We manage ChatGPT Ads end to end: strategy, campaign objectives, ad groups, context hints, creative, budgets, landing pages, measurement and reporting. The account and data remain under the client’s control; our role is to turn a new ad channel into an acquisition system that can be measured, corrected and scaled.
ChatGPT Ads has its own mechanics. Good management means coordinating objective, budget, structure, context, creative, destination and measurement without forcing the channel into a Google Ads template. Platform capabilities below are checked against current OpenAI documentation; strategy, testing discipline and scale/stop criteria are our operating methodology.
We begin with the commercial objective and translate it into Ads Manager structure. OpenAI currently documents CPM for reach, CPC for clicks and oCPC for post-click conversion optimisation. In addition, oCPM is in beta and extends conversion optimisation to impression billing; OpenAI says access is expanding.
Each campaign brings together one objective, budget, dates and markets. Within it, we separate ad groups when the product, need, intent or message changes. We avoid combining incompatible signals simply to keep the account smaller.
Primary sources: Create Campaigns for ChatGPT Ads · Conversion-optimized Campaigns.
Ad groups organise coherent themes and carry the context hints. OpenAI uses those hints to provide additional context about what the product offers, who it helps and the situations in which it may be useful.
We build them from buyer problems, use cases, needs and natural language. They are not exact-match keywords, audience-targeting rules or guarantees of delivery in a particular conversation. Coverage and specificity are therefore treated as hypotheses, then evaluated against delivery and outcomes.
Primary source: Create Ad Groups for ChatGPT Ads · OpenAI Help Center.
Managing ChatGPT Ads means testing headlines, descriptions, imagery and value propositions that are genuinely different enough to teach us something. Ten cosmetic variations of the same message are not a testing strategy.
The destination is part of the hypothesis. If the ad addresses a specific need, the landing page should continue that conversation with message match, proof, speed, clear action and appropriate forms. When the bottleneck sits after the click, we fix the experience before increasing spend.
Optimisation depends on the objective and the quality of the available signal. We read delivery, impressions, clicks, spend, CTR, average CPC, average CPM and conversions, but we do not automatically optimise towards the cheapest intermediate metric.
Where fixed bidding applies, Ads Manager uses maximum bids at ad-group level and a relevance-weighted, second-price auction. Separately, the daily budget is now an average over a seven-day period: a campaign can spend up to 2× the selected daily amount on an individual day, while billed media spend across the applicable seven-day period should not exceed 7× that budget. Pacing and alerts therefore need to be read across the full window rather than treating the daily number as a hard cap.
Every meaningful change has an explicit hypothesis: budget, bid, structure, context hints, creative, landing page or conversion event. We avoid moving too many variables at once so the learning remains interpretable.
Primary sources: Daily Budgets · Ads in ChatGPT: The Basics.
Where appropriate, we implement OpenAI Pixel, Conversions API, UTMs and business events. The oppref click reference can be preserved through to conversion and, when Pixel and CAPI send the same event, we use the same event ID to support deduplication. In ecommerce we follow purchase and revenue; in B2B we try to connect activity through to qualified lead, opportunity and revenue when the CRM allows it.
The client retains ownership of the account, billing and data. We document decisions, changes and results so the account history remains a transferable asset rather than an agency black box. If the channel fails to show defensible economics, stopping or redesigning the pilot is a valid management decision.
Primary source for measurement: Conversion Measurement · OpenAI Help Center.
A purchase, a demo request and a long-cycle commercial opportunity should not be optimised in the same way. The campaign needs a signal that reflects real business value.
Scope, ownership, budget, measurement and success criteria should be clear before the channel is delegated.
Strategy, account setup, campaign objectives, campaigns, ad groups, context hints, creative, budget management, optimisation, reporting and coordination with landing pages and measurement. Where needed, we can also take on CRO, tracking, product feeds or CRM integration.
Yes. We recommend that the advertiser retains ownership of the account, billing, data and core assets. We work with the access required to manage the channel without turning it into an agency black box.
We separate products, needs or situations when they require different messages or destinations. Context hints describe relevant conversations and needs, but we do not treat them as exact-match keywords or delivery guarantees.
Yes. OpenAI currently documents CPM, CPC and oCPC objectives, with oCPM in beta. We choose the model according to the commercial objective and the quality of the available conversion signal rather than using one buying model by default.
Yes. If the landing page limits relevance or conversion, we can design, develop and optimise a dedicated destination. We would rather fix a post-click bottleneck than compensate for it with more media spend.
Yes. We can implement Pixel, Conversions API, UTMs and conversion events, then connect them with the client’s analytics or CRM so platform attribution can be checked against real commercial outcomes.
Before launch we define which conversion matters, what it can cost and how much signal the pilot needs. We then read cost and volume alongside purchase value, lead quality, opportunity or revenue. Management should lead to a clear decision to scale, correct or stop.
We do not impose one universal figure across every business. A pilot needs enough spend to generate useful signal without creating risk that is disproportionate to the value of the conversion. Our pricing page explains how we separate media spend, setup and management.
Management centralises the channel, while these services go deeper where another layer is limiting performance.
Tell us what you sell, which conversion matters and which paid channels you use today. We will show you how we would structure the channel, what needs to be measured and what would justify scaling, correcting or stopping.
What you sell, which markets you work in and what you want to learn from the first pilot. If the scope is not clear yet, we will define it with you.