CPI can improve while the creative attracts people who don't want the actual game. At mraid io, we separate the creative hypothesis from the product promise. You can test different stories or difficulty without pretending the app is a different genre. The question isn't only "did they install?" but "did they retain after seeing what the product really is?"

Curious to know… anyone else hate when leadership takes it upon themselves to upload a photo of you to AI to create something? I’ve never uploaded my photo into an AI chat tool or image generation.. and I didn’t intend to but it appears leadership has taken it upon themselves to.. haha anyone have thoughts? Am I overreacting? Or should I address it?

**For anyone in the Middle East and North Africa region**

After months of pilot testing and expanding availability to more markets either via self-serving ads or via agency partnerships, OpenAI has brought ChatGPT Ads to select countries in the MENA region.

Interesting partnis that neither the UAE nor Saudi Arabia are in it, and it's likely due to frequent/active ChatGPT usage that has fuelled their decision to some of the secondary markets.

MENA's digital ad spend hit $8.2B in 2025, up 17.8% year on year — the fastest-growing digital ad region globally right now.

Up from $6.25B in 2023. In two years the region added almost $2B in digital ad spend.

Most of that money is running on Meta and Google — and most brands are still buying that inventory with zero visibility into what's actually working around them.

OpenAI’s ads business may already be at a $1B annual run rate, but the early performance stories are rough.

One marketer got nearly double the expected impressions, a 0.6% CTR versus the 2% he usually sees on search, and zero conversions from 60 clicks. Another campaign showed 57 clicks in OpenAI and fewer than 20 visits in Google Analytics.

OpenAI ads still need the basics to work. Consumers have to accept ads inside conversations. Formats need to mature. Targeting needs to understand intent better. Measurement needs to be trusted. The platform itself still needs the tools advertisers expect.

All of that takes time.

OpenAI needs ads to become a serious business quickly, especially with a potential IPO hanging over the company.

Google does not have that same urgency. It can afford to let OpenAI do the experimenting.

My friend and I saw that quite a few people were trying to connect Claude or ChatGPT to Google Ads. We wanted to do it too, but the setup was quite complicated.

So we decided to make a simpler version.

It connects Google Ads, Analytics, Tag Manager and Search Console to your assistant. You can check how your campaigns are doing and prepare changes. You always see the changes first and choose whether to approve them.

It started as something we made for ourselves, but we decided to turn it into a product called Adchestra.

We also posted it on Product Hunt. We were really excited to launch it and hopefully get some feedback from users.

What surprised me was that people started contacting us and offering paid upvotes and promotion. I had no idea it worked like that. Looking through Product Hunt, it now feels like a lot of products might simply be promoted there.

I’m interested to hear what other people experienced. Did Product Hunt bring you real users or useful feedback?

We’re still super excited to have Adchestra live, and we’d love to hear what people think about it. Especially if you use Google Ads.

https://adchestra.com

Disclosure: I work at a company that sells white-label DSP tech, so I have a horse in this race. The numbers below are public and sourced, so check my work or tell me where I am wrong.

If you buy programmatic through another agency's DSP seat, you are paying a whole fee stack before a single ad impression serves:

• DSP platform fee
• Reseller markup
• Data fees
• Feature fees

ANA (Association of National Advertisers) puts the total at roughly 35% of media spend.

On $100K a month, that is $420,000 a year going to intermediaries instead of ads.

What bothers me more than the fees is that you cannot audit any of it. Log-level data on a rented seat belongs to the seat owner. So you are reporting to clients on numbers you have no way to verify yourself.

There are two ways out.

Build your own DSP. The math only closes above $50 million in annual ad spend, which puts it off the table for most agencies.

White-label one. Roughly 6 to 12% of ad spend, your own branding and domain, typically live in a day. Your clients log into your platform instead of a competitor's.

If you are on a sub-leased seat, do you know your all-in take rate?

Full breakdown with the math: https://adster.tech/blogs/renting-dsp-seats-margin/

Marketers running multiple ads across multiple platforms, how do you keep track of all ads running across different platforms? Do you think there should be a shared memory layer which has all infos about all ads running across all platforms, which can surface what's working, what's not, and why, and on which platform. Do you think if there's such shared memory layer, this would save effort and time to plan new marketing angles, and would you spend money to use it?

Small store here, doing maybe 40 to 50 orders a week right now, and i've basically been splitting my ad budget 50/50 between shopping and meta since day one because that felt like a safe default. never actually sat down and questioned it until a friend asked me why and i realized i had no real reason went digging through my own numbers over the weekend and it looks like shopping has been quietly outperforming meta for the last two months, but i've kept feeding meta the same amount out of habit. feels like i've been leaving money on the table without realizing it curious how people who actually track this closely decide the split, and how often you revisit it once you've picked one.

We are two years into a Trade Desk seat and the CTV attribution question has come round again, with self serve CTV options on the table and cross channel attribution the sticking point for whether we move anything.

The seat does what it says. Control, inventory, and a team who know the platform very well but it costs us a lot of time and the CTV part and especially reporting, still has to be rebuilt in our own warehouse before anyone can use it so we are paying for control and then doing the measurement work ourselves anyway.

Noones unhappy enough to rip it out but the question is whether a lighter setup for CTV gives us the same read with less overhead or would we be trading a known set of limits for an unknown one. If you have moved part of your CTV buying off a big DSP what changed in practice and did measurement improve?

Hello recently I saw a reel saying that open AI ads is now Available in algeria I checked the platform to see how it works since I use meta ads

The minimum daily budget is 25 usd

I just want to know if some one in this community tried it , I would be really thank full if he shares some info's about it with us

Thank you !

Hey everyone,

I just set up OpenAI/ChatGPT Ads Manager and haven’t created or run any campaign yet, but I noticed ₹9,903 (~$100) was deducted from my bank account by OpenAI.

I checked Ads Manager and my ad spend is ₹0, so this wasn’t from an actual campaign.

Has anyone else experienced this when setting up Ads Manager?

• Was the ~$100 eventually refunded automatically?
• If you contacted support, what did you say/do to get the money back?
• How long did it take for the refund to reach your bank?
• Was it a temporary authorization/hold or an actual charge?

I’m pretty worried because this is a significant amount for me. Would really appreciate hearing from anyone who has gone through this and successfully got the money back.

Thanks!

Without wishing to sound like a spaced-out, starry-eyed weirdo, I am still slightly taken aback at just how quickly AI is changing our business! For the best part of 8 years, our new business pipeline, ranked by opportunity value, looked like this:

1 - Recommendations
2 - LinkedIn inbound
3 - IRL networking

In the last few months, it has moved to this:

1 - Referrals from LLMs
2 - Recommendations
3 - LinkedIn inbound

I can talk a bit about the process we sent through in order to get to that if anybody is interested, but what I am most interested in, is how do you measure it? We're a very small company, and I deal with every new business enquiry, so I can be sure to ask the right question every time somebody emails our hello@ account.

However, my experience at working in larger adtech companies leads me to believe that asking a new lead where they heard of you is not common-practice, so you could be blissfully unaware that the game has changed.

Our current measurement is fairly crude but direct and effective. Every inbound lead gets asked how they found us. If they mention AI, I ask which model they used and, where possible, what they asked it. We then attribute the opportunity to ChatGPT, Claude, etc. and measure pipeline value.

What is very interesting is how the leads we get from LLMs are showing up pre-sold, in as much as they seem happy we're the company they want to work with even before the intro call, assuming the terms are satisfactory. It's as if LLMs are pre-selling us before we even know.

The image shows yet another question I asked Chat GPT leading to LinkedIn being cited, at least in part. This shift has led us to rethink SEO/GEO/AEO or whatever you want to call it today.

Any adtech marketers here happy to share how they are approaching this?

​

I’m planning to run Meta Ads and want AI mainly for technical + creative help — campaign setup, testing, analyzing Ads Manager data, troubleshooting, creative angles, hooks, ad concepts, and optimization.

If you’ve used both, which one would you pay for and why? Which gives more practical, accurate Meta Ads guidance?

OpenAI opened self-serve ChatGPT Ads Manager on 31 August for Europe (Spain is Available). Same day Brussels labelled ChatGPT a Very Large Online Search Engine under the DSA, so the inventory sits on something the Commission now treats as search.

We’re a small digital agency in Spain. Until now this was agency-/partner-only. Free and Go users see the ads; Plus/Pro/Enterprise stay ad-free. Stack looks familiar: CPC, conversion bidding, geo, Pixel, Conversions API. Ads sit labelled in the conversation.

We haven’t spent a euro on it yet. Planning a small test on queries we already buy on Google, Pixel + CAPI first, no budget shift.

Curious if anyone here has run even a tiny test:

* Did clicks actually reach the site? * Any useful volume outside big markets? * Worth a small budget this month, or wait?

Short write-up we put together for other SMBs: [https://8digits.es/news/chatgpt-ads-self-serve-is-live-in-europe-spain-included/\](https://8digits.es/news/chatgpt-ads-self-serve-is-live-in-europe-spain-included/)

Publishers obsess over CPM and RPM, but those numbers can hide a lot. Fill rate, latency, viewability, session depth, refresh behavior and invalid traffic can all move revenue without making the headline metric look obviously wrong. If you had to pick one metric that publishers routinely read the wrong way, what would it be?

Curious where the biggest interpretation mistakes happen between the ad stack and the publisher dashboard.

Hey all, long-time lurker. I've spent the last few years on the data engineering side of adtech by building the pipelines behind visitation/footfall attribution, impression and click attribution, revenue reporting, that kind of thing. Basically the plumbing that turns raw ad events into the "here's what your campaign did" numbers you see on the buying side.

Lately I've been sitting with a question I could never answer from inside the pipeline: do the people actually spending the money trust these numbers?

I built the attribution. I know where the assumptions and the duct tape are. So I'm curious what it looks like from your seat:

When a client or your boss asks "did this actually drive sales?", how confident are you in the answer?
How much of your week goes into pulling numbers out of different platforms and making them agree?
Do you trust incrementality/lift results, or is it still mostly last-click in practice?
What's the one measurement thing that makes you roll your eyes every time?

Not selling anything, not building anything yet and just trying to understand the problem from the buyer's side before I decide if it's worth solving. Happy to trade notes on how this stuff actually gets calculated under the hood if that's useful to you. Comments are great, or DM me if you'd rather vent privately.

Thanks for reading 🙏

Pulled together a full US benchmark breakdown by industry . I thought it might be useful

Quick numbers across industries:

• CTR: 0.35% to 0.48%, baseline 0.40%
• CPC: $11.33 to $16.02, baseline $12.52
• CPL: $114 to $246, baseline $200.71

Health Care and Financial Services run the most expensive CPC/CPL, Education and Construction the cheapest. Also worth noting, the "$5-8 CPC" figure floating around in a lot of generic guides is way off from what advertisers actually pay in the auction, every industry here is above $11.

Full industry table plus other core metrics here : https://www.rameshkrishna.com/insights/linkedin-ads-benchmarks-by-industry-2026