Glossary & benchmarks

Definitions you can quote

Every term carries the definition, the formula where one exists, and a benchmark with its source named. No fabricated numbers, ever.

32
Terms
11
With benchmarks

Analytics

Activation event

The activation event is the earliest user behavior that separates users who stay from users who vanish. For a project tool that's inviting a teammate; for an analytics tool, saving a first chart. Pick an event that predicts retention, not one that flatters your numbers — if your activation rate is above 70%, you're probably measuring the wrong event.

Analytics

Activation rate

Activation rate is the percentage of new signups who reach the moment your product first delivers value. It's the single best early indicator of whether onboarding works, because it counts people who experienced value — not people who merely showed up.

Benchmark

Announcements & Changelog

Changelog

A changelog is the public, chronological record of what shipped in your product. The three models worth copying: Linear's curated weekly editorial, Vercel's high-velocity tagged stream, and Notion's versioned mini-launches. Pick by shipping cadence, then keep the cadence — a stale changelog reads as a stalled product.

Analytics

Churn rate

Churn rate is the percentage of customers (or revenue) you lose in a period. It's retention's inverse and compounding's enemy: a 5% monthly churn rate means losing nearly half your base in a year. Diagnose it with cohorts and session replay before treating it with discounts.

Formula

Feedback & Roadmap

Closing the feedback loop

Closing the feedback loop means telling the people who asked for something that you shipped it — automatically, at the moment it ships. It's the cheapest retention lever in product management, and almost nobody pulls it.

Benchmark · Gartner

Analytics

Cohort analysis

Cohort analysis groups users by when they started (or what they did) and tracks each group's behavior over time. It separates real product improvement from growth masking decay: if newer cohorts retain better than older ones, the product is getting stickier.

Analytics

Conversion window

The conversion window is the time limit a funnel gives users to complete the final step. Without one, someone who activates in month six counts the same as someone who activates on day one. Match the window to your onboarding promise: if your product should deliver value in a day, measure a day.

Surveys

Customer Effort Score (CES)

CES asks how easy it was to get something done — resolve an issue, complete a task — typically on a 1–7 agreement scale. It predicts loyalty in support contexts better than delight does: customers leave over friction more often than they stay for wow.

Surveys

Customer Satisfaction Score (CSAT)

CSAT measures satisfaction with a specific interaction — a support reply, an onboarding step, a feature — usually on a 1–5 scale, asked immediately after the moment it measures. Unlike NPS, it's transactional: good for finding broken moments, bad for measuring loyalty.

Formula

Analytics

DAU/MAU ratio (stickiness)

The DAU/MAU ratio divides daily active users by monthly active users to measure how often your monthly audience shows up. A ratio of 25% means the average monthly user is active about a week and a half per month. Expected values differ sharply by category — compare against products with the same natural usage frequency, not a universal bar.

Formula

Interactive Demos & Videos

Demo completion rate

Demo completion rate is the percentage of viewers who reach the last step of an interactive demo. It's the demo world's activation rate: starts are cheap, finishes signal intent. Copy and step count move it more than production polish does.

Benchmark · Arcade

Analytics

Feature adoption rate

Feature adoption rate is the percentage of your active users who use a specific feature in a given period. It's the launch metric that matters after the announcement: reach tells you who saw it, adoption tells you who changed their behavior.

Formula

Feedback & Roadmap

Feature request management

Feature request management is the system for collecting, deduplicating, prioritizing, and answering feature requests at scale — statuses, tags, merge rules, and auto-assignment instead of a spreadsheet and guilt. Done right, every request ends in one of two messages: "we shipped it" or an honest no.

Support Suite

First response time (FRT)

First response time is how long a customer waits for the first human (or accountable AI) reply after opening a support request. It's the support metric customers feel most: a fast first touch buys patience for the actual fix. Measure the median and the tail, and measure per channel — Slack expectations are not email expectations.

Analytics

Funnel analysis

Funnel analysis measures how many people complete a fixed sequence of steps — signup to activation, trial to paid, cart to checkout — and where the rest drop off. It counts people, not events: every later step uses the same population, so each drop-off is a real person who stalled.

Interactive Demos & Videos

Interactive demo

An interactive demo is a clickable, self-guided walkthrough of a product built from captured screens — no sandbox, no sales call. Buyers use them to evaluate before signup; the same captures work in onboarding, changelogs, docs, and support replies.

Benchmark · Arcade

Surveys

Microsurvey

A microsurvey is a one-to-three-question in-app survey triggered by a specific behavior — closing a feature, finishing onboarding, hitting an error. Short and contextual beats long and scheduled: the response rate advantage comes from asking at the moment the user has the answer.

Benchmark · Chameleon

Surveys

Net Promoter Score (NPS)

NPS measures customer loyalty by asking how likely someone is to recommend you, on a 0–10 scale. Scores of 9–10 are promoters, 7–8 passives, 0–6 detractors. The score ranges from −100 to +100.

Benchmark · Retently

Analytics

North star metric

A north star metric is the single measure of delivered value a team aligns around — the output at the top of a tree of input metrics you can actually move. A good one captures value delivered to customers, not value captured from them: messages sent, not revenue.

Feedback & Roadmap

Now-Next-Later roadmap

Now-Next-Later organizes a roadmap by commitment horizon instead of dates: Now is in progress, Next is committed, Later is directional. It communicates priority honestly — near things are concrete, far things are vague — which is exactly how real planning works.

Tours & Onboarding

Onboarding checklist

An onboarding checklist is a persistent in-app list of setup tasks that guides new users to activation. It works because it externalizes progress: users see what's left, and the Zeigarnik itch to finish does the rest. Keep it short and tie every item to an actual activation behavior.

Benchmark · Userpilot

Tours & Onboarding

Product tour

A product tour is a guided sequence of in-app steps — popovers, hotspots, modals — that walks users through a workflow. The data says restraint wins: contextual, user-triggered guidance outperforms forced linear tours, and completion collapses as step count grows.

Benchmark · Chameleon

Feedback & Roadmap

Public roadmap

A public roadmap shows customers what you're considering, building, and shipping — usually as Now/Next/Later or status columns fed by a feedback board. It sets expectations without promising dates, and it turns feature requests into votes you can actually count.

Announcements & Changelog

Release notes

Release notes explain a specific release to the people it affects: what changed, why it matters, what to do next. Lead with the benefit, show the feature, link the docs. The reader is deciding whether to care in one scroll — write for that scroll.

Analytics

Retention curve

A retention curve plots what percentage of a cohort is still active over time. The shape matters more than any single point: a curve that flattens means a retained core exists; a curve that slides to zero means the product hasn't found product-market fit for that cohort yet.

Analytics

Retention rate

Retention rate is the percentage of users from a starting cohort who come back and use your product in a later period. It's the metric that compounds: acquisition fills the bucket, retention decides whether the bucket has holes.

Formula

Feedback & Roadmap

RICE score

RICE scores feature ideas on Reach, Impact, Confidence, and Effort to force explicit trade-offs instead of loudest-voice prioritization. The output number matters less than the argument it forces: writing down reach and confidence exposes which bets are actually guesses.

Formula

Surveys

Sean Ellis test (PMF survey)

The Sean Ellis test asks users: "How would you feel if you could no longer use this product?" If at least 40% answer "very disappointed," the product has a strong product-market fit signal. Survey users who recently experienced the core product, not everyone in the database.

Benchmark · Sean Ellis

Analytics

Session replay

Session replay records real user sessions as replayable video-like recordings, reconstructed from DOM events. It answers the question analytics can't: not where users dropped off, but what it looked like when they did. Modern replay masks text and PII at capture time, before anything leaves the browser.

Surveys

Survey response rate

Survey response rate is the percentage of people shown a survey who answer it. In-app surveys dramatically outperform email because they catch users in context. Published benchmarks differ by methodology — averages and medians are different claims — so state which one you're quoting.

Benchmark · Refiner, Survicate

Help Center

Ticket deflection rate

Ticket deflection rate is the share of would-be support tickets resolved by self-service — help center articles, AI agents, widget chat — before a human touches them. The category's numbers are contested: measure deflection as tickets avoided against a stated baseline, not as bot conversations that ended.

Benchmark

Analytics

Time to value

Time to value is how long it takes a new user to reach your activation event. Shorter is almost always better: every extra day between signup and first value gives users another chance to forget why they came. Measure the distribution, not just the average — the median lies when a few slow users drag the tail.