Analytics

How to Build a Product Usage Analytics Dashboard With AI

A product usage analytics dashboard with AI turns raw event data into charts your team can act on. On aidowith.me, the Analytics Dashboard route has 14 steps that walk you through building a dashboard from scratch. You start by connecting your data source and defining the metrics that matter: daily active users, retention cohorts, feature adoption rates, and session duration. AI helps you write queries, structure data transformations, and pick the right chart type for each metric. The route covers cohort analysis setup so you can see 7-day and 30-day retention curves side by side. It also shows how to build feature adoption funnels that reveal where users drop off. Most product teams spend weeks getting a dashboard like this right. With this route, you'll have a working version in about 3 hours and a framework for adding new metrics as your product grows.

14 steps ~3h For analysts Free
Start This Skill →

The Problem and the Fix

Without a skill

  • Your product data sits in 3 different tools and nobody has a single view of usage
  • Building retention cohorts in a spreadsheet takes your analyst 2 full days every month
  • You can't answer the CEO's question about feature adoption without a 4-hour data pull

With aidowith.me

  • A single dashboard showing DAU, retention, and feature adoption, updated automatically
  • Cohort analysis with 7-day and 30-day retention curves built in under an hour
  • A framework for adding new metrics without rebuilding the whole dashboard

Who Builds This With AI

Ops & Analysts

Summaries, process docs, and structured output from messy inputs.

Managers & Leads

Reports, presentations, and team comms handled faster.

Marketers

Content, campaigns, and briefs done in hours instead of days.

How It Works

1

Connect data and define metrics

Link your event data source and decide which metrics to track. AI helps you pick the right KPIs based on your product type.

2

Build charts and cohort analysis

Create DAU trends, retention cohorts, and feature adoption funnels. AI writes queries and suggests chart types for each metric.

3

Polish and share

Add filters, set up auto-refresh, and configure access for your team. Walk away with a dashboard that updates on its own.

Build your product usage dashboard with AI

14 steps. About 3 hours. A dashboard your team will check every day.

Start This Skill →

What You Walk Away With

Connect data and define metrics

Build charts and cohort analysis

Polish and share

A framework for adding new metrics without rebuilding the whole dashboard

"We went from a messy spreadsheet to a real dashboard in one afternoon. Now the whole team checks it before standup."
- Product Manager, Series A startup
See full skill: An Analytics Dashboard

Questions

You need event-level data with user IDs, timestamps, and event names. Most products already have this in tools like Mixpanel, Amplitude, BigQuery, or a database. The route shows you how to connect your source and structure queries, even if your data is messy. No prior analytics experience is required. The route provides clear guidance at every step so you can move from setup to results without guesswork.

Yes. The route starts with standard metrics like DAU and retention, then shows you how to add custom ones. If your product has a unique activation event or a specific feature funnel, you define it during the route and AI helps you build the query and chart. The dashboard is yours to extend.

The route is tool-agnostic. You can use Google Sheets, Looker Studio, Metabase, Tableau, or any dashboard tool that accepts data queries. AI generates the logic and you apply it in your preferred platform. Most users pick whatever their team already has access to. The route provides clear guidance at every step so you can move from setup to results without guesswork.