The story centers on New energy vehicles teams who aggregate dealer feedback into improvements and support.
Overview
Background
Core collaborators include Channel manager, Service lead, Product manager, each adding context in a fast-moving thread.
Without a structured capture, decisions blur and follow-through slows.
Intervention
When the thread hits a decision point, the team triggers “@Holycrab_AI summarize dealer feedback and output improvement list”. Holycrab AI then Dealer meetings, service data, training notes, Cluster issues -> assess impact -> define support, Improvement list + support plan + follow-up.
The distilled output stays tied to the original context for quick review.
- Input Dealer meetings, service data, training notes
- Process Cluster issues -> assess impact -> define support
- Output Improvement list + support plan + follow-up
Deliverables & Impact
Deliverables include Improvement list, Support plan, Follow-up, giving the team a clear handoff.
Impact shows up as Prep time: 1 day -> 20 min; Resolution rate: Higher.
- Improvement list Product and process improvements
- Support plan Training and resources
- Follow-up Review schedule
Prep time1 day -> 20 min
Resolution rateHigher
Channel satisfactionUp
Example
Prompt: @Holycrab_AI summarize dealer feedback and output improvement list
Issue: inconsistent training materials
Support: unified kit + on-site tour
Follow-up: check after two weeks