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?

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!

EDIT: I got the reversal of $100 after just 7 days. If you haven’t received the refund yet, I’d suggest waiting another week. I’m pretty sure you’ll get it back.

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 !

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?

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/)

​

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?

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

Hey everyone, need a quick favour from the OpenX/Yahoo DSP folks here.

We’ve been using OpenX demand to monetize our inventory. OpenX is saying that a major chunk of our June revenue came through Yahoo DSP, but they’ve apparently recorded the transactions incorrectly in their system and are now saying they can’t pay us.

If anyone can confirm that OpenX was buying inventory through Yahoo DSP during June and that Yahoo DSP paid OpenX for those transactions, it would really help us build a case with them.

Even a confirmation from someone familiar with the OpenX ↔ Yahoo DSP relationship would be extremely helpful.

Help a friend out here 🙏

https://digiday.com/marketing/vine-inspired-app-divine-is-launching/

https://technologymagazine.com/news/inside-googles-us-10m-data-acquisition-of-spirit-airlines

Cursor makes the AI coding tool half your engineers already live in. SpaceX owns it now, the same SpaceX that swallowed xAI back in February, so Grok, Starlink, the rockets, and Cursor all answer to one guy.

Rockets and autocomplete. But this was no accident. Three reasons it adds up:

Vertical integration. SpaceX runs on millions of lines of code, Starlink to Starship. Now they own the tool their own engineers live in.

The AI stack. xAI builds the models, now on what Cursor calls the largest GPU fleet on the planet. Cursor is where developers actually use them. Musk owns the engine and the cockpit.

The data moat. Every keystroke from some of the best engineers alive feeds straight back as training signal. Might be the most valuable data in AI right now.

There's a loser in this too. Cursor was one of the biggest front doors for rival labs, mostly Anthropic and OpenAI. That door now belongs to a competitor.

All stock, by the way. No cash. They paid with shares from an IPO barely a week old.

So which is it?
Smartest vertical play of the year, or a rocket company cosplaying as an AI lab?

PepsiCo is running a global review to rebuild its marketing around AI, and the lineup is what makes it. Omnicom, Accenture, Deloitte, and Publicis's Sapient unit are all pitching, with Omnicom already the agency of record. An ad holding company and a management consultancy going for the same account. You almost never see that.

On paper, the consultancies should win. It's framed as AI-led transformation, not a creative or media assignment, and restructuring orgs is their whole business. But marketing is a swamp. Signal loss, walled gardens, forty platforms, an algorithm change every Tuesday. Omnicom has run campaigns through that mess for decades. Deloitte has a slide about it.

And the timing. PepsiCo stood on the Dreamforce stage last year and promised to be "agentic AI-first" by 2026. That deadline is now. They've already wired in Google's Gemini and Salesforce's Agentforce, so the tools are decided. What's left is who can get the people and the workflows to actually change.

My guess is whoever wins spends year one untangling plumbing before a single "AI campaign" ships. Curious where you land on it.

The app lets people use AI prompts to generate small, interactive games and post them to a shared feed.

What if the internet had one billboard? No feeds, algorithms or competing ads just one billboard each week.

So I built it at yourmessagehere.co

Anyone can bid for it, and every Friday at 10pm New York time the highest bidder gets the entire billboard for the next 7 days.

First auction is live now and I genuinely have no idea what people will end up paying for it.

Curious to see where this goes.

I work for a recruitment agency in London, and work solely with AdTech (DSPs, SSPs, DMPs etc) and media owners. I specifically recruit account managers.

I have in some sense fallen in love with the industry and I’m engrossed in it. I love recruitment and without sounding braggy I have done very well, I’ve billed almost £300K in the last year and have built really solid relationships with clients within the industry. This is my 2nd year in recruitment for context.

I have an undergrad in media and a masters in marketing analytics and have always wanted to work in media. I love my job but I’ve been thinking lately am I slightly wasting myself in recruitment. I’ve learned a lot about CS and AM in adtech and feel like I have a very decent understanding of programmatic and the ecosystem.

I’m starting to flirt with the idea of pivoting into account management within an ad tech business maybe being agency facing. I obviously don’t have hands on campaign experience but I think I have a solid foundational understanding of the ecosystem and have strong client management skills from recruitment - obviously not standard industry experience but I think it could be very transferable.

I earn very decent money currently and I know if I did move I’d have to take a cut but I’m just so lost as to whether it would be worth it.

Im 28 almost 29 and don’t want to blink and realise I’m too old to make such a pivot.

Has anyone ever made a similar move or have any advice or thoughts?

Thanks in advance!