Every closed-won deal at a B2B consulting firm can trigger an automated case study pipeline: the client books a short interview, the call is transcribed and AI drafts a structured story with pull-quotes, typically shipping case studies six times faster.
Typical results
14
Case studies in six months
48 hrs
From interview to draft
2 hrs
Marketing polish per story
Figures reflect typical results for this kind of automation.
The challenge
The firm's best marketing asset — client success stories — almost never got written. After a win, everyone moved to delivery; months later nobody remembered the details, clients were harder to pin down, and marketing spent weeks chasing consultants for facts. Twelve months produced just three case studies from more than forty strong wins.
Before and after
Weeks from win to published
−83%Case studies per year
9.3×Marketing hours per case study
−80%The automation
We wired a Make scenario to the CRM's closed-won stage. The moment a deal closes, the client receives a warm email with a booking link for a 20-minute interview while the win is still fresh. The recorded call is transcribed automatically, and an OpenAI step turns the transcript into a structured draft — challenge, solution, results, plus three ready pull-quotes — which lands in marketing's review queue with the deal data attached.
How it works
- 01
Closed-won trigger
The moment a deal is marked closed-won in the CRM, the flow starts — no one has to remember anything.
- 02
Interview scheduled
The client gets a warm email with a booking link for a 20-minute interview while the win is fresh.
- 03
Auto-transcription
The recorded call is transcribed automatically and attached to the deal record.
- 04
AI drafting
OpenAI structures the transcript into challenge, solution, and results — with three ready pull-quotes.
- 05
Marketing polish
The draft lands in marketing's review queue with deal data attached, ready to edit and publish.
Starts from
- Closed-won trigger
- Client interview booking
Delivers
- Structured draft
- Ready pull-quotes
- To marketing queue
The impact
The cycle from win to published story typically drops from about twelve weeks to two, six times faster. A firm that used to manage three case studies a year can publish one or two a month, and marketing spends about two hours polishing each draft instead of ten writing from scratch.
Questions about this automation
What starts the case study workflow?
Marking a deal as closed-won in the CRM. That stage change sends the client a warm email with a booking link for a 20-minute interview while the project is still fresh, so nobody on the team has to remember to ask. Deals can be filtered by size or service line first.
How is the interview turned into a draft?
The recorded call is transcribed automatically and attached to the deal record. An OpenAI step then structures the transcript into challenge, solution and results sections and picks three pull-quotes in the client's own words. The draft lands in marketing's review queue with the deal data attached.
Is the story checked before it is published?
Yes. The automation only prepares the draft. Marketing edits it and can send it to the client for sign-off before anything is published, with the approval status tracked on the deal record so pending stories are easy to follow up. This is a multi-step build, usually rolled out in stages.