How to market your app using AI
To market your app using AI, give it real customer evidence, choose one audience and one offer, produce a campaign you can publish, then use the response to improve the next campaign. Track whether people complete a useful action in your app. More generated posts alone do not tell you whether your marketing works.
This guide is for vibe coders and solo software founders with a working product. It includes a copyable brief and a seven-day execution plan. The example is illustrative; it is not a customer case study or a promise of users.
1. Find the problem people already describe
Start with five relevant conversations: support messages, interviews or public discussions where your intended customer describes a problem. Save the source link and a short observation. Do not feed private customer information into a tool without permission. Ask AI to group the problems and distinguish direct observations from guesses.
For example, imagine an expense app for freelance designers. “Everyone needs expense tracking” is too broad. A testable audience is freelance designers who collect receipts across email and photos before sending monthly expenses to an accountant. Confirm that pain with real people before writing the campaign.
AI can summarize the material you provide and suggest search phrases such as “organize freelance receipts” or “send expenses to accountant.” These are hypotheses until you check actual conversations, search results or your own search data. A language model's estimated search volume is not evidence.
2. Turn product context into an execution brief
Use this prompt in your chosen AI tool. Fill the brackets and attach your observations. Ask for deliverables you can use this week, rather than a long list of channels.
Help me run one app marketing experiment. Product and current availability: [working features, limits, price] Audience and problem: [one segment, one problem] Evidence: [source links and observations] Proof I can show: [a real screenshot or demonstration] Destination and action: [URL, action] Activation: [the first useful task completed in the app] Channel and permission: [one place, its rules, what I can publish] Time and spending limit: [my actual limits] Produce: one offer, a 30-second demo outline, one channel-specific post, a tagged destination link, and a seven-day action checklist. Separate facts from assumptions. Do not invent users, results or features. List what needs my approval before it is published. After I supply outcomes, propose one change for the next experiment.
3. Ship one campaign over seven days
| Day | Action | Finished evidence |
|---|---|---|
| 1–2 | Read five relevant conversations and choose one audience. | Source links, customer words and one problem statement. |
| 3 | Record a real product demonstration and draft one offer. | A short demo and a page showing the same promise. |
| 4 | Review the AI draft for accuracy, then publish where participation is allowed. | The approved post URL and destination link. |
| 5–6 | Reply to relevant questions and watch the first product sessions. | Questions, objections and setup friction. |
| 7 | Record outcomes and choose one change. | Raw counts, observations and next week's brief. |
For the expense-app example, the offer could be “See how to turn a folder of receipt photos into an accountant-ready export.” Show that exact working task in the demo. Ask people who experience the problem whether the export fits their workflow. Follow community rules and disclose that you built the app.
4. Measure visits, signups and useful product use separately
For a web landing page, tag campaign links with a source, medium and campaign. For example: https://example.com/?utm_source=founder_demo&utm_medium=community&utm_campaign=receipt_export. These are illustrative values. Google's campaign URL documentation explains how those parameters appear in Analytics acquisition reports.
Confirm your analytics receives the tags before publishing. Then record visits, signups and completed receipt exports separately. A tagged visit does not prove a signup or an activated user. For a native app, track the store visit, installation and the first completed app task using the attribution and event measurement your app actually supports.
5. Give the results back to AI
Paste the raw counts, customer questions and what shipped into your brief. If people view the demo but do not click, investigate whether the offer matters to that audience. If they sign up but never export, inspect onboarding with them. If they complete the task and return, repeat the experiment with another relevant group before increasing spend.
Ask AI to name the evidence behind each suggested change and what remains uncertain. With small samples, treat the answer as a next test, not a statistically reliable conclusion.
Where an AI marketing co-founder fits
Crany.ai is an AI marketing co-founder in development for vibe coders: it strategizes, executes your marketing with your approval, and improves based on results while you keep building. Execution is central to the planned product. Public access, launch date and pricing have not been announced.
You can follow this workflow today with available tools. Compare AI marketing tools for app founders, use the SaaS marketing plan worksheet, or join Crany's free waitlist.
Related guides
- How to market your app: a step-by-step plan for solo founders, before and after launch, with or without a budget.
- How to promote your app on Reddit: find threads that ask for what you built and reply without getting banned.
- Founder-led content for app founders: turn your day into a video script to shoot and a post that pulls replies.
- AI marketing agents: can AI do your marketing?: what AI can run on its own today, what still needs you, and how to judge a tool.