BI & Analytics Vocabulary

Master the language of dashboards, metrics frameworks, funnels, and attribution — essential for data analysts, PMs, and anyone who presents data to stakeholders.

Intermediate 5 exercises BI & Analytics
Tip: BI vocabulary is heavily context-driven — the same metric can be a KPI for one team and a guardrail for another. Focus on how terms are used in sentences, not just their definitions.

0 / 5 completed

Exercise 1 of 5

Multiple choice

The head of product says: "We track dozens of KPIs, but leadership wants us to align every team around a single metric that best captures the value we deliver to customers — something like 'weekly active users who complete a core action'."

What term describes this single unifying metric?

Exercise 2 of 5

Fill in the blank

The analyst explains: "Daily sign-ups tell us what is happening right now and help us predict future revenue — that makes sign-ups a _______ indicator, whereas monthly revenue itself is a _______ indicator because it reflects past activity."

Exercise 3 of 5

Multiple choice

The growth team reviews a report: "We have 10,000 users visit the pricing page, 2,000 start the checkout, but only 400 complete the purchase. The biggest drop-off is between checkout start and payment confirmation. We need to run experiments to improve that step."

What practice describes systematically improving the percentage of users who complete each step?

Exercise 4 of 5

Definition match

A user sees a Facebook ad on Monday, clicks a Google search ad on Wednesday, and buys on Friday after clicking an email link. Which attribution model gives all credit for the sale to the Facebook ad?

Exercise 5 of 5

Multiple choice

The data analyst presents to the board: "I'd like to walk you through the dashboard. As you can see here, our D1 retention dropped from 42% to 36% last month, which is driving up churn. If we look at the cohort of users who signed up in April, they show stronger D7 numbers — 28% versus the 21% we saw in March. This suggests the onboarding changes we shipped in late March are working."

What does "D7 retention of 28%" mean in this context?

Vocabulary Reference

Key BI & Analytics terms used in this exercise and in day-to-day data work.

KPI (Key Performance Indicator)
A quantifiable measure used to evaluate progress towards a business objective. Teams track multiple KPIs; not every metric is a KPI.
North star metric
The single metric that best captures the core value a product delivers to customers, used to align the whole organisation around one goal.
Guardrail metric
A metric set as a boundary condition — an experiment may optimise its primary metric only as long as guardrail metrics (e.g. latency, error rate) do not degrade beyond an acceptable threshold.
Leading / lagging indicator
A leading indicator predicts future outcomes (e.g. sign-ups, feature adoption rate). A lagging indicator confirms past results (e.g. quarterly revenue, annual churn).
Cohort
A group of users who share a common characteristic within a defined time period — typically the week or month they first signed up. Cohort analysis tracks how behaviour changes over time for that group.
D1 / D7 / D30 retention
The percentage of users from a cohort who are still active on day 1, 7, or 30 after their first session. Standard benchmarks for measuring product stickiness and habit formation.
Churn rate
The proportion of users or customers who stop using a product within a given period. High churn undermines growth — acquiring new users cannot compensate for losing existing ones.
Funnel & drop-off
A funnel maps the sequential steps users take towards a goal (e.g. visit → sign up → activate → pay). Drop-off is the percentage of users who leave the funnel at a given step.
Conversion rate & CRO
Conversion rate is the percentage of users who complete a desired action. CRO (Conversion Rate Optimisation) is the practice of running experiments and UX improvements to increase that percentage.
Attribution (first-touch, last-touch, multi-touch)
Attribution assigns credit to marketing touchpoints for a conversion. First-touch credits the first interaction; last-touch credits the final one; multi-touch distributes credit across all touchpoints in the customer journey.