Reviewing closed-lost deal notes to identify why competitors are winning deals so we can update our sales training

• Filter the CRM for deals marked closed-lost during the last quarter
• Export the deal records and loss reason notes into a spreadsheet
• Read through individual notes to find mentions of specific competitors
• Group the mentions by competitor and loss reason manually
• Write a summary document outlining the main competitor trends
• Present the findings to the team before the next training session

Manually sorting through inconsistent text fields and trying to categorize messy notes without missing key details.

1. You

   1. Prepare the closed-lost deal file

   Filter the CRM for deals marked closed-lost during the last quarter and export the deal identifier, competitor information, loss reason fields, notes, segment, and deal value if available. Remove unrelated customer data before sharing the file for analysis.

2. AI

   2. Normalize and classify the notes

   Provide the exported file and ask AI to combine relevant text fields, standardize competitor name variations, and classify each deal by competitor, stated loss reason, evidence strength, and unresolved ambiguity. Require it to quote or reference the source note for every classification rather than treating missing information as a known reason.

3. You

   3. Set the analysis rules

   Inspect the proposed categories and decide which competitor aliases should be merged, which notes are too vague to count, and which categories are appropriate for sales-training decisions. This decision determines which patterns enter the final analysis and prevents weak or misread notes from driving training changes.

4. AI

   4. Create the competitor trend summary

   Using the approved categories, ask AI to group the deals by competitor and loss reason, identify recurring objections or process gaps, and draft a summary that separates observed evidence from interpretation. Include the supporting deal references, note excerpts, unresolved data gaps, and areas where the sample is too ambiguous for a firm conclusion.

5. You

   5. Choose the training changes

   Use the summary to decide which competitor responses, discovery questions, qualification practices, or objection-handling exercises should be added or revised for the next training session. Record the selected changes and reject findings that lack enough evidence, rather than asking AI to make the final training decision.

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