60–90 minute calls do not scale
A proper JTBD conversation is long, and you need dozens of them to see the patterns. Multiply 75 minutes by 30 customers across two time zones and the calendar problem alone kills the project.
Jobs-to-be-done without booking calls.
The JTBD conversation is the gold standard for understanding why customers switch, and almost nobody actually runs them. Diaform is an AI agent that conducts the full jobs-to-be-done conversation structure, probes the four forces, and captures the switch trigger moment, all over a shareable link. The depth of a moderated study, without the calendar.
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Why teams stop running JTBD conversations
Researcher skill is the bottleneck
JTBD conversations live or die on the AI agent's ability to follow the timeline, probe the forces, and avoid leading questions. Most teams have one person who can do this, and that person is always busy.
Synthesis is days of transcript coding
Even when you get the conversations done, turning twenty hours of audio into push, pull, anxiety, and habit categories is a week of manual work. The insight arrives long after the decision was made.
How Diaform runs JTBD conversations end to end
01
Follows the JTBD conversation structure
The AI agent opens with the timeline, walks the customer to the switch event, and stays in the structure even when the customer wants to wander into feature requests.
02
Probes the four forces by name
Push from the old solution, pull of the new, anxiety about switching, habit holding them back. The AI knows what to fish for, and what each force should sound like in a real answer.
03
Captures the switch trigger moment
The most important sentence in every JTBD conversation is when the customer remembers the exact moment they decided. The AI is trained to recognise that moment and slow down to capture it in the customer's own words.
04
Structured JTBD responses
Each completed session includes summaries, sentiment, answer confidence, optional notable quotes, and the transcript. Export the response set to code pushes, pulls, anxieties, and habits across customers.
05
Multilingual native conversations
The AI conducts the conversation in the customer's native language and summarizes back to English for your team. Switching stories are deeply personal, running them in a second language loses the nuance.
06
No scheduling, ever
Share one link. Customers complete the JTBD conversation when it suits them, on any device. You never open a calendar invite, and the response rate goes up, not down.
How to run a JTBD study with Diaform
- 01
Load your JTBD conversation guide
Paste your existing guide, or start from a template. The AI follows your structure: timeline, switch event, four forces, desired outcome, alternatives considered.
- 02
Upload product and competitor context
Add notes on your product, the alternatives you compete against, and the language your customers use. The AI references this in real time when probing pulls and anxieties.
- 03
Share one link
Send the link to recent switchers, churned customers, or your target segment. Each respondent gets a fresh AI-led session in their own time, in their own language.
- 04
Review and code the JTBD responses
Review each structured response and transcript, verify any notable quote, and use search or CSV export to compare switch triggers and forces across the cohort.
What teams use JTBD conversations for
New product JTBD validation
Run JTBD conversations with the segment you think will switch to a new product, before you build. Find out whether the push is strong enough, or whether you are designing a vitamin nobody hires.
Competitive switching research
Talk with customers who recently moved to or from a competitor. Surface the exact trigger, the anxieties they had, and the alternatives they almost picked instead.
Churned-customer JTBD post-mortem
Run a JTBD conversation in reverse with churned customers. What pushed them away from you, what pulled them to the next solution, and what habit you failed to disrupt.
JTBD-driven persona work
Replace demographic personas with job-based ones. The AI surfaces the recurring jobs, contexts, and switching patterns across a segment so personas reflect behaviour rather than headshots.
Market entry research
Before entering a new market or vertical, run JTBD conversations with the segment in their native language. Find out what they currently hire, what they wish was different, and what would trigger a switch.
Feature deprecation research
Before killing a feature, talk with the customers who use it about the underlying job. Decide whether the job goes away, gets folded in, or needs a new solution to take its place.
Traditional JTBD conversations vs. AI-led JTBD
Traditional moderated JTBD conversations
- 60–90 minute calls that do not scale beyond a handful
- Researcher skill is the bottleneck on every study
- Weeks of manual transcript coding before insights land
- Single language, usually the researcher's, not the customer's
- Calendar friction sinks half the recruited respondents
Diaform
- 60-minute conversation depth in an async format that scales
- AI follows the JTBD structure on every single session
- Structured responses and transcripts ready for analysis
- Multilingual conversations in the customer's native language
- Switch-trigger probing built into every conversation
Frequently asked questions.
The practical details behind setting up, running, and scaling this kind of research with Diaform.
Jobs-to-be-done (JTBD) is a research framework that explains customer behaviour through the lens of the job they are hiring a product to do. Instead of asking what features people want, a JTBD conversation walks a customer back to the moment they switched solutions and surfaces the underlying job, the forces pushing them away from the old option, the forces pulling them to the new one, the anxieties about switching, and the habits holding them in place. It is widely considered the most predictive form of qualitative customer research.
More conversations your team can run.
Explore the other ways Diaform can turn a static request for feedback into a useful conversation.
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