Maybe I’m missing something obvious, but this feels like a huge gap.

I manage Meta Ads, Google Ads, and Amazon Ads daily, and I make so many micro changes that after a few days I genuinely cannot remember:

• what changed
• when it changed
• why performance shifted

And platform change histories are technically there… but useless for actual understanding.

I wish there was:

• a lightweight desktop app or Chrome extension
• that passively watches ad platform activity
• detects meaningful actions
• and generates an AI summary/changelog automatically

Almost like:
“Here’s everything you changed in your accounts this week.”

I don’t want another Notion template or spreadsheet.
I want automatic memory for performance marketing work.

Has anyone found something close to this?

Ads on Google AI mode was the most interesting topic on Google Marketing Live EMEA, according to me. Do you think it will increase the popularity of Google Ads AI Max? Till now the reviews have been mixed, mostly negative.

I’m working on a small mobile game (hyper-casual puzzle style), and user acquisition has felt noticeably harder over the past year.

Even when installs look okay, the actual player quality seems very inconsistent.

I’ve been experimenting with different acquisition approaches recently and started paying closer attention to how users behave after install rather than just install volume.

A few things I’ve noticed:

• Some campaigns that look “cheap” don’t bring engaged users
• Retention seems to tell a much clearer story than acquisition cost
• It’s getting harder to understand what’s actually driving quality users
• Tracking and attribution feel less reliable than before

At this point, I’m starting to question whether focusing on cost per install is even useful anymore without deeper engagement data.

Curious how others are approaching this right now:

Are you still optimizing mainly for install cost, or have you shifted focus more toward retention / long-term value?

What’s actually working for you in mobile UA lately?

A quick note up front: Everything in this post is from my own hands-on experience going through the OpenAI Ads Manager beta — every step, every screenshot, every observation is real. My original write-up was scattered (I was taking notes as I went), so I used AI to help me organize the structure and make it readable. The substance is mine; the formatting got help. Full screenshots included below for anyone who wants to verify. If AI-assisted editing is a dealbreaker, no hard feelings — skip away.

TL;DR:

• Got into the OpenAI Ads Manager beta (15-day wait after applying)
• Full walkthrough below: dashboard → campaign setup → context hints → ad creative → submit
• Real performance data coming in a few days

Applied for the OpenAI Ads Manager beta about two weeks ago and got approved a few days back — roughly 15 days from submitting the application to receiving the access email. Just finished setting up my first campaign.

Since the self-serve beta opened on May 5th there haven't been a ton of hands-on walkthroughs out there, so I figured I'd document the whole process — from the invite email through hitting submit — and come back in a few days with actual performance numbers.

Posting this now while it's fresh. Data update will go in the edits.

The invite email

Came through as a standard transactional email — clean, minimal, just a login button. Nothing fancy.

Dashboard — first impression

Once you're in, the UI is minimal — almost surprisingly so. Left sidebar has just four sections: Campaigns, Tools, Billing, Settings. No reports tab, no audience manager, no asset library. Compared to the sprawl of Google Ads or Meta Ads Manager, this feels stripped down.

The main view defaults to a Campaigns tab with sub-tabs for Campaigns / Ad groups / Ads — so the classic three-level hierarchy is there, just collapsed into one screen instead of separate pages. A green banner at the top confirms "Account verified — you're approved to launch ads in ChatGPT."

A few things worth flagging from the sidebar before diving into campaign creation:

• Tools only has Change History and Conversions right now
• Billing has the full set (Overview / Activity / Documents / Settings) — payment infrastructure is clearly more built out than the campaign tooling
• Settings has an API Keys section. So programmatic campaign management is on the table from day one, which is more than I can say for some platforms that have been around for a decade

Creating a campaign — Objective

First decision: campaign objective. Three options in the dropdown — Reach, Clicks, and Conversions — but Conversions is currently labeled "Coming soon." So right now you're choosing between optimizing for impressions (CPM) or clicks (CPC). The CPC option only launched with this beta — during the earlier managed pilot, CPM was the only buying model.

Worth noting: even though Conversions as an objective isn't live, you can still set up conversion tracking to measure results. The algorithm just won't optimize toward those events yet.

Country targeting

Location targeting at the campaign level is hard-capped to four countries: United States, Canada, Australia, New Zealand. That's it. The "Enter another location" field exists but the dropdown won't accept anything else.

Matches what OpenAI said publicly: ads only serve to Free and Go tier ChatGPT users in those four markets right now. If you're hoping to run ChatGPT ads in the UK, EU, or anywhere in APAC outside ANZ, you're waiting.

Budget

Standard setup — pick Campaign budget (total spend cap) or Daily budget (a daily ceiling). Same model as Google Ads and Meta. No minimum spend floor that I could find — which is a real change from the early pilot days when entry was reportedly $50K+.

Conversion tracking & the web-only problem

Before you can set up conversion events, you have to create a data source. The form asks for a name, then a Type: Web / iOS / Android.

Only Web is selectable. iOS and Android are both marked "Coming soon."

This is the single biggest limitation for anyone planning to run ChatGPT ads for an app. You can drive traffic to a web landing page and track it, but there's no native app-install or in-app event tracking yet. If your business is app-first, this beta isn't ready for you — though the fact that the form already has iOS/Android slots suggests it's on the roadmap.

The Web data source itself gives you a standard pixel: a <script> tag with a unique pixel ID that you drop into your site's <head>. Once installed, you can define conversion events — currently the only base event type is page_viewed, with a configurable conversion window (default 30 days). There's also a separate Conversions module under the Tools sidebar with a "Manage conversion keys" option — so the pixel/server-side infrastructure exists, it's just gated to Web for now.

Ad group — where it stops looking like Google Ads

The Ad group page is where ChatGPT Ads starts to diverge from everything else. Four fields:

1. Ad group name — standard
2. Maximum CPC bid — range is $0.01 to $100.00. The default placeholder is $3.00, which is a tell: OpenAI seems to think that's roughly the right ballpark for early auctions. For context, average Google Search CPC sits around $1-$2 and Meta around $0.50-$1.50 in most verticals. ChatGPT Ads is launching with a higher floor signal than either
3. Website URL — default destination for ads in this group. Standard ad-group-level setting
4. Context hints — and this is the part that's actually new

OpenAI's own description of context hints:

>"Describe the conversations, topics, or keywords where your products or services may be relevant; these hints guide matching but aren't exact-match targeting rules."

Read that twice. A few things stand out:

• It's called hints, not keywords or targets. Soft guidance, not hard filters
• "Guide matching" — the LLM uses these to understand what conversations your ad belongs in, not to do string-matching against user input
• "Aren't exact-match targeting rules" — they're explicitly telling you not to think in Google Ads terms

So this isn't keyword bidding. It isn't audience targeting either. It's something closer to: "here's a description of the context where my ad makes sense — figure out the rest, model."

The input UI itself is bare. Just a multi-line text box. No tagging, no chips, no autocomplete, no suggested hints, no keyword volume tool, no competitor research. You're writing into a blank text box and trusting the model. That's either liberating or terrifying depending on where you sit.

My read on how to write them (happy to be wrong):

• Too narrow probably under-delivers — the model can semantically expand from transcribing meetings to a lot of related conversations, so being too literal limits reach
• Too broad probably tanks relevance — productivity is so vague the model has nothing to anchor on
• Sweet spot is probably scenario + intent, e.g. taking notes during long meetings rather than just notes

No one knows the best practice yet. This beta launched two weeks ago. There's no data on what works.

Ad creative

Five fields:

• Ad name — internal label
• Website URL — inherits the ad group default but can override
• Headline — 50 character limit
• Description — 100 character limit
• Ad images — PNG/JPG, square recommended, minimum 256×256px

Character limits are tight. For comparison, Google Search Ads gives you 3× 30-char headlines plus 2× 90-char descriptions — roughly 270 characters total. ChatGPT Ads gives you 150 characters total. You have to land the value prop in one sentence.

The preview shown in the panel looks like a small card with a "Sponsored" label, brand name, headline (truncated at ~35 chars in the preview), description (also truncated), and a small thumbnail image. The ad unit is clearly designed to slot below a ChatGPT response, not to dominate the screen.

A few observations on the creative spec:

• Image displays small in the preview — fine detail in the image is wasted
• Headline gets truncated well before 50 chars in the actual preview — front-load the most important information
• No CTA button selection that I could find (no "Learn More" / "Download" / "Sign Up" picker)
• No A/B testing primitives at the ad level yet — if you want to test creatives, you build multiple ads under one ad group

Review and submit

The final step is a Review page that summarizes everything: campaign name, objective, locations, budget, conversion event, schedule, ad group settings, context hints, and the ad itself. Hit submit and the campaign goes into review.

No timeline given on how long ad review takes. I'll update once mine clears.

Surprises, friction, and what's missing

A few takeaways after going through the whole flow:

🟢 Surprises (in a good way)

• API Keys section exists in Settings — programmatic management from day one
• No minimum spend floor — the rumored $50K pilot entry is gone
• The three-level Campaign / Ad group / Ad hierarchy is exactly Google Ads — zero conceptual onboarding for anyone with Google experience
• Conversion tracking infrastructure (pixel + events + conversion keys) is mature for a 2-week-old self-serve beta

🟡 Friction

• Default CPC suggestion of $3.00 is high relative to other channels — feels like an anchoring move
• Context hints input is a blank text box with no guidance, no suggestions, no volume estimator — you're flying blind
• Character limits on headlines/descriptions are aggressive
• Preview truncates headlines around 35 chars even though the field accepts 50

🔴 Missing (for now)

• Conversions as an objective — Coming soon
• iOS / Android data sources — Coming soon
• Countries outside US / CA / AU / NZ
• CTA button selection
• A/B testing tooling
• Audience exclusion / frequency cap (didn't find these — happy to be corrected if I missed them)

What I'm doing next

The campaign is configured and ready. I'll come back with actual performance data once it's been live for a few days — impressions, clicks, real CPC, CTR, which context hints actually pulled volume, and how the ads end up looking inside ChatGPT.

For anyone else in the beta — would love to compare notes, especially on context hints. Did your first batch get approved on the first try? Any patterns on what gets flagged?

https://preview.redd.it/uy8gnpvf7g2h1.png?width=1899&format=png&auto=webp&s=b9c8b343b6ff51c0a5a8c9d0624ac4fe9bce89f3

Will edit this post with the data update soon.

I’ve been digging into how third-party cookie deprecation is reshaping performance marketing, especially from a game UA perspective, and I think most of the discussion around it is still framed incorrectly.

A lot of teams treat this like a sudden loss of capability. In practice, most cookie-based tracking was already degraded long before full deprecation.

TL;DR (high level)

• Cookie-based attribution was already unreliable (inflated ROAS, duplicated conversions, fraud exposure, consent loss)
• The shift isn’t removing signal it’s changing where the signal comes from
• First-party data + server-to-server tracking are becoming the core measurement layer
• “More data” is being replaced by “cleaner data”
• The winners are systems built around direct user relationships, not browser-based inference

What was already broken before cookies disappeared

Even before deprecation, most performance stacks were operating on compromised data:

Attribution was heavily duplicated
Multiple platforms often claimed the same conversion, especially in multi-channel setups. This made ROAS look stronger than actual incremental performance.

Fraud and invalid traffic were underestimated
Browser-based tracking created room for manipulation (click injection, attribution spoofing, etc.), which distorted channel quality.

Consent reduced usable datasets
GDPR/CCPA-style opt-outs already removed a large portion of users from tracking pools, meaning a lot of “tracked” audiences were never truly representative.

What actually changes after cookies

The shift is less about “loss” and more about restructuring:

1. First-party data becomes the baseline

Owned audiences (logged-in users, CRM lists, app users) become significantly more important because they are not dependent on browser behavior.

2. Server-to-server (S2S) tracking replaces browser pixels

Instead of relying on client-side scripts, conversion events are passed directly between systems.

This reduces:

• duplicate firing
• cross-device noise
• browser restrictions (Safari/Chrome privacy changes)

And improves:

• consistency of attribution
• fraud resistance
• data cleanliness

3. Measurement shifts from volume to quality

Instead of optimizing for:

• installs / clicks / raw ROAS

Teams move toward:

• retention-based cohorts
• LTV signals
• incremental lift testing

Who actually benefits from this shift

From what I’ve seen across campaigns and discussions, the advantage shifts toward:

1. Teams with first-party audiences
Apps, games, and products with direct user relationships have a structural advantage because they’re not dependent on external tracking systems.

2. Server-side tracking setups
Teams using MMPs (or similar infrastructure) with proper S2S integrations generally get cleaner attribution than browser-based setups.

3. Controlled traffic environments
Environments where the user relationship is explicit (opt-in audiences, logged-in ecosystems) tend to produce more stable conversion signals than open aggregated traffic sources.

What changes in practice for UA / performance teams

Most teams adapting well are doing some combination of:

• moving key tracking events server-side (S2S)
• reducing reliance on last-click reporting alone
• validating campaigns through incrementality tests
• separating “reported performance” from “true incremental performance”

The biggest shift isn’t technical it’s mental:
Stop trusting dashboards at face value and start validating signal quality.

Key takeaway

Cookie deprecation didn’t remove performance marketing tracking.

It exposed how noisy and inflated a lot of it already was.

What replaces it is not a single tool, but a stack built around:

• direct user relationships
• server-side event flow
• and measurement methods that prioritize real lift over reported attribution

Question for discussion

For those working on UA / growth:

• Are you still heavily relying on browser-based attribution models?
• Have you fully shifted parts of your stack to server-side tracking?
• What’s been the hardest part of trusting “cleaner but smaller” datasets?

Curious how others are adapting this in real production setups.

Stream kicks off at 11:00 BST. Yesterday's US keynote covered a lot (Ask Advisor, AI Max for Shopping, Asset Studio, Universal Commerce Protocol, Ads in AI Mode) but will EMEA bring a different angle?

I'm curious about:

• Any concrete EU rollout timelines for the big announcements
• How Universal Commerce Protocol fits with PSD2 and the EU payments landscape
• Anything specifically built for EMEA markets that didn't make the US stage

What's on your list? Anyone tuning in? Maybe we can play Bingo with how many times "AI driven" is said :D

Noticed that some accounts have recently changed. The quality of traffic seems to be stable. The audience has not really changed. The bid is very good. However, the conversion rate of landing pages that have been strong for more than a year has begun to decline.

At first I thought it was seasonality or attribution. But honestly, I think the actual searcher has changed. The person who logged in to your page today is not the same person who clicked on that result 18 months ago.

Before the click happened, they had already got part of the answer from the AI overview. They already understand the basics, already know the problem, and have compared several options before even reaching your website.
Therefore, when they landed on a page that educated them from scratch, they suddenly felt very slow. There are too many settings. Too much that's why it's important.This page is talking to buyers who arrived earlier than the buyers who actually arrived.

It feels like many landing pages are still built for ai's pre-search behavior, and no one has really adjusted the messaging of this shift.

One thing we have started testing is to move the content of the differentiation and decision-making stages higher on the page. Explain the category less. More answers "Why are you in the other options I already know?"

I wonder if anyone else has noticed any recent changes in customer behavior or landing page effectiveness??

Interested in metrics that look scary early but need more context before changing the campaign.

Managing meta ads for a licensed HVAC company covering Dallas and San Antonio. $80/day, instant forms, broad targeting. Client is on the verge of walking.

I've thrown everything at this. Multiple creative angles, energy savings, health/air quality, financing ($34/month through 15+ lenders), free inspection, buyback program for old units, before/after images, AI creative, real job photos, Spanish and English copy. Nothing is moving the needle. CPL is high, lead volume is low, and the client has lost patience.

The problem is the market is just brutally competitive. Dallas and San Antonio HVAC in May is a bloodbath. Every company is running the same offers and the same hooks.

I just told the client they need to get their lead technician on camera, authentic, unscripted, real job site, and film two videos. One for tune-up season, one for installations. My theory is that everything I've been running (only static ads) looks like every other HVAC ad and real video might actually stop the scroll.

Hoping that's the move. Not 100% sure it is.

Anyone running home services in saturated markets on Meta? What's actually working for you right now?

I currently have four PMax campaigns running on Google Ads. Three of these campaigns have maintained a ROAS of 5 or higher (based on data from the last 20 to 30 days). Furthermore, the daily budget for each of these campaigns is consistently being fully utilized.

Previously, the target ROAS for these campaigns was set at 220%. I have now increased this target from 220% to a range of 250%–270%. I would like to know: can I expect to see a further increase in conversion value as a result of this adjustment?

The bloat on the Google Ads web UI is unbearable lately and only seem to get worse. Are there any browser extensions out there that clear this unnecessary crap? I use uBlock Origin to block elements I don't like but unfortunately it also blocks my ads themselves so I frequently have to turn it off to do stuff to my ads.

One of my long term clients (a remodeler) have asked me during our last meeting to create some facebook slop for their facebook page. This convo fully evolved into something different, and he started to ask me to put money into ads generated by some ai platform, wheter video or picture. I must say that our regular cmpaign's aren't that great lately and he's a kind of young still man (in his 40s) so he's very deep into all these Ai chatgpt stuff in his company.

I have past experience with Ai images, creating them for his website, but I've never tried to do an actual Ad and i'm kind of afraid of wasting budget. Y'all have any experience that can share with me? Thank you in advance.

Need some advice from people who’ve worked on performance marketing for restaurant/bakery/food brands.

Recently joined a brand that’s upgrading their static site to a site with own direct online ordering to reduce the orders on 3rd party platforms, and I’m currently planning the performance marketing strategy. The challenge is that the budget is fairly limited, and the product category includes bakery items, restaurant food and hampers.

Their goal is to get sales through their own site.

From the research that I have carried:

• Local competitors aren’t really running strong direct-ordering performance campaigns and most only use the 3rd party platforms for delivery.

• The nation wide brands are mainly using Meta ads for awareness with few conversion focused ads and are running multiple PMax ads targeting branded keywords.

• Attribution also feels tricky since a lot of actual purchases still happen offline/repeat behaviour based.

I am confused on what should I focus on? I have a list of customers, so I am thinking of running a LAL sales campaign on Meta and then running low-budget search campaign on Google with branded and few query words focused on delivery.

Open to suggestions if there’s a better approach or something important I might be missing here, especially when working with smaller budgets and mixed online/offline purchase behaviour.

Neil Patel IMO was the biggest show off for GML, and u/google violated a patent and trademark for "QFC" grocery store.

Though would you invest more now as an SMB knowing 6 months from now you can get QFC?

We’re in event tech (event registration, ticketing, onsite check-in, access management, event software/hardware). For years, Google Search worked extremely well for us.

Since late 2025 / early 2026, something feels materially different.

What we’ve tried in the last 4 months:

• roughly doubled budget
• tested new search campaigns
• phrase match expansion
• India + UAE markets
• high impression share / top-of-page presence (often outranking competitors in auction insights)
• budget exhausting and impressions coming in

Problem:

Leads have almost disappeared.

Historically we used to get consistent inbound demo/leads. Now traffic/impressions are there but conversions are extremely weak.

What’s confusing me:

1. We are showing at the top most of the time.
2. Competitors seem weaker in auction insights.
3. Search demand doesn’t look “dead.”
4. Yet buyer intent feels dramatically worse.

For people managing B2B PPC:

What actually changed in search behavior?

Would love to hear if others are seeing this or if I’m diagnosing this wrong.

Help plz! I am managing a Grant account and it seriously underspending. I've tried P-Max, Search, Search + A.I. Max, broad match etc but getting nowhere near budget.

https://preview.redd.it/dcihlkdeva2h1.jpg?width=1290&format=pjpg&auto=webp&s=3c0da54bb72a1bbdde6b9c1c4915476596b3d0d7

Clicking the link takes me directly to the "Appointment Successful" page. Does anyone know how to fix this?

I have a client who we do SEO for and ads in the past but haven't in over a year. We want to run ads again but just realized the account got suspended for "Circumventing systems: Advertiser verification." Im thinking this is because we didn't submit our advertiser verification in time.

The problem is now I can't submit the documents needed, it just says contact us and submit an appeal. I submitted the appeal but haven't heard back.

My question is, what's the best course of action here and is this even possible to reinstate it?

I have a client who does non surgical fat removal in Washington DC, we spent $6k on ads and got 20 form fills and 30 phone calls. Conv rate on ads is 6%

But the client says he's not profitable and has closed $7k in sales (2 sales total) only.

I think his sales process sucks as his conv rate from leads is less than 5%

What is a good lead to sale conv ratio

And how would you handle this situation

(He gave me till month end to figure things out)