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AI Marketing30 August 20267 min read

How to Set Up ChatGPT Ads: A Step-by-Step Guide for Indian Businesses

From your first list of target queries to a live campaign — here's exactly how to set up ChatGPT Ads in India, whether you're going through an agency partner now or waiting for self-serve on September 4.

By The Vardhan AI Team, Vardhan AI

A real ChatGPT conversation: a founder asks for a CRM recommendation for their 15-person Bangalore startup, and ChatGPT responds with a comparison table

This is the kind of query your setup process needs to be built around.

Setting up ChatGPT Ads is a four-step process: identify the exact questions your buyers ask, write copy that sounds like a recommendation rather than an ad, build a landing page matched to each question, and launch. Right now, launching means going through an agency partner (WPP or Omnicom); from September 4, 2026, it also means the self-serve ChatGPT Ads Manager. Either way, the first three steps are identical — and they're the ones worth doing properly before you spend anything.

Step 1: Query Research

Identify 30-50 real questions your ideal customers ask — not keywords, actual natural-language questions like "best CRM for a 15-person startup in India" or "cheapest term insurance for a 30-year-old non-smoker." Pull these from sales call transcripts, support tickets, and your existing SEO keyword data; the goal is questions with a specific, comparison-driven shape, since that's exactly where a sponsored recommendation gets shown.

A real ChatGPT conversation showing a founder asking a specific, constraint-based question and getting a detailed comparison answer
Specific, constraint-based questions like this one are the target — not generic category searches.

Step 2: Write Ad Copy That Sounds Like a Recommendation

This isn't Google Ads. Keyword-stuffed, benefit-bullet copy stands out as an ad and gets ignored or distrusted. Write the way ChatGPT itself would recommend something — specific, matched to the stated constraint (budget, team size, location), and honest about tradeoffs rather than purely promotional.

Step 3: Build a Landing Page for Each Query Cluster

Send clicks to a page that matches the specific question, not your generic homepage. Add UTM parameters per query cluster so you can see which questions actually convert. Someone who asked about "CRM under ₹2,000/user/month with WhatsApp integration" should land on a page that speaks directly to that, not a broad "About Our CRM" page.

Step 4: Launch the Campaign

  • Right now: launch through an agency partner — WPP or Omnicom are OpenAI's first partners in India
  • From September 4, 2026: launch directly through the self-serve ChatGPT Ads Manager
  • Either path uses the same query research, copy, and landing pages from Steps 1-3

What to Track After Launch

Track clicks and conversions by query cluster, not just in aggregate — some questions will convert far better than others. Keep in mind that OpenAI doesn't share personal user data with advertisers, so your reporting will be aggregated performance data (views, clicks), not individual-level targeting insight; our breakdown of what data OpenAI actually shares covers exactly what to expect in your reporting dashboard.

Want your query research, ad copy, and landing pages ready before September 4? Talk to an AI Strategist and get your ChatGPT Ads setup done →

[ FAQ ]Frequently asked

Frequently asked.

Not directly through self-serve yet — that opens September 4, 2026. Right now, access in India runs through agency partners WPP and Omnicom.

30-50 real, specific, comparison-driven questions your ideal customers actually ask — pulled from sales calls, support tickets, and existing keyword research, not guessed keywords.

Not one-to-one, but pages should be grouped by query cluster — a page matched to the specific question and constraint (budget, use case, location) converts meaningfully better than sending every click to a generic homepage.

Google ad copy is written to stand out and match a keyword. ChatGPT ad copy needs to sound like a natural recommendation embedded in a conversation — specific, honest about tradeoffs, and free of keyword-stuffing.

Aggregated, non-identifying performance data like views and clicks. OpenAI does not share individual chat content, history, or personal details with advertisers, so reporting is less granular than Meta or Google's behavioral data.

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