Mazo vs ChatGPT for go-to-market strategy: what each is good for

How to get a good GTM strategy out of ChatGPT

ChatGPT and Claude can give you a solid go-to-market strategy. Most weak answers come from a weak brief: "How do I get customers for my SaaS?" gets you a generic list of channels. Give it the same facts a good advisor would ask for, make it question you before it plans, and make it argue with the plan before you commit to it.

1. Give it the context an advisor would ask for

• Product and what it replaces: what it does, and what customers use today instead (a spreadsheet, an agency, a competitor, nothing).
• ICP: company type and size, the buyer's role, and the event that makes them start looking.
• Price: what one customer pays you a year (your ACV) and how you charge.
• Stage: MRR and number of paying customers, even if both are zero.
• Channels tried, with numbers: "LinkedIn posts for 6 weeks, 2 demos" beats "LinkedIn didn't work".
• Constraints: hours a week you can spend on go-to-market, budget, and who else is on the team.
• The one decision you're trying to make right now.

Paste this in once and reuse it. In ChatGPT you can keep it in a project's instructions or files; in Claude, in a project's instructions or knowledge base. That way every new chat in the project starts with it and you don't have to paste it again.

2. Copy-paste prompts

You are a go-to-market advisor for early-stage B2B SaaS. Here is my situation:
- Product: [what it does, and what customers use instead today]
- ICP: [company type and size, buyer role, the event that makes them start looking]
- Price: [what one customer pays per year, and how I charge]
- Stage: [MRR, number of paying customers]
- Channels tried: [channel, what I did, result in numbers]
- Constraints: [hours a week for go-to-market, budget, team]

Before you recommend anything, ask me the questions you need answered to find the single biggest thing holding my growth back. Ask them one at a time. Don't give me a plan until I've answered.

Based on everything I've told you, give me a 90-day go-to-market plan for my stage. Maximum 6 moves, in order.

For each move: what I do this week, why it comes before the next move, and a pass/fail test with a number and a date ("if X happens by [date], move on; if not, change Y").

Then tell me what I should NOT do yet, and why.

Argue against this plan. Assume it has failed 90 days from now and give me the three most likely reasons, starting with the one I'll least want to hear.

For each reason, point to the specific number or assumption in what I told you that it rests on. Tell me which of my statements are evidence and which are guesses. Don't soften it, and don't end with reassurance.

3. Keep it honest week to week

• Ask for one move, not ten. "What's the one thing I should do this week?" is easier to act on than a list.
• Bring the result back. Next week, paste the numbers and ask: "Did this pass the test? What's the next move, and why?"
• Update your context when it changes. New MRR, a new price, a channel you've dropped. Otherwise the advice is built on last month's business.
• Watch for agreement. If every answer confirms what you already planned, run prompt 3 again.

Where general AI falls short for running go-to-market week to week

None of this is about intelligence. ChatGPT and Claude are general-purpose assistants, and the gaps below come from how they're used, not from what they know.

• It answers the question you asked, not the one you should have asked. Ask "should I add a free plan to get more signups?" and you get the pros and cons of free plans, when the real problem might be that trial users never come back.
• It tends to go along with your framing. Unless you ask it to argue, you mostly get your own plan back, better written.
• Context is your job. ChatGPT and Claude both have memory and projects, so set up well they can carry what you've told them across chats. But what they know is whatever you've told them, and nobody checks that your MRR, price and last month's results are current before the next answer.
• It doesn't hold you to what you committed to. A chat waits for you. Unless you set up a reminder yourself, nothing comes back in a week to ask whether the cold emails got replies.
• No stage model or pass/fail tests unless you ask for them. The advice can be good in general but wrong for your stage, like running three channels before you have ten paying customers, and it rarely comes with a number that tells you whether it worked.

You can work around every one of these with the prompts above and some discipline. A dedicated advisor builds that discipline in.

What that looks like in Mazo

Mazo is an AI go-to-market advisor for B2B SaaS founders, €0–€1M ARR. It builds your go-to-market plan from where you are today, then runs it with you every week.

• It asks before it advises. One focused question at a time until it knows your product, buyer, stage and what's stuck, and it doesn't re-ask what it already knows.
• It pushes back. When your assumption is wrong, it says so, like "signups aren't your problem, activation is".
• It remembers your founder facts. Your ICP, ACV, MRR, channels tried and constraints are saved to your account and used in every session.
• It follows up. Moves that need a real-world test get a metric, a threshold and a check-in date, and Mazo emails you when the test is due. A new session opens by asking whether you did what you committed to last time.
• It keeps you on one move. A 90-day plan of six to eight moves for your stage, each with why it's next and the framework behind it. Mark one done and the next comes up.

Mazo vs ChatGPT or Claude, side by side

Or use both

They aren't exclusive. Use ChatGPT or Claude for drafting and research, and Mazo for the plan and the weekly calls on what to do next.

Weighing up other kinds of help? Read fractional CMO vs Mazo, or start with our go-to-market strategy guide for B2B SaaS, from €0 to €1M ARR.

Who wrote this

Madalena Rugeroni built Mazo. She's an ex-Googler, a startup advisor and investor, and runs a portfolio of internet companies. Before that, as Head of Growth at Amplemarket, she scaled a B2B SaaS to $10M ARR. LinkedIn

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