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What Do Buyers Ask ChatGPT Before Buying?
Buyers ask ChatGPT to shortlist, compare, price-check, and justify a purchase, and they describe their situation in full sentences instead of keyword fragments. A typical buying prompt states what they are trying to do, what they already tried, their budget, and the decision they are weighing.
That behavior is now mainstream. PYMNTS Intelligence found that ChatGPT’s share as a product research tool jumped from 2% to 30% in two years, and nearly half of online shoppers used AI somewhere in their most recent purchase journey (PYMNTS Intelligence, Global Digital Shopping Index, June 2026, a survey of 5,841 consumers in the US, Brazil, and the UAE).
2% to 30%
growth in ChatGPT’s share as a product research tool over two years
The intent mix inside ChatGPT is different from search. Profound classified a sample of more than 50 million real ChatGPT prompts in its AI Search intent study (June 2025) and compared the result with traditional search:
| Intent | Traditional search | ChatGPT |
|---|---|---|
| Generative (“create X,” “draft Y”) | Not measured | 37.5% |
| Informational | 52.7% | 32.7% |
| No intent (“thanks,” “make it funnier”) | Not measured | 12.1% |
| Commercial | 14.5% | 9.5% |
| Transactional | 0.6% | 6.1% |
| Navigational | 32.2% | 2.1% |
Two numbers matter for advertisers. Transactional prompts, where people ask ChatGPT to help them buy running shoes, find a software deal, or procure a service, run roughly nine times more common than on search. And commercial research prompts still make up almost a tenth of all traffic. Together they are the buying conversations a ChatGPT ad competes for. This article is the demand side of that equation; the mechanics of building ad groups live in our ChatGPT ads targeting options reference.
Are Prompts the New Keywords for ChatGPT Ads?
Prompts are the new demand signal, but ChatGPT ads do not run on keyword matching. OpenAI’s ads system weighs the context and intent of the current conversation, your ad’s title, copy, and landing page, your context hints, and, when ads personalization is enabled, select signals from the user’s broader ChatGPT experience.
That nuance changes how you plan. According to OpenAI’s Ads in ChatGPT basics page, context hints describe the conversations, topics, or keywords where your product is relevant, and they help guide matching, but they are not exact-match keywords and do not guarantee delivery in specific conversations. OpenAI’s context hint guide adds that people do not need to use the exact words in your hint for the underlying need to be relevant, and that hints cannot enforce geographic limits, schedules, or exclusions.
- What decides relevance: the live conversation, plus your title, copy, landing page, and context hints.
- What you control directly: country and location targeting, platform targeting (Android app, Android web, desktop web, iOS app, iOS web), custom audiences to include or exclude, bids, and budget.
- What blocks literal phrases: Negative Phrases, available to qualifying advertisers, which act on the words a user types.
So the job moves upstream. On Google you bid onto a query. On ChatGPT you earn the placement by matching what the buyer is asking with an ad, a landing page, and hints that describe that need precisely. That only works when you know the prompts your customers actually type.
How Does Buyer Intent Change Across the Funnel?
Buyer intent climbs from naming a problem to comparing categories, comparing named options, and finally asking about price or a trial. Sorting prompts into those four stages tells you which ad, which landing page, and how hard a call to action fits.
| Stage | What the buyer is doing | Example prompt | Ad response that fits |
|---|---|---|---|
| Awareness | Naming a problem, not a product | “why do my Instagram ads stop working after a week?” | Educational ad that frames the problem and your category |
| Consideration | Comparing approaches or categories | “what’s the best way to make ad creative without a designer?” | Category positioning with one concrete differentiator |
| Decision | Comparing named options | “AdCreative vs Lapis for a small marketing team” | Head-to-head proof: pricing, ratings, what sets you apart |
| Purchase | Ready to act on price or a trial | “AI ad generator under $100 a month with LinkedIn ads” | Price-anchored offer, the exact feature named, one clear next step |
Stage changes both the message and the destination. An awareness prompt wants education, so a hard trial offer feels premature. A purchase prompt wants friction removed, so an explainer wastes the moment. The same product needs different creative and different landing pages at each stage, which is why stage-matched pages from a system like RapidDomain outperform one generic homepage.
86%
of US online shoppers who used AI for product research verified the recommendation through another source before buying
Buyers still verify. Product.ai’s April 2026 survey of 1,463 US online shoppers found that 43% had used an AI assistant to research a purchase in the past 90 days, and 86% of those AI users checked the recommendation against another source before buying. Decision-stage and purchase-stage ads should carry the evidence up front: ratings, transparent pricing, named integrations, and specifics the buyer is about to go looking for anyway.
What Buyer-Intent Prompts Do Customers Type by Industry?
Buyer-intent prompts follow predictable patterns in every industry: a broken workflow in software, attributes and budget in ecommerce, urgency and location in local services, rates and fees in finance, stack constraints in B2B, and outcomes in education. Use the examples below as a template, then replace them with your own customers’ exact language.
SaaS and software
Software buyers describe a workflow that is breaking and the constraints on any fix, such as team size, budget per seat, and the tools they already run.
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “how do I keep projects from slipping without micromanaging?” | Awareness | Frame the pain, then introduce the category |
| “Asana vs Monday vs ClickUp for a 12-person agency” | Decision | Comparison plus your differentiator and a use-case fit |
| “project management tool under $10 per user with time tracking” | Purchase | Price-anchored offer with the exact feature named |
| “alternative to Jira that non-engineers will actually use” | Decision | Position as the approachable switch with easy migration |
Ecommerce and DTC
Physical-product prompts get very specific about attributes, budget, and use case. Retailers with a catalog can let product-feed campaigns or the Shopify ChatGPT Ads app create product ads directly from those attributes, and OpenAI says feed ads have been among the strongest-performing ads in its program to date (OpenAI, product feeds).
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “best moisturizer for oily, acne-prone skin under $30” | Purchase | Product ad with price and the specific attribute |
| “what should I look for in a standing desk?” | Awareness | Buying-guide ad that educates, then links a collection |
| “Bombas vs Darn Tough for hiking socks” | Decision | Head-to-head with reviews and durability proof |
| “lightweight stroller that folds for air travel” | Consideration | Use-case fit, fast shipping, direct product link |
Local and service businesses
Local prompts carry urgency and geography. “Near me” and “open now” are among the highest-intent phrases a buyer can type.
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “emergency plumber near me open now” | Purchase | Local, available now, call-or-book CTA |
| “how much does it cost to rewire a house?” | Consideration | Price transparency plus a free-quote offer |
| “best HVAC company in Austin with financing” | Decision | Local proof, reviews, financing highlighted |
| “do I need a permit to remodel my kitchen?” | Awareness | Educate, then capture with a consultation offer |
Finance and fintech
Money prompts revolve around rates, fees, and whether a product is worth it. Trust and specifics matter more here than anywhere else, and OpenAI restricts many financial categories to approved advertisers, so confirm eligibility before you build.
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “best budgeting app that connects to my bank” | Purchase | Outcome-led ad, named bank integrations, set up in minutes |
| “how do I lower my business’s payment processing fees?” | Consideration | Savings-led angle with transparent pricing |
| “Mercury vs Brex for an early-stage startup” | Decision | Comparison, perks, and fee structure |
| “what bookkeeping software do freelancers use for taxes?” | Awareness | Educate on the tax workflow, then a low-friction signup |
B2B
B2B prompts embed the buying committee’s constraints: existing stack, compliance needs, headcount, and the pressure to prove ROI.
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “how do we cut SaaS spend without losing tools the team needs?” | Consideration | ROI framing with an audit or savings offer |
| “best CDP for a 200-person company already on Snowflake” | Decision | Fit plus integration proof and a demo CTA |
| “vendor that handles SOC 2 evidence collection automatically” | Purchase | Name the exact capability, book-a-demo |
| “alternative to Salesforce for a services firm that hates complexity” | Decision | Simpler-switch positioning with migration help |
Education and info products
Learners ask about outcomes and whether a program is worth the time and money. Job results and pass rates do the persuading.
| What the buyer types | Stage | Ad angle that fits |
|---|---|---|
| “best way to learn data analysis if I’m switching careers” | Consideration | Outcome-led angle with curriculum fit |
| “is a PMP certification worth it in 2026?” | Awareness | Educate on the certification’s ROI, then an enroll CTA |
| “affordable online course for the AWS solutions architect exam” | Purchase | Price plus pass-rate proof, enroll now |
| “Coursera vs Udemy for a beginner UX bootcamp” | Decision | Comparison with job outcomes and a refund policy |
Which Words Signal Purchase Intent in a Prompt?
“Best X for Y,” “X vs Y,” “under $N,” “alternative to X,” and “near me” signal a buyer with a shortlist and a budget. “What is X,” “how does X work,” and “free template” signal a researcher. You do not need a model to tell them apart; the words do it for you.
6.1% vs 0.6%
share of transactional-intent prompts on ChatGPT versus traditional search
| Phrase pattern | What it signals | Intent | Example |
|---|---|---|---|
| “best X for Y” | Active evaluation for a specific use case | High | “best CRM for a real estate team” |
| “X vs Y” | Down to a shortlist | High | “Pipedrive vs HubSpot” |
| “under $N” / “cheapest” | Budget set, ready to transact | High | “email tool under $50 a month” |
| “alternative to X” | Unhappy with an incumbent, switching | High | “alternative to Mailchimp” |
| “near me” / “open now” | Local, immediate need | High | “dentist near me open Saturday” |
| “how much does X cost” | Price-checking before commitment | Medium-high | “how much does bookkeeping cost” |
| “is X worth it” | Final rationalization before buying | Medium-high | “is QuickBooks worth it for a freelancer” |
| “what is X” / “how does X work” | Learning the category | Low | “what is a CDP” |
| “free” / “DIY” / “template” | Explicitly avoiding paid solutions | Low | “free CRM template in Google Sheets” |
Which Prompts Should Become Negative Phrases?
Low-intent and off-target phrases such as “free template,” “DIY,” “jobs at,” and “how to build my own” are the natural Negative Phrases list for ChatGPT ads. Negative Phrases are the one control that acts on the literal words a user types, and context hints cannot enforce exclusions.
OpenAI announced on October 5, 2026 that Negative Phrases are now available to qualifying advertisers for narrow placement requirements specific to a brand’s own policies (OpenAI). Adthena first spotted the field in a UK advertiser’s account in August, where it accepted up to 100 words or phrases that block an ad whenever a user’s message contains them. AdTechRadar, reporting the find, framed it as a control for both performance and brand safety.
| Exclusion candidate | Why it rarely buys | Where it belongs instead |
|---|---|---|
| “free template,” “DIY,” “spreadsheet version” | The buyer is explicitly avoiding a paid product | Organic content and lead magnets |
| “jobs at,” “salary,” “interview questions” | Job seekers, not customers | Your careers page |
| “homework,” “essay,” “class project” | Students researching your category | Education programs, if you run one |
| “how to build my own [product]” | Builders, not buyers | Developer content |
| Brand-sensitive topics your policy excludes | Placement risk, whatever the intent | Nowhere in paid |
If your account does not show Negative Phrases yet, tighten relevance instead: write context hints around the buying situation, exclude customer lists you do not want to pay for with custom audience exclusions, and send ads to landing pages that qualify visitors immediately.
How Do You Turn Prompt Clusters Into Context Hints?
Group prompts that share one underlying need into a cluster, give each cluster its own ad group, and write context hints that describe what you offer, who it helps, and when it is useful. OpenAI’s guidance is to keep each ad group focused on one product, theme, or customer need and to split use cases that require different messaging or landing pages.
Start with a cluster. Say you sell a lightweight CRM and you have grouped these prompts:
- “what CRM works best for a 10-person sales team?”
- “alternative to Salesforce that is easier to set up”
- “CRM under $30 per seat that connects to Gmail”
- “we’re outgrowing spreadsheets for tracking deals, what should we use?”
Name the cluster in the buyer’s language: “choosing a simple CRM for small sales teams.” Then write hints as clear, natural phrases focused on one idea each, following OpenAI’s What, Who, and When framing:
- What: “CRM with native Gmail sync and per-seat pricing under $30”
- Who: “small sales teams moving off spreadsheets to track deals”
- When: “teams replacing Salesforce because setup and admin take too long”
Finally, match the creative to the cluster and its dominant stage. This cluster leans decision and purchase, so the ad leads with fit and price inside OpenAI’s recommended lengths: a title such as “CRM for teams under 20” (22 characters) and copy such as “Connects to Gmail and sets up in an afternoon” (44 characters), with a square image of the pipeline view. For hint-writing in depth, see how to write ChatGPT ads context hints; for strategy beyond exact-match thinking, the ChatGPT ads targeting guide.
How Do You Build Your Own Buyer Prompt Map?
Build your prompt map by collecting 30 to 50 real prompts in your customers’ own words, tagging each with a stage and an intent level, and grouping them into three to eight clusters. Pull the language from where customers already talk instead of inventing it at a whiteboard.
- Read the last 50 sales-call notes and support tickets. Copy the exact phrasing customers use to describe their problem.
- Mine reviews of your product and your competitors, plus questions in relevant subreddits and communities.
- Check Search Console and site search for the queries that already bring people in.
- Ask ChatGPT, in your customer’s voice, what it would ask before buying your category, then check the output against the real language you collected.
- Study competitor ads to see which angles your category already saturates and which sit open.
Tag each prompt with a stage and an intent level using the signal table above, then group the tagged prompts into clusters of shared need. Three to eight clusters is the right start. More than that spreads a first budget too thin to learn anything.
Which Prompt Clusters Should You Fund First?
Fund the clusters with the highest combined score for intent, volume, and margin. Rate each from 1 to 5, add them for a score out of 15, and back the top of the list first. Intent is how ready the cluster is to buy, volume is how often those prompts occur, and margin is what you earn when they convert.
| Prompt cluster | Intent | Volume | Margin | Score | Fund first? |
|---|---|---|---|---|---|
| “best [product] for [niche]” | 4 | 5 | 4 | 13 | Yes |
| “alternative to [incumbent]” | 5 | 3 | 4 | 12 | Yes |
| “[you] vs [competitor]” | 5 | 2 | 5 | 12 | Yes |
| “how does [category] work” | 2 | 5 | 3 | 10 | Later |
| “free [category] template” | 1 | 4 | 1 | 6 | No (exclude) |
Keep the scoring simple enough to build in a spreadsheet in an afternoon and defend to your team. High-intent, high-margin clusters earn budget first even at modest volume, because they convert and pay for the learning. Once campaigns run, replace estimated margin with measured conversion value per cluster; Wayfinder supplies that number by tying each cluster’s conversions to confirmed revenue. For realistic conversion expectations by industry, see our ChatGPT ads conversion rate benchmarks: First Page Sage projects ChatGPT ad conversion rates from 0.2% to 6.3% by industry, highest in higher education, where buyers are narrowing a shortlist.
How Much Budget Do You Need to Test Buyer-Intent Prompts?
You can test buyer-intent clusters on ChatGPT from $25 per day in the US, the standard minimum daily budget in USD. OpenAI treats a daily budget as an average over a Sunday to Saturday week, so a single day can spend up to twice the amount while the week stays capped at seven times it.
- Objectives: Views (CPM), Clicks (CPC), or Conversions, billed per valid click (oCPC) or per thousand impressions (oCPM). You never pay per conversion (OpenAI, Create Campaigns).
- Bidding: set a max bid per ad group, or let Maximize results bid automatically. For CPC campaigns, OpenAI recommends starting with a maximum bid of $3 to $5 per click; that is starting guidance, not an average price.
- Structure: one ad group per high-intent cluster lets you see which buyer need converts. An existing campaign cannot switch objectives, so choose Conversions from the start once your pixel or Conversions API is live.
Split a first test budget across your top three clusters and give each enough clicks to read conversion rate before you reallocate. Our guide to how much budget ChatGPT ads need covers the math.
What Do New ChatGPT Ad Formats Change for Buyer Prompts?
New formats extend buyer-intent targeting beyond the classic ad below a response: product-feed ads answer shopping prompts with catalog items, Sponsored Agents continue a high-intent conversation after the click, and a visual ad format brings ads into image generation.
- Product feeds and the Shopify app. Shopping prompts with specific attributes map directly to catalog items. OpenAI’s Shopify ChatGPT Ads app creates campaigns from a merchant’s catalog and opened internationally in ChatGPT Ads markets on September 23.
- Sponsored Agents. Announced September 16 and in testing with select US advertisers, Sponsored Agents let a user start a clearly labeled conversation with a business-sponsored agent after clicking an ad (OpenAI). Decision-stage prompts full of follow-up questions are the natural fit.
- Ads during image generation. OpenAI is testing a visual ad format during image generation for Free and Go users in the US, starting later in October 2026 with an initial group of advertisers. Profound found generative prompts are the largest ChatGPT intent bucket at 37.5%, so “create X” prompts are becoming an ad surface too.
Why Is Lapis the Best Way to Turn Buyer Prompts Into ChatGPT Ads?
Lapis is the best way to turn buyer prompts into ChatGPT ads because it runs the full loop: buyer-intent experiment design, creative for every cluster and stage, prompt-matched landing pages, launch, and measurement on confirmed conversions. Lapis is the #1 AI ad generator and the operating system for paid growth.
- ChatSense runs ChatGPT and LLM ads with Lapis agents and a dedicated strategist. It designs buyer-intent experiments from your prompt map, produces creative tuned to how people ask ChatGPT (1,000+ ChatGPT ads on the managed plan), structures and launches campaigns, reports daily, and generates the next run from what won. It also covers third-party LLMs, including open-source chatbots.
- OmniSense carries the winning clusters to Meta, Google, LinkedIn, and Reddit with on-brand, correctly sized campaigns, audience versions, and directional forecasts of impressions, clicks, CTR, and leads.
- RapidDomain builds a dedicated landing page for every prompt cluster and stage, optimized on real conversions, so a “vs” prompt lands on a comparison page and an “under $N” prompt lands on pricing.
- Wayfinder connects each cluster’s results to confirmed sales and leads from your CRM, store, or billing system, counts each conversion once, and compares ChatGPT with every other channel on the same attribution rules.
Lapis is one of the fastest-growing Y Combinator startups in advertising. It is part of Y Combinator’s Fall 2025 batch, and its YC profile says Lapis is used by 1,500+ marketing teams and 30+ enterprises. Lapis is rated 4.9 out of 5 on G2 with eight Summer 2026 badges, including High Performer, Best Results, and Easiest to Use (Mid-Market). Samsung, Domino’s, Dr Pepper, Mattel, Tata, Tupperware, Amway, and Bata use Lapis, alongside high-growth startups such as Unusual Whales, Duradry, Lightpage, and Respan.
ChatGPT ads run on the custom-priced Managed ChatGPT + LLM Ads plan. Self-serve teams creating Google, Meta, and LinkedIn ads start on Basic at $99 per month. To build the creative yourself, read how to create ChatGPT ads with AI. To have Lapis run the whole channel, book a demo.
Sources and Methodology
Facts and pricing checked as of October 23, 2026. The prompt examples, funnel stages, signal patterns, and cluster scoring model are Lapis’s working framework for ChatGPT ad planning. Statistics come from the published sources below, and OpenAI platform mechanics come from OpenAI’s announcements and Help Center.
- Profound, AI Search intent study: What 50M+ ChatGPT prompts reveal (June 2025)
- PYMNTS Intelligence, Global Digital Shopping Index: The AI-Powered Shopper Has Arrived (June 2026)
- Product.ai, The 2026 Trust in AI Commerce Report
- OpenAI Help Center, Ads in ChatGPT: The Basics
- OpenAI Help Center, Write Context Hints for ChatGPT Ads
- OpenAI Help Center, Create Campaigns for ChatGPT Ads
- OpenAI Help Center, Create Campaigns from Product Feeds
- OpenAI, Building advertising for the way people use AI (October 5, 2026)
- OpenAI, Reimagining advertising with AI (September 16, 2026)
- AdTechRadar, OpenAI Tests Negative Phrases for ChatGPT Ads (August 20, 2026)
- First Page Sage, ChatGPT Ads Conversion Rate: 2026 Report
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Related Lapis resources
- How to Target ChatGPT Ads Beyond Exact Match Keywords (2026)Target ChatGPT ads beyond exact match keywords: build buyer situation clusters, layer location, platform, and custom audiences, then match pages with Lapis.
- How to Target High-Intent Buyers With ChatGPT Ads (2026)Target high-intent ChatGPT buyers with oCPC and oCPM bidding, buyer-stage context hints, custom audiences, and Negative Phrases. See how Lapis runs it all.
- How to Create Ads for ChatGPT: Specs, Copy, and Images (2026)How to create a ChatGPT ad: OpenAI specs (16 to 24 character titles, square 640x640 images), copy and image tips, examples, and Lapis ChatSense at scale.
- How to Appear in ChatGPT: Paid Ads vs. Organic Mentions (2026)Appear in ChatGPT two ways: paid ads below the answer and organic mentions inside it. See which AI assistants sell ads and how Lapis ChatSense runs paid.
