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ChatGPT Brings Apps Into the Chat, Redefining Search Again

ChatGPT’s in-chat apps collapse the funnel into a message, and every brand now competes inside the conversation.
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By

Giovana B.

The familiar rhythm of opening new tabs to get something done is about to change. ChatGPT has begun allowing interactive apps to run directly inside a conversation, with early partners spanning travel, design, education, music, and real estate. Ask for a weekend in Lisbon, and Booking can appear in the thread with options you can refine in plain language. Request a social post, and Canva or Figma can spin up a working canvas without leaving the chat. Browse neighborhoods, and Zillow can surface listings, filters, and follow-ups in the same flow. Alongside these integrations, a new Apps SDK invites developers to bring their own capabilities into the interface millions already use.

The new feature signals a shift in distribution. If attention compresses into conversational surfaces, the first point of contact for many tasks will no longer be a search box or a home screen of icons, but a thread where results are rendered, adjusted, and confirmed in real-time. That reorders incentives for platforms and brands alike.

Chat Becomes The Front Door

For a decade, the consumer journey has pivoted around search, app stores, and social feeds, with marketers stitching together traffic, retargeting, and conversion across a patchwork of pages. In-chat apps remix that journey. Discovery, consideration, and action are all part of one dialogue. The assistant observes the user’s intent, proposes a relevant tool, and keeps the context intact as the user narrows their choices. Fewer hops mean fewer places to drop off, which typically lifts completion rates for templated tasks such as reservations, quotes, and creative production.

The strategic implication is blunt. If the conversation owns the start of the journey, brands must compete to be the app the assistant suggests. That means clearly defined capabilities, predictable inputs and outputs, and results that present beautifully inside a message stream.

From Answers To Actions

Furthermore, large language models began as powerful answer engines; combined with apps layered on top, they become orchestrators of outcomes. The difference is material, as answers satisfy curiosity; actions settle intent. In categories with structured supply and clear inventory, such as flights, hotels, cars, courses, playlists, and housing, this shift enables AI to serve as a transactional surface. The assistant does more than recommend a path; it walks the user down it, one prompt at a time.

For marketers, this collapses two persistent frictions. First, context loss between channels is reduced because the app executes where the conversation happens. Second, micro-iterations become trivial. Instead of bouncing between toolbars, a user can say, “Make it moodier” or “Expand budget by ten percent,” and the app responds in line. That fluidity encourages experimentation and often nudges users past the last mile of indecision.

The New Math Of Conversion

When the entire flow is contained in a single thread, attribution becomes both messy and powerful at once. Messy because last-click models struggle when there is no click, and traffic never touches a traditional landing page. Powerful because, with the right server-side events and consent, brands can measure the true arc of a session from intent through confirmation. Expect to see new performance surfaces emerge around conversation-native placements, whether through organic ranking based on utility and satisfaction or paid boosts that promote eligible apps for specific intents.

The economic models will follow. Affiliate and CPA structures are a natural starting point for these types of partnerships. Over time, marketplace dynamics, such as eligibility criteria, quality thresholds, user ratings, and even category caps, are likely to influence visibility. For early adopters, the lesson is to instrument everything: start, refine, preview, confirm, and hand off, with deep links for identity and payment when you must exit the thread.

Platform Risk In A Hosted World

Winning inside ChatGPT is not the same as winning on your own site. Distribution improves, but control diminishes. Brands trade some ownership of UI, data, and retargeting for a seat in the conversation. That creates classic platform risk. The antidote is design discipline. Expose small, high-value capabilities that travel well, generating a quote, checking order status, or assembling a pitch deck, while preserving off-ramps to owned channels for account management, complex checkout, or regulated disclosures. The key is to treat the chat surface like a shop-in-shop with its own visual grammar and performance rules.

Additionally, privacy and compliance will influence the rollout, particularly in regions with more stringent consent requirements. Product teams should plan graceful degradation for markets where in-chat apps are delayed or limited, using the assistant to prefill context before handing off to mobile web or native apps.

What to Build Now and The Road Ahead

The practical adoption of conversational apps begins with a clear mapping of priorities. Most organizations start by defining a handful of high-value actions that users perform most frequently, those with the highest intent and direct impact on revenue. Each of these “money tasks” must then be translated into structured capabilities with minimal input requirements, standardized output formats, and safeguards that ensure consistency with brand guidelines and policy. For the system to recognize and activate these tools effectively, their functions need to be described in precise, machine-readable terms within the ChatGPT framework.

Visual design also plays a decisive role. Interfaces that render outputs as dynamic cards, previews, or micro-controls increase clarity and encourage interaction within the conversation stream. Behind the scenes, telemetry must be configured to capture every stage of engagement, while respecting consent and privacy, to measure how efficiently the path from intent to completion unfolds. Many early prototypes are launched with a limited slice of inventory or services, allowing teams to learn from actual conversational patterns before scaling the model.

Although conversational apps will not supplant every channel or interface, they are expected to redirect a growing share of high-intent actions toward a more immediate, outcome-driven environment. In this model, success will favor companies that treat the chat interface as a genuine product channel rather than a marketing experiment, designing for speed, transparency, and reliability in a context where words replace buttons and the entire transaction can unfold in a single exchange.

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