Funnel Analyst
Compares signup, product use and billing records to show where potential customers drop out before paying.
Use cases · Growth & Customer Analytics
Your team has the data, but not the hours to dig into every drop. AgentWorks agents watch your funnel, activation and retention every day, explain each drop with the evidence behind it, and follow the fix until the number recovers.
How this team runs on agents
Goal Illustrative
“Recover checkout conversion to 3.5%”
Agents own the target end to end. Every day the number is checked and what is not working gets changed.
Flow
Daily metric check
Read the funnel every morning, flag any drop, break it down by release, device and source.
Crew
Growth analyst
Answers "why did signups drop?" with the evidence: the release, the screen, the tickets.
People
Approve the exceptions
The head of product decides the fix; the agent tracks whether the number comes back.
Everyone’s personal AI connects in, through AgentBridge
Claude CoworkChatGPTThe head of product asks ChatGPT "why did activation dip?" and gets the analyst’s answer with charts.
Claude CodeCodexCursorAn engineer’s Claude Code receives the evidence and the failing screen, and proposes the fix.
SlackWhatsAppEveryone else asks and approves where they already talk.
Example goal
Recover checkout conversion
target 3.5%. Illustrative numbers.
Premade agents
Each one comes with its goal, its tools and its guardrails. We set up the first one with you.
Compares signup, product use and billing records to show where potential customers drop out before paying.
Checks whether customers are using a feature and reaching the useful first result your team defined.
Compares groups of customers over time so your team can see who gets started and who keeps coming back.
Investigates a change in your signup-to-payment funnel and proposes an experiment for your team to review.
Compares how customer groups get started and return, then proposes a retention experiment for your review.
Works with Mixpanel, PostHog or your analytics through MCP, your database, Slack and your ticketing tool. See connectors →
How it works
Pick a premade agent or describe the outcome, then agree the metric and target with us.
Agents work through your tools on a schedule. You choose which actions run on their own and which wait for a person; we agree those rules during setup.
Every run records what it did and what it moved, so you see progress, not activity.
What broke gets fixed, what didn't work gets dropped, and the next idea gets tried.
FAQ
No. Agents read the analytics and database you already have. We connect them with you on the first call.
No. It explains and recommends. Changes go to your team, and it checks the number afterwards.
Any you can query: signups, activation, conversion, retention, revenue per user.
More use cases
Book a short call. We connect your tools, pick the agent and agree the metric together.