This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
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MarketMirror
Test ads, prices and pitches with simulated buyers
Rehearse marketing decisions before spending on a campaign. MarketMirror is an open-source toolkit for testing ads, prices, emails and pitches with AI-simulated buyers. Self-host it and use it with your AI agent. Validate findings with real customers.
Hey Product Hunt! I’m Ayush, the maker of MarketMirror.
MarketMirror gives founders and marketers a practice audience for decisions they would otherwise take straight into a paid campaign. Describe your product and audience, then compare ads, messages, prices, emails or a sales pitch with AI-simulated buyers. The dashboard shows their reactions, objections and what to test next.
This is an invented app with AI-simulated buyers; it lets you inspect the report without starting a new run.
It is self-hosted and licensed under AGPL-3.0. You can use it with Claude Code, Codex, Cursor, Gemini or another MCP-compatible agent, and inspect the saved results. AI provider usage or local computing resources may still cost money.
These buyers are simulated. Their responses help explore ideas; they do not establish how real customers will behave. Promising findings still need customer conversations and small live experiments.
MarketMirror builds on MiroFish and OASIS, with a workflow focused on marketing tests and decision reports.
I’d love feedback on the setup experience and the dashboard. Which decision would you test first: your ad, your price or your pitch?
About MarketMirror on Product Hunt
“Test ads, prices and pitches with simulated buyers”
MarketMirror was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #146 on the daily leaderboard. Rehearse marketing decisions before spending on a campaign. MarketMirror is an open-source toolkit for testing ads, prices, emails and pitches with AI-simulated buyers. Self-host it and use it with your AI agent. Validate findings with real customers.
On the analytics side, MarketMirror competes within Open Source, Marketing, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how MarketMirror performed against the three products that launched closest to it on the same day.
Who hunted MarketMirror?
MarketMirror was hunted by Ayush Niroula. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of MarketMirror including community comment highlights and product details, visit the product overview.
Ayush Niroula
Hey Product Hunt! I’m Ayush, the maker of MarketMirror.
MarketMirror gives founders and marketers a practice audience for decisions they would otherwise take straight into a paid campaign. Describe your product and audience, then compare ads, messages, prices, emails or a sales pitch with AI-simulated buyers. The dashboard shows their reactions, objections and what to test next.
Explore the saved demo before installing: https://darkworldcoder.github.io/market-mirror/demo/
This is an invented app with AI-simulated buyers; it lets you inspect the report without starting a new run.
It is self-hosted and licensed under AGPL-3.0. You can use it with Claude Code, Codex, Cursor, Gemini or another MCP-compatible agent, and inspect the saved results. AI provider usage or local computing resources may still cost money.
These buyers are simulated. Their responses help explore ideas; they do not establish how real customers will behave. Promising findings still need customer conversations and small live experiments.
MarketMirror builds on MiroFish and OASIS, with a workflow focused on marketing tests and decision reports.
I’d love feedback on the setup experience and the dashboard. Which decision would you test first: your ad, your price or your pitch?