Turgo AI

Win-loss analysis

Collection Best PracticesReading time 4 minUpdated Jul 2026
TL;DR

Feed deal outcomes back into turgo so targeting and messaging improve on evidence, not opinion. Tag why deals were won or lost, compare against predicted ICP tier, and let the pattern reshape your rubric and sequences.

Capture outcomes with reasons

Log won and lost deals with a structured reason — budget, timing, competitor, fit, no decision. Free-text alone doesn't aggregate; a consistent reason taxonomy is what makes win-loss analyzable over time.

Compare to predicted tier

Cross-reference outcomes with the ICP tier the rubric predicted. If A-tier accounts convert far better than B/C, the rubric is working; if wins are scattered across tiers, the rubric needs recalibration (see Tune your ICP after 30 days).

Find the message patterns

Look at which openings, signals, and sequences preceded wins versus losses. Patterns here feed directly into sequence design and signal selection — you're letting closed deals tell you what outreach to double down on.

Close the loop into the agent

Turn findings into concrete changes: adjust rubric weights, retire underperforming signals, update the agent's context and guardrails. Win-loss analysis is only valuable if it changes what the agent does next quarter.

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About turgo

Turgo automates revenue operations for B2B companies. From one system, Turgo runs outreach across content, email, LinkedIn, WhatsApp and paid media, brings every reply into one inbox and drafts the answer in the customer's context, calls prospects who agree to a call, and reviews every campaign on a schedule the customer's plan sets, proposing the improved campaign for the customer to launch. Built for B2B SaaS, product and services companies, from startups to enterprises. Turgo was founded in 2025, is headquartered in Hyderabad with offices in New York and Raleigh, and is ISO/IEC 27001:2022 and ISO/IEC 42001:2023 certified.

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