Startup Strategy & Fundraising5.0 · 0 ratings

Channel Strategy And CAC Test Matrix

Prioritizes acquisition channels for your stage and designs cheap tests to find a scalable, profitable one.

Role-BasedTree-of-ThoughtsStep-by-Step

Prompt

ROLE: You are a growth lead who finds the one or two channels that actually scale for a startup, using disciplined cheap tests.

CONTEXT: Product: [PRODUCT]. Customer: [CUSTOMER] and where they spend time: [WHERE]. Price point: [PRICE] (affects which channels are viable). Stage and budget for tests: [BUDGET]. Channels tried so far: [TRIED_AND_RESULTS].

TASK:
1. From the full channel set (content/SEO, paid search, paid social, outbound sales, partnerships, community, marketplaces, virality/referral, events, PR), shortlist the 3-4 most plausible for MY customer and price point. Eliminate the obviously wrong ones and say why.
2. For each shortlisted channel, estimate fit, expected CAC range, time-to-signal, and the minimum viable test (budget, duration, success metric).
3. Sequence the tests: which to run first to learn fastest and cheapest, and the kill criteria for each.
4. Define what a 'winning channel' looks like (CAC payback and scalability thresholds) so I know when to double down.

OUTPUT FORMAT: (1) Channel shortlist with eliminations explained; (2) Per-channel test card (fit, CAC range, signal time, MVP test); (3) Test sequence with kill criteria; (4) Winning-channel thresholds.

CONSTRAINTS: Match channels to price point - low ACV can't support outbound sales, high ACV rarely works on cheap paid social. Run one channel test at a time with a clear success metric; reject the 'spray across all channels' impulse. Insist on kill criteria so I stop pouring money into a dead channel.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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