Insights, not dashboards
Tableau gives you a chart; you still have to figure out what it means. David delivers the answer — "revenue dropped 12% because the signup flow on mobile broke last Tuesday" — with the chart as supporting evidence.
David·Data AnalystAI Data Analyst Agent that turns events into decisions
David plans the tracking, reads the results, and turns numbers into tasks your AI Team actually ships.
Analytics that change the product, not just the dashboard.
Trusted by builders at
Why dashboards do not change the product
Per-event pricing that grows with usage
The product gets bigger, the bill gets bigger, the value does not. David runs inside Atoms with no per-event meter for the analyses most product teams actually need to make decisions.
Screenshots in Slack that nobody can verify
Hex and Mixpanel land charts in messages a month later nobody can re-run. David's analyses live in Notebook blocks you can reproduce, audit, and challenge.
A day with David
From your first prompt to a shipped result — here is how David actually works.
- 01
Listen for the business question
David turns "why did revenue dip?" into a clear analytical question — not a dashboard request.
- 02
Query the live data model
Run the analysis against the database Bob designed inside your Atoms app — no CSV exports.
- 03
Spot the pattern and drill into the cause
Not just "conversion dropped 12%" — David traces it to the segment, the page, the device, the day.
- 04
Frame the finding with supporting evidence
One-sentence headline + chart + the SQL behind it — so the insight is reproducible, not magic.
- 05
Hand the insight to Emma for next sprint
Findings flow into the PM backlog — your roadmap is data-informed, not just gut-driven.
Hand-off to Emma
Everything David needs to drive data decisions
Event schema design
Naming conventions, properties, and identity model designed before any code is written.
Tracking handoff to Engineer
Events get wired into the codebase by Alex during the same task, not weeks later.
Notebook analyses
Reproducible Notebook block analyses you can re-run, audit, and share.
A/B test plans
Hypothesis, primary metric, guardrails, and sample size sketched before the test goes live.
Test cases for features
Acceptance tests that map directly to the user stories Emma wrote.
Plain-language findings
Insights written as decisions, not as charts only a data team can read.
Action handoffs
Findings become tasks for Emma or Alex so analyses actually change the product.
What changes when David is on your team
Hand-rolled workflows are slow, manual, and tool-heavy. Hover any card to see why each gain matters.
Why builders pick David over the rest
Compare vs
Coming from Tableau? Here is where David pulls ahead.
Wired into the product, not a CSV upload
ChatGPT can analyze a CSV you paste in. David queries the live data model Bob designed inside your Atoms app — so the analysis is always fresh and you don't waste time exporting and pasting.
Findings drive the next sprint
Looker reports sit on a dashboard nobody opens on Monday. David surfaces high-confidence findings to Emma directly, so the PM team prioritizes the next sprint based on what your data says, not just intuition.
Atoms vs Mixpanel: compare features, pricing, and capabilities
| Feature | Atoms Recommended | Mixpanel |
|---|---|---|
| Output | Insight + cause | Dashboard |
| Wired into your product data | Live query, no exports | Connector setup |
| Findings reach the PM team | Direct to Emma's backlog | Lives on a dashboard |
| Surfaces SQL behind the finding | Reproducible by anyone | Hidden in workbook |
| Charts and visualizations | Auto-generated | Drag-and-drop |
How David works with the rest of your AI team
David does not work alone. Here is how the handoffs land when you build with the full team.
DavidEmma
David's insights feed Emma's next sprint. The PM team prioritizes based on what your data says, not just intuition.
See how Emma worksDavidAdrian
David tells Adrian which channels actually convert. Ad budget shifts to winning audiences faster.
See how Adrian worksDavidBob
David flags data model gaps to Bob early. No "instrumentation tech debt" surfacing during a board review.
See how Bob worksWhat David analyzes for product teams
Concrete analyses David runs that lead to product changes.
- Diagnose a funnel
Funnel diagnostics
Find the step that loses the most users and the change that would fix it.
- Plan an A/B test
A/B test design and read
Design experiments, run them with Alex, and call the result with confidence intervals.
- Analyze retention
Retention cohorts
Compare retention across cohorts and surface what early signals predict long-term users.
- Review adoption
Feature adoption review
See which features actually get used and which can be cut without users noticing.
- Study activation
Activation studies
Define and measure the activation moment, then move it earlier in the user journey.
- Plan a launch
Pre-launch test plans
Write the test plan and tracking spec before launch so you know what to look at on day one.
Try these prompts with David
Design tracking for a new feature
@David design tracking for the referral program Emma scoped. Define the event schema, properties, and identity model. Coordinate with Alex so the events ship the same day as the feature.
Diagnose a drop in activation
@David week-1 retention dropped from 38% to 31% after the onboarding redesign. Run the funnel analysis in a Notebook, find the step that broke, and write the recommended change as a task for Emma.
Plan and call an A/B test
@David plan an A/B test for the new pricing page. Define the hypothesis, primary metric, guardrails, and sample size. After Alex ships both variants, call the result with a confidence interval.
Review feature adoption to cut scope
@David review the last 90 days of feature usage. List the bottom 5 features by adoption and the cost of supporting them. Tell me which we can cut without users noticing.
Meet the rest of David's AI team
No agent works alone. Tap any teammate to see how they handle their part of your product.
Frequently Asked Questions
Put David to work
Stop drowning in dashboards no one acts on. Let David design tracking, run analyses, and turn data into product changes with your AI Team in Atoms.
