ChatGPT App Opportunity Filter
Score app ideas by intent, native gaps, visual value, and platform fit.
- Difficulty
- Advanced
- Time to result
- ~weeks to results
- Steps
- 8
- Confidence
- 97%
The ChatGPT App Opportunity Filter evaluates an app idea against several linked criteria. It begins with a commercially valuable, high-intent request that users naturally express in conversation, such as getting a mortgage or planning a wedding. The proposed app must then provide something ChatGPT cannot adequately deliver by itself: proprietary data, a transaction, specialized workflow, or useful visual interface. The product should be designed chat-first, with its interaction and UI adapted to the conversational surface rather than copied from a website. Founders also assess monetization, approval dependence, technical limitations, competition, and the loss of direct control that comes with a curated ecosystem. Because building both web and chat versions can dilute early execution, the framework recommends selecting one primary surface until demand is established.
Origin
Greg Eisenberg introduced this framework on Marketing Against The Grain while discussing the emerging ChatGPT app ecosystem.
Core principles
- 01Target a high-value request users already express in chat.
- 02Solve work the host platform cannot complete natively.
- 03Use visual interfaces only where they improve the task.
- 04Design chat-first rather than transplanting a website.
- 05Balance early distribution against platform dependency.
- 06Focus on one surface before building parallel experiences.
How to run it
- 1
Find High-Intent Requests
List valuable tasks users explicitly ask ChatGPT to help complete.
Pro tip Use action-oriented phrases such as planning, buying, applying, comparing, or launching.
Watch out Broad informational queries may have little commercial value.
- 2
Measure Keyword Value
Estimate transaction value, urgency, frequency, and the economic benefit of becoming the surfaced app for that request.
Pro tip Compare the opportunity with the economics of owning a high-intent search term.
Watch out A large audience does not compensate for weak monetization or intent.
- 3
Identify the Native Gap
Specify the workflow, proprietary data, action, or expertise that ChatGPT cannot provide alone.
Pro tip Prefer gaps where the app completes a job rather than merely adding more text.
Watch out The platform may later absorb simple features.
- 4
Test Visual Necessity
Determine whether a custom visual interface materially improves selection, planning, comparison, or execution.
Pro tip Use UI for tasks that are cumbersome or ambiguous in plain conversation.
Watch out Do not add visual complexity merely to differentiate the app.
- 5
Design Chat-First
Build the flow around conversational intent, progressive clarification, and native platform behavior.
Pro tip Let chat collect context before revealing the specialized interface.
Watch out A compressed website experience may feel awkward inside ChatGPT.
- 6
Map Monetization
Choose whether payment, subscription, lead generation, or transaction completion occurs inside the app or through a deliberate handoff.
Pro tip Keep the transition consistent with the user's current task.
Watch out A premature external redirect can destroy the convenience that created the opportunity.
- 7
Score Platform Risk
Assess approval dependence, ranking control, technical constraints, data access, and the likelihood of platform competition.
Pro tip Compare the distribution upside with the autonomy of an open-web alternative.
Watch out OpenAI can control approval and discovery in ways no founder controls.
- 8
Choose One Primary Surface
Focus initial development on either the chat-native or standalone experience based on where the strongest advantage exists.
Pro tip Expand only after one version demonstrates demand.
Watch out Building both simultaneously can double complexity before product-market fit.
In the wild
The app targets the urgent request for help planning a funeral. Chat gathers requirements, while a visual interface compares services or plots and supports actions ChatGPT cannot complete natively. The founder evaluates monetization and OpenAI approval risk before choosing whether the chat experience or a standalone cemetery product should come first.
→ A broad idea becomes a platform-specific product hypothesis with explicit distribution and dependency trade-offs.
A developer learns the platform early, builds native apps for companies, and charges either a project fee or a recurring maintenance subscription. The service benefits from immediate business demand without requiring the developer to discover a consumer app winner first.
→ Platform expertise is monetized through a service portfolio.
Common mistakes
Wrapping a Website in Chat
A product that ignores conversational behavior fails to exploit the platform's distinctive interaction model.
Ignoring Platform Control
Approval, discovery, technical limits, and ranking remain controlled by OpenAI rather than the builder.
Building Both Surfaces at Once
Simultaneous web and chat development can split attention and create two incomplete experiences.
Is it for you?
Best for
Builders evaluating early app-store opportunities within ChatGPT or similar conversational platforms.
Not ideal for
Businesses requiring complete distribution autonomy or functionality that the platform cannot safely support.
From the transcript
“try to own a high value keyword, solve a specific high intent request that ChatGPT can't handle natively, and have a custom UI that's visual…”
“the apps that are going to crush it on ChatGPT are going to be chat first, very like focused on this experience and how do…”
“I would recommend someone just focus on either one or the other.”
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