win-loss-pattern-analyzer

Win/Loss Pattern Analyzer

Sales teams need to understand why they win and lose deals. This skill analyzes historical closed opportunities to identify patterns, highlight what winners do differently, recognize common loss signals, and provide data-driven playbook recommendations.

Instructions

Step 1: Define Analysis Scope

When user asks "Why are we losing enterprise deals in manufacturing vertical?":

1.1 Parse Analysis Criteria: Extract filters from user query:

• Deal size segment (enterprise, mid-market, SMB)
• Industry/vertical (manufacturing, financial services, etc.)
• Time period (last 6 months, last year, etc.)
• Sales stage of loss (if applicable)
• Competitor (if mentioned)
• Owner/team (if specified)

1.2 Build Analysis Query:

Important: Dataverse SQL Limitations Dataverse SQL does NOT support: DATEADD(), GETUTCDATE(), subqueries, HAVING, DISTINCT, UNION, CASE, DATEDIFF. Calculate date filters and durations programmatically (e.g., use '2025-03-01' for last year).

SELECT opportunityid, name, accountid, customerid, estimatedvalue, actualvalue,
       createdon, actualclosedate, statecode, statuscode,
       salesstage, closeprobability, budgetstatus, need, 
       purchasetimeframe, purchaseprocess, decisionmaker,
       description, qualificationcomments, msdyn_forecastcategory,
       ownerid
FROM opportunity
WHERE actualclosedate > '2025-03-01'

Then filter programmatically for statecode = 1 (Won) or statecode = 2 (Lost).

Add Segment Filters:

-- Enterprise deals (example threshold)
SELECT opportunityid, name, accountid, estimatedvalue, actualvalue,
       createdon, actualclosedate, statecode, statuscode
FROM opportunity
WHERE actualclosedate > '2025-03-01'
AND estimatedvalue >= 100000

-- Industry filter (via account join)
SELECT o.opportunityid, o.name, o.estimatedvalue, a.industrycode
FROM opportunity o
JOIN account a ON o.accountid = a.accountid
WHERE o.actualclosedate > '2025-03-01'
AND a.industrycode = 12