high revenue + high engagement
These are the customers you want more of: high contract value or spend, strong and consistent usage of key features, and often advocates or reference accounts. The recommended focus is to maintain value (ensure the product continues to solve their core problems), capture insights about what makes them successful, and explore co-marketing or reference opportunities where it fits. In many teams, champions are visually obvious from logo size and references, but the matrix helps document why they are champions.
Expansion: low revenue + high engagement
These accounts use the product heavily but pay relatively little today — and often have room to grow with more seats, more features, or higher tiers. The recommended focus is to validate fit (confirm they are seeing value and could use more), identify constraints such as budget, procurement, or missing features, and coordinate with sales for structured expansion conversations rather than ad-hoc upsells. Without a combined Revenue × Health view, expansion candidates tend to blend into the general “active” segment and get less targeted attention.
Revenue at risk: high revenue + low engagement
This is typically the most sensitive quadrant: accounts that pay a lot but show weak or declining engagement, with vulnerable renewals. Typical signals are few active users in relation to seats bought, declining use of core workflows, and logins concentrated around reporting or admin tasks only. The recommended focus is to understand causes (onboarding gaps, missing features, organizational changes), offer guidance through targeted enablement, QBRs, or collaborative planning, and make decisions — sometimes the right move is to let truly misaligned accounts churn, but the key is to do so intentionally, not by surprise. This segment is where combining usage signals and revenue context matters most.
Low value: low revenue + low engagement
These accounts pay relatively little and use the product weakly or sporadically. They are still important to understand: some will grow into expansion candidates, others are simply not a good fit. The recommended focus is to use them to test onboarding improvements at low risk, avoid over-investing high-touch resources unless there is a clear path to higher value, and decide whether to keep them on lower-touch plans. The goal is not to ignore these customers, but to calibrate expectations and investment.
How SaaS Tracker implements this
SaaS Tracker is built around organization-level analytics for B2B SaaS, which makes it a natural fit for a Revenue × Health view.
Revenue Health view
SaaS Tracker provides a Revenue × Health view that combines revenue signals (MRR, plan, contract context) with organization health (engagement trends, core actions, active days). Accounts are placed into segments similar to the matrix above, so teams can see which high-revenue accounts are true champions, which show weak or declining health, and where expansion candidates are clustered.
Signals
Under the hood, the view is based on organization-level events rather than individual sessions, aggregations over time windows (e.g. last 30 or 90 days), and signals that are designed to be reproducible and explainable — for example, “this account is flagged because active days and core actions fell vs. baseline”. This is not a guarantee about the future; it is a structured way to surface where attention is likely to matter most.
Org-level analytics
Because the underlying model is organization-first, the same event stream can support health views for churn-risk work, expansion views (strong usage, low current revenue), and governance views for internal reporting. For more detail on how SaaS Tracker handles organization-level analytics, see the product and docs.
Conclusion
The Revenue × Health matrix is deliberately simple. Its power comes from forcing clarity about what “health” means, making revenue context explicit for prioritization, and giving product, customer success, and finance a shared map of the customer base. A tool that can represent this view reliably at the account level reduces the need for ad-hoc spreadsheets and keeps prioritization grounded in actual behavior and value.
To see how SaaS Tracker implements the Revenue × Health view in practice, explore the product, review the documentation, or check pricing.
CTA: See the Revenue × Health view in SaaS Tracker on the product page.