Customer Success Glossary

The percentage of provisioned users or accounts that actively use a product within a defined window. A core indicator that the customer is realizing value, not just paying for access.

The share of customer issues resolved with AI involvement (suggestion, draft response, or full deflection). Measures how much CS leverage AI is producing, not how much AI is deployed.

The number of months of gross profit needed to recover the cost of acquiring a customer. Lower is better. Often owned by finance but watched by CS because retention extends payback economics.

A survey item asking how much effort it took to get something done with the product or with support. Lower effort correlates more strongly with loyalty than satisfaction does.

Customer or revenue loss over a period. Logo churn counts customers; revenue churn counts dollars. Distinguishing the two is the first step to diagnosing the cause.

The first stage of CS maturity. Foundations being built, processes are ad hoc, success depends on individual heroics. The work is to install repeatable basics, not to optimize.

The function that builds and maintains the systems CS runs on: tooling, segmentation, health scores, reporting, playbook tracking. Emerges as a distinct role in the walk and run stages.

A short post-interaction survey measuring how satisfied a customer was with a specific touchpoint. Useful for spotting service quality drift; weak as a leading indicator of retention.

The role responsible for a portfolio of customer accounts after the initial sale. The job is value realization, retention, and expansion, in that order.

The share of CSMs who use AI tools in their weekly workflow above a defined threshold. A leading indicator of whether AI investment is producing leverage or sitting unused.

A composite indicator that combines product usage, engagement, support signals, and other inputs into a single risk-or-strength rating per account. Useful for prioritization, not as the only retention metric.

The organizational pattern where retention and expansion are shared responsibilities across product, sales, marketing, and support. The opposite of CS-as-a-silo, where the CS team owns outcomes it cannot control alone.

Daily active users divided by monthly active users. A coarse stickiness measure; higher means the product is part of the user's daily routine. Less meaningful for products with naturally infrequent usage.

The frequency of customer issues that require executive or cross-functional intervention. Rising escalation rate is often a leading indicator that health scores are missing something.

Additional revenue from existing customers through upsell, cross-sell, or seat expansion. The component of NRR that pulls retention above 100%.

Expansion revenue expressed as a percentage of starting recurring revenue over a period. The growth-from-existing-customers half of NRR.

Recurring revenue retained from existing customers, excluding expansion. Caps at 100%. Tells you how leaky your bucket is before any growth is layered on top.

The percentage of customers retained over a period, ignoring deal size. A counterweight to revenue retention: a healthy NRR with falling logo retention often hides concentration risk.

One of three levels (Crawl, Walk, Run) describing where a CS organization stands across structure, process, data, and impact. Stage governs which playbooks and metrics to prioritize.

Recurring revenue retained from existing customers including expansion, net of churn and contraction. The single most-quoted CS health metric for SaaS. Above 100% means existing customers are growing faster than they are leaving.

The structured period after purchase during which a customer reaches first value. The boundary between onboarding and ongoing CS is when the customer has demonstrably achieved the outcome they bought the product for.

The percentage of customers who finish a defined onboarding milestone within a target window. A leading indicator of retention; customers who stall in onboarding rarely recover.

A documented, repeatable response to a specific customer situation: onboarding, renewal risk, expansion opportunity, escalation. Playbooks turn individual judgment into team-level consistency.

How many of a product's high-value features each account actively uses. Width matters less than depth: customers using 3 features deeply churn less than those using 10 features shallowly.

A scheduled review with a customer covering value delivered, outcomes achieved, and the path forward. Quarterly is conventional; the right cadence depends on segment and contract size.

The third and top stage of CS maturity. Customer outcomes are tracked and predicted, expansion is a repeatable motion, and AI-assisted workflows are in practice. The ongoing discipline is continued improvement within this stage.

The third stage of CS maturity. Operations are scaled and measurable, segmentation is multi-factor, digital and human touch are blended deliberately. The work shifts from execution to optimization.

The elapsed time from contract signature to the customer experiencing a first meaningful value moment, ahead of full outcome realization. A useful early signal in long onboarding cycles.

The elapsed time from contract signature to the customer reaching the outcome they bought the product for. Different from time to first login or time to onboarding completion, both of which are easier to measure but mean less.

The second stage of CS maturity. Process is forming, segmentation exists, basic health scoring is in place. The work is to standardize what worked at smaller scale and remove the dependency on heroics.