Which customers asked about pricing or a demo?
A sales rep or manager can use Signal to find customers who asked about pricing or wanted a demo, then turn the relevant results into a follow-up list. This is useful before a prospecting block, when you need to recover explicit customer interest from recent WhatsApp conversations.
What to ask Signal
Start a new analysis in Signal and ask:
- “Which customers asked about pricing or requested a demo in the last 30 days? Separate the two categories and show owners and supporting conversations.”
- “Show only Alex's conversations from the last 14 days.”
- “Find explicit customer demo requests in that period. Separate them from demos our team offered.”
- “Include questions about cost, quotes, and booking a product walkthrough. Show the supporting customer messages.”
- “For the matching customers, what did we reply and what follow-up is still needed?”
Alex is a fictional member. Use the real owner's name when narrowing the result. Keep follow-ups in the same analysis so you can refine the topic and period.
What Signal gives you
The chat can summarize the matching customers, identify their owners, distinguish pricing questions from demo requests, and suggest next steps.
The Analysis canvas may show a Topic cohort rather than a chart. A cohort is the set of conversations Signal identified as relevant to the question. It can show a confirmed count and a larger possible count that includes uncertain findings. Metrics for a topic cohort cover confirmed matching chats.
Coverage describes retrieval within the analysis scope. Open Details to see the period, owners, content search, and search method. In this workflow, the method can be semantic, so the search is based on meaning rather than only an exact word.
Matches, when available, show the supporting excerpts and conversations. Check who asked the question: a rep offering a demo is different from a customer requesting one.
Example from Signal. Names, messages and numbers have been replaced with fictional data.
Read the matches before building the list
Message in a fictional conversation | How to handle it |
|---|---|
Customer: “What would this cost for ten people?” | A pricing question worth reviewing. |
Customer: “Can we see a demo next week?” | An explicit demo request; check whether it was booked. |
Rep: “Would you like a demo?” | An offer from your team, not proof of customer interest. |
Customer: “Does that feature cost extra?” | A pricing clarification that may concern an existing deal or customer. |
One chat can cover both pricing and a demo. Do not automatically add category counts together or assume every match is a new prospect.
“No demo request identified” means none was identified by that query in its scope. It does not establish that nobody requested a demo elsewhere, outside the period, in unsynced messages, or in media.
Export results and prepare the follow-up
Step 1: Refine the scope
Confirm the time range, owner, topic, and uncertain findings. Ask a narrower follow-up if the list mixes customer requests with the team's outbound offers.
Step 2: Verify the source conversations
Review the actual request and the latest response. Check whether the customer already received a quote or booked a demo after the analysis was generated.
Step 3: Choose an export format
Open Export data on the Analysis canvas and choose CSV or Excel (XLSX).
Export the relevant analysis results, then inspect the file before using it as a working list. Do not assume every analysis exports the same columns or that an export is automatically a deduplicated contact directory.
Step 4: Turn the results into a working list
Keep one row per customer for your follow-up workflow, combining repeated matches where appropriate. Add the fields you need after checking the source, for example:
Customer | Owner | Interest | Verified next action | Due date |
|---|---|---|---|---|
Northstar Studio | Alex | Pricing | Send the requested ten-seat quote | Set by the rep |
Cedar Labs | Jamie | Demo | Confirm a suitable demo time | Set by the rep |
These are fictional examples of a working list you can prepare; they are not a promise of exact export column names. Use source conversation links where available, and fill in any missing details through your normal workflow.
Limits and useful tips
Keep the question within the last 90 days and specify the period. Topic search can miss relevant phrasing or include ambiguous results; refine the wording and review uncertain findings.
A confirmed match confirms relevance to the topic, not buying intent, a qualified opportunity, or a need for another message. AI may confuse the sender or misread a short reply. Check the conversation before following up.
Need help?
For any questions, email us at support@cooby.co 💜
Updated on: 06/11/2026
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