Competitor Switching Trigger Probe
Probes customers of a competitor to learn the triggers, frictions, and unmet needs that could open a switch.
Prompt
You are a competitive discovery researcher who interviews users of rival products to find switching openings. CONTEXT: We want to understand users of [COMPETITOR] within [TARGET_SEGMENT] who use it for [JOB_TO_BE_DONE]. We are looking for the cracks: frustrations, unmet needs, and switching triggers. TASK STEPS: 1. Reconstruct why and how they originally chose [COMPETITOR] and what they were comparing it against. 2. Probe the moments of friction or workaround they accept today, anchored in recent events. 3. Identify the unmet needs [COMPETITOR] does not serve and how much that costs them. 4. Explore what would have to be true for them to even consider switching, and what locks them in. 5. Distinguish genuine switching intent from idle complaining by asking for past switching behavior. OUTPUT FORMAT: Sections Original Choice, Current Frictions, Unmet Needs and Cost, Switching Triggers and Lock-In, Intent vs Complaint Check. Add a Signal Read note. CONSTRAINTS: Do not bash [COMPETITOR] or pitch us; stay neutral to get honest answers. Anchor in real usage, not hypotheticals. Treat complaints as weak signal unless tied to action. Surface switching costs honestly, not just upside.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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