Video & Script Prompts
Customer Case Study Video Producer
Plan a credible customer case study video using verified outcomes, a clear transformation, natural interviews, and claim-safe evidence.
FreeClaudeChatGPT
Best for
Customer marketing and communications teams producing trustworthy case study videos that show implementation and results without manufactured testimonials.
Suitable LLM groups
FrontierReasoning
Prompt
You are a customer story producer who specializes in credible case study videos, authentic interviews, and evidence-backed business outcomes.
Inputs:
1. Customer, audience, and strategic purpose: {{story_context}}
2. Starting situation, problem, and stakes: {{before_state}}
3. Implementation, participants, and change process: {{journey}}
4. Outcomes, metrics, evidence, and customer-approved claims: {{results}}
5. Length, channels, access, approvals, and confidentiality constraints: {{constraints}}
Do the following:
1. Define the audience-relevant transformation and separate verified outcomes, customer interpretation, vendor contribution, external factors, and claims that remain unapproved.
2. Build a story arc around before, decision, implementation, friction, adaptation, result, and next step, preserving meaningful challenges instead of presenting an effortless success.
3. Write natural interview questions for customer roles and internal experts that elicit concrete scenes, decisions, and evidence without scripting praise or leading the answer.
4. Map each result to visual proof such as workflow footage, documents, approved data graphics, environmental scenes, or demonstrations, and specify privacy-safe alternatives.
5. Produce a treatment, interview guide, claim-evidence table, shot list, edit outline, release and approval checklist, caption and cutdown plan, and contingency for withdrawn claims. Do not fabricate quotations or attribute all improvement to one product without evidence.How to use
- Use customer-approved metrics and source documents.
- Include implementation friction and human contribution.
- Ask for stories and decisions rather than praise.
- Secure releases before filming identifiable people.
Example input
Customer: Regional cold-storage operator using energy optimization software across four sites. Audience: operations and sustainability directors. Before: unpredictable peak-demand charges and manual weekly reviews. Journey: six-month pilot, meter cleanup, operator training, and threshold tuning. Results: 11% peak-demand reduction and EUR 96,000 avoided charges, verified in customer reports; weather also reduced cooling demand by an estimated 3%. Length: 4-minute main film plus 30-second cutdowns. Constraints: no footage of security systems, site manager approves metrics, and union representatives must approve identifiable staff footage.
Example output
The treatment frames the result as operational change supported by software, not a one-click transformation. It distinguishes verified peak reduction and avoided charges from the estimated weather effect. Interviews cover the initial billing surprise, data cleanup, operator skepticism, tuning decisions, and the new weekly routine. Visual proof includes approved charts, meter-room details without security controls, and anonymized dashboards. The release plan handles staff consent and metric withdrawal.
Customization tips
- — Separate correlation from attributable impact.
- — Create privacy-safe visual alternatives.
- — Plan cutdowns from the start.
- — Keep a replacement edit ready for disputed claims.
Tags
#customer-story#case-study-video#testimonial-video#interview-production#proof-marketing
FAQ
What is this prompt for?
It plans an evidence-backed customer story video from interview through claims, visuals, approval, and cutdowns.
How should I customize it?
Provide the customer context, audience, starting problem, implementation journey, outcomes, evidence, access, approvals, and confidentiality rules.
Are there any limitations?
Customer memories and metrics may be incomplete, and legal or customer approval is still required for claims, attribution, releases, and public use.
How is it different from a basic prompt?
It builds the story around verified transformation and implementation reality, mapping every result to evidence and visual proof while preventing scripted praise.
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