Reports via the AI Co-Worker
An agency running ten clients doesn't have time to learn a BI tool, build ten dashboards, and keep them updated.
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An agency running ten clients doesn't have time to learn a BI tool, build ten dashboards, and keep them updated. Chatfuel takes a different route: the analyst is already on staff. Ask the AI Co-Worker a question in plain language — inside any client's company — and it answers from that client's real data: the conversations, the pipeline, the bookings, the outcomes. Every analytics report described here — starting with the end-to-end chain from ad spend to sales — is pulled exactly this way.
Ask anything
The Co-Worker covers the whole span from "one number, quick" to "read a hundred conversations and tell me what's wrong":
| You want | Ask something like |
|---|---|
| The funnel | "show conversion funnel", "business report" |
| Period stats | "new leads this month", "how does this month compare to last?" |
| Hot leads to push today | "who are my hot leads" |
| Deals about to die | "clients at risk", "who went silent" |
| One lead's full story | "what did we discuss with Maria?" |
| A contact, fast | "who is this number", "find contacts with email set" |
| Why deals are lost | "why do deals fail" |
| What leads keep asking | "what do clients ask most" |
| Where the AI struggles | "why is AI failing", "find AI mistakes in conversations" |
No query language, no filters to configure — the phrasing above is literally how you ask. For the funnel view specifically, the stage-by-stage breakdown is decoded in Funnel and drop-off report.
It reads the actual conversations
The Co-Worker doesn't just count rows — it reads the transcripts. Ask "why do deals fail" and it studies lost conversations against won ones, names the typical drop-off point, and lists the objection patterns — quoting the leads' real messages, not paraphrasing. Ask "what do clients ask most" and it mines the whole history for recurring questions, complaints, and missed opportunities. Sentiment, open issues, what was agreed with a specific lead — it's all in there, because it's all in the conversations. The full playbook for this kind of transcript mining is in Conversation analytics.
And it plays by an analyst's rules: it never invents a number. Every figure comes from the client's actual data, and if the data isn't there, it says so instead of estimating.
Every report ends in a to-do
A funnel chart that just sits there is trivia. The Co-Worker's reports end with what to do: a business report closes with its top recommendations, a risk scan ends with the list of contacts to rescue first, an AI diagnostic names the exact knowledge worth adding to the Knowledge Base. It surfaces and advises — the actions themselves stay yours to trigger, which is exactly how you want an analyst to behave around a client's live funnel. When a recommendation calls for a settings change, make it either way: in the client's automations at Fuely AI → Automations, or by telling the Co-Worker to apply it.
The agency workflow
Because every client is a separate company in your workspace, the same questions work identically across your whole roster. A Monday routine that used to be a morning of spreadsheet archaeology becomes ten minutes of chat: open each client's company, ask "business report" and "clients at risk", collect the numbers and the to-dos, move on. Same questions, every client, zero setup per client. And when those ten minutes need to become a monthly deliverable, Client reporting shows how to package them.
Note: Answers are only as good as the data behind them. The Co-Worker reports on what actually happened in the client's funnel — so the quality bar is set upstream. A well-filled Knowledge Base and qualification fields that match the niche make every answer sharper, from the funnel counts to the lost-deal analysis.