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Lead intent signal review

Reviews activity and account signals to identify leads showing meaningful buying interest, with evidence, recency, confidence, and recommended priority. Use for intent review, high-intent lead detection, buying-signal analysis, prospect prioritisation, or sales research.

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Publicado 21 de ago de 2026 · Actualizado 26 de ago de 2026

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Requisitos

Define accepted signals, recency and priority rules. Add the ICP and privacy boundaries.

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Lead intent signal review

Purpose

Find and rank credible signs that a lead or account may have a relevant business need. The result supports prioritisation while making clear what is observed, what is inferred, and what still needs confirmation.

Scope

Lead activity, public company events, hiring or investment signals, stated problems, engagement records, recency, fit, and evidence quality.

Excluded: automated outreach, covert monitoring, personal profiling, and claims that a signal proves purchase intent.

Data basis

  • Lead, account, activity, and opportunity records in scope.
  • Public sources when enabled.
  • ICP and intent interpretation guide in scope.

Result

A signal register with confidence and a prioritisation memo with validation questions.

Quality criteria

  • Every signal has a source, date, and affected account.
  • Duplicate signals are consolidated.
  • Recency and fit are assessed separately.
  • Weak signals cannot alone create a high-priority recommendation.
  • Unknown data is not treated as negative evidence.

Instructions

Use the configured lookback and signal definitions. Prefer direct statements or primary evidence. Record competing explanations when a signal is ambiguous. Explain priority using signal strength, recency, account fit, and data confidence. Keep recommendations as research priorities, not facts about a buyer's intent.

Adapt before use

Keep a clear audit trail throughout the run. Use the source wording and field values that support each material conclusion, and retain uncertainty when the evidence does not decide the issue. Separate a missing record from a negative result and a contradictory record from an exception. Prefer a short, prioritised result over unsupported completeness. Check that counts, identifiers, dates, and labels agree across the written result and the structured output. When a rule, source, or mapping is unavailable, name the limitation and explain how it affects interpretation. Do not silently infer ownership, approval, timing, or business intent.

  • Define accepted signals, lookback periods, and confidence labels.
  • Add the ICP and priority bands.
  • Specify public-source and privacy boundaries.

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