Context & Entry Point (Start Where They Are)
- What prompted this conversation now?
- What problem are you trying to solve first?
- Is this coming from operations, engineering, or IT?
(Do not interrupt. Let them talk.)
Dashboards (Accept, Then Qualify)
If they mention dashboards:
- Who uses these dashboards day to day?
- What decisions are made based on what people see there?
- How often are those dashboards looked at?
Signal to listen for: Operational decisions vs. reporting.
Operational Importance (Critical Pivot)
Ask one or two only:
- What happens if this data is missing or delayed?
- What happens if the data turns out to be wrong?
- Has this data ever been needed to explain an incident or issue?
If consequences exist → historian conversation is valid.
History & Lookback (Historian Signal)
- How far back do you typically need to look?
- Do you compare performance across time periods?
- Do you ever need to analyze “what happened last time”?
Even vague answers are enough.
Events & Context (Without Jargon)
- Do you analyze things like batches, runs, downtime windows, or incidents?
- Do you need to understand performance during those periods, not just overall trends?
If yes → event-based analysis is needed.
Scale & Growth (Future Proofing)
- Is this for one site or multiple sites?
- Are more assets, sensors, or sites coming?
- Is the amount or frequency of data increasing?
Any growth = strong fit.
Current Stack & Friction (Optional)
- What are you using today to store this data?
- What works well?
- What’s painful or limiting right now?
Do not attack the current solution.
Ownership & Decision (Reality Check)
- Who owns the outcome of this project?
- If this works, what would success look like?
- What’s the next step after validation?
This avoids stalled deals.
Close the Discovery (Set Direction)
“Based on what you shared, it sounds like the dashboards are operational and the data needs to be trusted over time. The usual next step is a small PoC to validate ingestion, history, and analysis with real data.”
Fast Internal Read (For Sales)
Strong Fit If:
- Dashboards drive operations
- History matters
- Events or incidents matter
- Someone owns the outcome
Weak Fit If:
- Dashboards are cosmetic
- Data is disposable
- No owner or urgency
One Rule for Discovery
Do not explain TDengine until the customer explains their pain. Let their answers justify the historian.
