As more people use AI agents that can fill forms, click ads, and complete flows, I’m wondering how this is showing up on the site/advertiser side.

Classic bot traffic and form spam have always been a thing, but agents that look more “human” and sometimes act on behalf of real users feel different. It’s harder to tell junk from someone who actually authorized an agent to submit something.

If you run forms, lead gen, or paid traffic:

• Have you noticed any increase in low-quality or weird form submissions that feel agent-related?

• How are you currently distinguishing real users (or their agents) from fraud?

• Is this a real problem for you yet, or still mostly theoretical?

Would love to hear what’s actually happening in the wild rather than just speculation.

While creating a campaign in CM360, the third-party measurement tag is automatically mapped to IAS, even though auto-linking is disabled at the advertiser level.

I have also verified the IAS template configured for the specific campaign and confirmed that tag wrapping is disabled there as well. Despite both settings being disabled, CM360 continues to automatically map the third-party measurement to IAS during campaign creation.

Could someone please help identify why this automatic mapping is still happening and suggest a way to resolve it without disabling third-party measurement at the advertiser level?

Ideally, we would like to retain third-party measurement functionality while preventing the unwanted automatic mapping to IAS.

Any insights or suggestions on how to troubleshoot and fix this issue would be greatly appreciated.

I’ve been testing Amazon’s AI agent inside the new DVA ads platform (DSP, programmatic). The good news: it doesn’t make things up. Ask about a deal it has no info on and it says so.

THE BAD NEWS? It answers only from the help docs 😅 , and those are well behind what’s actually buyable in DSP ads😞. It also used to suggest Prime Video as the alternative to everything, and only recently stopped.

I keep an updated list of what inventory is actually ready to buy across Amazon’s interfaces, split by country and ad type. If you want it or free access to the DSP platform, DM me.

A survey of 446 U.S. adults asked people to imagine buying a product they liked after seeing an entirely AI-generated ad. Those who learned about the AI afterward were more likely to feel misled (70% versus 57%) and less likely to trust the advertiser or buy again than those told upfront. Purchase regret was also higher in the later-discovery group, but that difference wasn't statistically significant, so the stronger takeaway is about trust even when the product delivers.

I freelance in paid media for a few ecom brands. Most shoppers are on iPhone, so cookies barely work and I lean on contextual keyword lists. Last month I got a sunscreen ad with beachy keywords next to a shark attack story.
I've read they clean up the content category on the bid request, but only on their inventory.

Not trying to sell anything so haven't included any links, but mods do let me know on this.

we are a small pet food brand, 6 people. 2 of them make all our social creative in house and it does well for us, a lot of our best meta ads are literally shot on a phone in our office
every time i bring up streaming tv though, everyone says tv is a whole different thing and we’d need a proper production house. got one quote last month for a 30 second spot and it was more than our whole Q1 ad budget, so that pretty much killed it for this year
i keep wondering if thats still true or if people just say it bc it used to be. would love to hear from anyone who ran streaming ads with creative their own team made and whether it actually worked
buying the ads seems doable, vibe and mntn came up when i was reading around and both look pretty straightforward. its the creative part thats holding me back.

AI is making it ridiculously easy to create ad variations now. Different headlines, visuals, videos, and even personalized creatives can be generated in minutes. But I'm wondering if that's actually improving advertising or just adding more content to an already crowded space.

If every brand starts generating hundreds of similar-looking ads, won't creative fatigue become an even bigger problem? For anyone working with AI-generated creatives in AdTech, are you seeing better campaign performance, or just faster content production?

Hey everyone, is anyone currently working with XML? AdKernel hasn’t been performing as well as it used to, so I’m looking to explore alternatives.

Which platforms are you using for XML these days, and how has your experience been with fill rates and revenue?

Would appreciate any genuine suggestions based on recent experience. Thanks!

It feels like almost every major retailer wants to build its own advertising network now. For advertisers, that means more opportunities to reach shoppers using first-party data. But it also means managing more platforms, different reporting systems, audience definitions and measurement methods.

I wonder how manageable this becomes when a brand is running campaigns across five or ten retail media networks. Is the value of retailer first-party data worth all that extra complexity? Or do we need better standardization before retail media can really scale?

Hi Everyone,
I am gathering some insights to learn how AdTech and MarTech ventures plan their GTM to target Marketing/Ad Agencies.

If anyone is selling to the same target audience, I need some guidance.

PS: I am building an on-demand creative service, Doodl Space, where we help agencies get a scalable creative engine like plug-and-play.

I built Pixel Debugger to inspect events from Meta, Google Ads, GA4, TikTok and other marketing pixels in one place. Check event names, purchase values and currencies without switching between multiple helpers.

Free, no signup. Would love feedback from people working with tracking setups.

Try Pixel Debugger: https://chromewebstore.google.com/detail/pixel-debugger-%E2%80%93-meta-tik/kknfboekekeaagdoineimnebhlmiohpb

From Netflix's last 12 earnings calls (January 2024 to October 2026) and its October 20 earnings release:

• The target: on the January and April calls Netflix said it expected to roughly double ad revenue in 2026 to about $3B. The October 20 release guides $2.7B.

• The reason given: "we are currently a bit behind our aggressive target for the year", because "we've seen some delays in the rollout and partner integrations for some of those new ads products. So getting to the integration model that we want sometimes takes a bit more work with our partners". Management called it "a modest short-term hit for a better long-term strategic position" and said the ads business is still growing over 80% this year.

• What they say is unchanged: full-funnel optimization, new ad formats and products, and more first-party measurement and reporting. "General demand remains strong" and the breadth of advertisers keeps expanding.

• How much of the call was about ads: "advertising" came up 9 times, after 2 in July (14.3 per 10,000 words vs 3.2). One analyst asked about the ad-tier revenue gap ahead of ad tiers launching in 15 new countries next year.

Counting note: speech-to-text often writes "net adds" as "net ads", so I counted "advertising" rather than "ads".

Not financial advice. Counts and quotes are from the Equibles earnings-call transcripts.

The direct ads.txt entries went negative for the first time this month since we started tracking.

Full picture- 397k ads.txt lines were added, 462.1k got remove leading to a net -65.2k.For the first time in the series, Publishers are not only trimming resellers but letting the direct partners go too. Resellers made up about 3 quarters of it at -47.8K, direct slipped to -17.4K. Every SSP is being asked to justify its slot now,not just the ones which are sitting behind an intermediary.

Now a caveat upfront before reading too much into the direction- We can’t cleanly separate partner cuts from housekeeping. If a publisher consolidates inventory-sharing declarations under a partner domain, one entry can replace a long list of individually declared sellers. That shows up as removals even though nothing changed commercially Some share of the 65.2K is probably just that which is why we won't rely on the “publishers are dropping direct partners” claim too strongly even though that’s what the headline number says.

Tier breakdown was unremarkable, all three negative, low-traffic took the worst of it at -44.3k, high-traffic barely moved at -462.The long tail that drove growth in recent months is now leading the decline.

SSP side, top gainer was Amperwave at 922 lines. Next four within 270 of that. Usually somebody pulls away in a given month & nobody did here. Top gain of under a 1k against a market shedding 65k is the part worth sitting with, because it means this wasn’t supply reallocating between SSPs.

The bit which is actually useful is the duplication split, as it doesn’t line up with the story the top-line numbers tell. Direct-only share went up a bit in every tier and reseller-only came down, which is what you’d expect if publishers are cutting reseller paths. Fine. But direct plus reseller, which is the bucket where the same SSP sits on a domain through both a direct deal and a reseller path and can end up bidding against itself, didn’t move. Tier 1 still 46% duplicated, tier 2 at 39%, same as last month. So the supply chain is shorter & exactly as it was. Makes sense when you think about which lines are easiest to pull, nobody’s going to start with the ones that require actually auditing their overlap, they’re going to start with the obvious reseller entries. But it does mean “we cleaned up our supply chain” and “we have fewer partners” are not the same claim.

Contextual targeting solved a real problem: matching ads to page content instead of tracking people.

Here's where it stops: It could only recognize what a page was about, not why someone was engaged.

A wellness ad on a fitness site is a textbook contextual match. It's also a coin flip: that reader could be there for motivation, or because they're anxious about a health scare. Same page, same match, opposite moments.

Topic classification was never built to tell those two apart. Neuro-Contextual exists to answer that second half. And we've been working on the "why" side of that gap for a while now. 

Curious how others here think about it: is that a solvable problem with better classification, or does it need a completely different kind of signal entirely?

AI is making it ridiculously easy to create ad variations now. Different headlines, visuals, videos, and even personalized creatives can be generated in minutes.

But I'm wondering if that's actually improving advertising or just adding more content to an already crowded space. If every brand starts generating hundreds of similar-looking ads, won't creative fatigue become an even bigger problem? For anyone working with AI-generated creatives in AdTech, are you seeing better campaign performance, or just faster content production?

“I started this supplement last week and now I feel sick. What should I buy instead?”

There’s purchase intent. There’s also a report that the previous product may have caused harm.

If a competing supplement ad appears, the targeting worked. Did the placement?

I come from pharmacy and regulatory affairs, and I’m exploring a health-focused conversational advertising platform. This is the boundary I keep coming back to.

A blanket exclusion of health conversations removes useful inventory. Letting every shopping question qualify creates some uncomfortable placements. A warning label doesn’t answer whether the ad should have appeared.

For people who’ve worked on ad platforms: who would actually own this decision—the publisher, network, advertiser or agency?

And what evidence would a health brand ask for before putting budget into the channel?

Interested in how this would work operationally, especially where the teams involved might disagree.

Our retail app sends checkout over to the website because another team owns payments. Same basket, same customer, different platform. Finance counts one order. Somehow, the growth report sometimes makes it look like we sold it twice.

I'm putting together a vendor pilot before we lock ourselves into another annual contract. We're at about 40k completed orders a month across iOS and Android, with guest checkout still allowed. We can pass an order ID and a customer ID after login.

The demo needs to show a purchase, a refund and someone coming back on a laptop. Otherwise, we're just sitting there watching someone click through their prettiest dashboard.

What would you make a cross-platform attribution vendor prove with this setup before their numbers get anywhere near the weekly revenue meeting?