Win Loss Analysis

The problem

CRM loss reason fields are notoriously unreliable because they are filled out by the reps who lost the deals. This leads to a false consensus that every deal is lost on "price" when the actual cause is often structural or targeting-related.

What it does

• Treats rep-reported loss reasons as hypotheses to be tested rather than facts.
• Compares won and lost deal sets across variables like deal size, industry, source, and sales cycle length.
• Separates "dark" deals from active competitive losses to identify specific funnel failures.
• Identifies if losses cluster in specific segments to determine if the issue is the pitch or the targeting.
• Weights direct buyer feedback above internal notes to find the ground truth.

Why this beats prompting it yourself

Most prompts simply summarize what is in the CRM fields. This skill applies a specific analytical methodology that cross-references deal metadata to find structural patterns that a standard summary would miss.

Use cases

• Identify why close rates have dropped in a specific quarter.
• Validate if "price" is a genuine objection or a placeholder for poor discovery.
• Audit whether the sales team is targeting the wrong industry or company size.
• Determine the impact of "no decision" versus competitive losses.

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