Analytics templates: the questions to ask your business data

Why templates are questions, not dashboards

Most dashboard templates give you twelve tiles and hope some of them matter. In practice, people use two or three and ignore the rest.

A better template is a short sequence of questions that follows how you actually investigate a business: start with the headline number, break it down, then find out why it moved. With conversational analytics, each question produces a chart on the canvas, and the next question builds on it.

Every template below follows the same pattern:

1. Headline: the one number that tells you if things are on track.
2. Breakdown: where that number comes from.
3. Change: what moved, and when.
4. Cause: why it moved.
5. Action: what to look at next.

SaaS metrics template

Data you need: a billing or subscription export (for example from Stripe), with customer ID, plan, amount, start date and cancellation date.

Questions to ask, in order:

1. What is our MRR by month for the last 12 months?
2. Break MRR into new, expansion, contraction and churned.
3. What is the monthly churn rate by plan?
4. Show 6-month retention by signup cohort.
5. Which 10 accounts contributed most to expansion revenue this quarter?

What to look for: a churn rate that is rising in one plan only, cohorts that drop sharply in month 2 (an onboarding problem), and expansion concentrated in a few accounts (a concentration risk).

Marketing analytics template

Data you need: an ad spend and conversions export by channel and campaign, with date, spend, clicks, signups and, if possible, revenue.

Questions to ask, in order:

1. What was total spend and total signups by week for the last 8 weeks?
2. Show cost per signup by channel.
3. Which campaigns have spend above average but signups below average?
4. Compare this month's cost per signup with last month, by channel.
5. If we moved 20% of budget from the worst channel to the best, what would signups have been?

What to look for: one channel quietly absorbing budget with rising cost per signup, and campaigns that drive clicks but not signups (usually a landing page mismatch).

Sales pipeline template

Data you need: a CRM export of deals, with stage, amount, owner, created date, close date and outcome. A CRMLeaf, HubSpot or Salesforce export all work.

Questions to ask, in order:

1. What is the total open pipeline by stage?
2. What is the win rate by quarter for the last four quarters?
3. Show average days from created to closed-won by deal size band.
4. Which stage has the biggest drop-off?
5. Which reps have the highest win rate on deals above $10,000?

What to look for: a stage where deals stall for weeks, win rate falling while pipeline grows (quality problem), and cycle time jumping for larger deals.

Financial analysis template

Data you need: a general ledger or expense export with date, category, department, vendor and amount, plus monthly revenue.

Questions to ask, in order:

1. What were total revenue, total costs and gross margin by month this year?
2. Show operating expenses by category, month over month.
3. Which vendors account for 80% of spend?
4. Which expense categories grew faster than revenue this quarter?
5. At the current burn rate, how many months of runway do we have?

What to look for: costs growing faster than revenue, spend concentrated in a handful of vendors, and one department driving most of the increase.

Operations template

Data you need: an orders or tickets export with created time, resolved or shipped time, status, category and assignee.

Questions to ask, in order:

1. How many orders (or tickets) did we handle per week for the last 12 weeks?
2. What is the median time from created to shipped (or resolved)?
3. Show that time by category and by day of week.
4. What share of orders missed our 48-hour target, by week?
5. Which categories have the most reopened tickets or returns?

What to look for: delays clustered on specific days (a staffing issue), one category with most of the misses, and a backlog that grows every Monday.

Product analytics template

Data you need: an events export with user ID, event name, timestamp and plan, or a daily active users table.

Questions to ask, in order:

1. What are daily and weekly active users for the last 90 days?
2. What share of new signups complete the key activation event within 7 days?
3. Which features are used by more than 50% of weekly active users?
4. Compare feature usage between users who stayed and users who churned.
5. Where do new users drop out of the onboarding flow?

What to look for: activation that differs sharply by signup source, features used heavily by retained users but rarely by churned ones, and a single onboarding step with most of the drop-off.

How to run any template

1. Open the playground and run the template on the demo dataset to see the flow.
2. Export your own data as CSV or Excel: one file per template is enough to start.
3. Upload it on the free Explore plan (files up to 50 MB).
4. Ask the questions in order, selecting each chart before you ask the next follow-up so context carries through.
5. Group the answers on the canvas into headline, breakdown and cause, then share the canvas with your team.

Tips for better answers

• Rename cryptic columns before upload. amt_usd becomes amount_usd; st becomes status.
• Keep one row per record. One row per order, per deal or per subscription change.
• Include dates as dates. A YYYY-MM-DD format avoids ambiguity.
• State your definitions. If "active" means "logged in within 7 days", say so in the question.
• Check one number you already know. It is the fastest way to confirm the data was read correctly.