PlaybookPrompts

Define the exact triggers that should fire an expansion revenue motion

Business Strategy revenuesaascustomer-success

Most SaaS teams know expansion revenue matters but never codify when to actually pursue it. This prompt produces a concrete trigger map your CS and sales teams can act on this week.

Prompt
You are a revenue strategy consultant. My product is {{PRODUCT_DESCRIPTION}}. Our current pricing tiers or expansion levers are {{PRICING_OR_EXPANSION_LEVERS}}. Our average contract value is {{AVERAGE_CONTRACT_VALUE}}.

1. Propose five specific, measurable behavioral or usage signals that should trigger an expansion conversation. For each signal, specify: (a) what data you would track, (b) the threshold that indicates readiness, and (c) who on the team should act.
2. For each trigger, write one sentence of talk-track a CS rep could use to open the expansion conversation without it feeling like a sales push.
3. Identify which triggers are likely available in our current tooling versus which require instrumentation we probably don't have yet.
4. Rank the five triggers by expected expansion revenue impact and implementation ease, displayed as a simple 2×2 table.
5. Note any edge cases where a trigger might fire but expansion would be the wrong move (e.g., a customer who is churning and inflating usage as a last resort).

Be specific. Avoid generic advice about 'monitoring health scores.'
Variables to fill in
  • {{PRODUCT_DESCRIPTION}}
  • {{PRICING_OR_EXPANSION_LEVERS}}
  • {{AVERAGE_CONTRACT_VALUE}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{PRODUCT_DESCRIPTION}}{{PRICING_OR_EXPANSION_LEVERS}}{{AVERAGE_CONTRACT_VALUE}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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