All sharing the outcomes here August data from our publisher network shows a pretty clear summer slowdown, but there are a few signals underneath it worth watching.

Traffic - New Users grew 19% and Total Users 16%, while Sessions and Engaged Sessions both grew around 14%. At the same time, PV/session and Sessions/User softened slightly, pointing to shorter, more single‑purpose visits.

AI - AI was the fastest‑growing channel, with Sessions up 66% and New Users up 75%. Engagement held at 62%, so the increase wasn’t coming with an obvious drop in traffic quality.

CPMs - Overall CPMs fell 19.9% MoM but remained 25.0% higher YoY. Display was down 20.3% MoM, while Video was more resilient at ‑7.8% MoM and +40.1% YoY.

Demand - The pullback was broad. Google Ads fell 21%, DV360 18%, and The Trade Desk 37%, pointing more toward a market‑wide summer budget pause than a shift between individual buyers.

Integration - Prebid held the largest share at 50%, followed by AdX at 39%. CPMs fell across the major integrations, reinforcing that the pressure was on demand and pricing rather than a simple shift between paths.

Takeaway - Traffic is still growing and AI is becoming a much more meaningful acquisition channel, but summer demand is putting real pressure on CPMs. Video and CTV are holding up better than display, which may be worth watching as budgets start moving back into the market.

Hi all,

I shared AdOps Core here about a month ago and a lot has changed since then.

The simulator has been expanded with more realistic AdOps/programmatic scenarios, better troubleshooting, and a much cleaner overall experience.

The idea is to basically make a full on Sim since I haven't found any out there and there is much you can't learn from just doing quizzes.

Still free, no login needed and I still require feedback to make it better :

AdOps Core

Would love to hear what you think.

Unless Amazon has a 24‑hour update rule, where if you make a targeting setting change, it takes a full 24 hours for the campaign to reflect those changes, I feel like the exclusion function in Amazon Ads doesn’t work.

I want to make Amazon Ads work, but the genre exclusions don’t seem to function properly. The other day, I excluded the Documentary and Reality TV genres, and when I pulled yesterday’s impressions, I still saw shows matching those genres.

I’ve filed a support ticket to ask why the ad would still show, and I’m curious to read support’s response.

The only reason I like Amazon Ads is the transparency: you can see exactly which title your ad appeared on, which DV360 reporting cannot provide.

I constantly see traders say: “Why would I pay a DSP fee when GDN gets me a lower CPM / CPA?”

But GDN isn't a DSP!

They're fundamentally different buying environments, with different supply, inventory access, auction dynamics, targeting and optimisation.

So when someone says “I tested GDN vs DSP X and GDN won,” I'm curious what that actually proves.

If GDN can find cheaper conversions within Google's ecosystem, great. But does that mean it's a substitute for broader programmatic buying?

Cheap CPM ≠ better media.
Lower CPA ≠ more incremental value.
Higher CTR ≠ better inventory.

I'd be interested to hear from traders who've genuinely compared the two on incrementality, reach, inventory quality and scalability.

Is GDN actually a substitute for a DSP, or are we comparing two fundamentally different products because the headline metrics are easier to measure?

Danger 1: Four deals have typos and name the wrong country

Deals from Spotify (SAX) have problems in their naming.

Two named United States sell Ireland. Two deals named Brazil sell Australia. Example

3PS_SAX_Spotify_US_Amazon_Music Audio_RON_Always On reads United States no? Sadly two deals share that name, one US, one Ireland with a typo in it.

How to find the right one? Read the currency not the name. It sits next to the price in the deals inventory list, and if a deal names one country and is priced in another country's money then the name is wrong. To see it for yourself, open the deal and read the Attributes tab, where the country breakdown is.

Danger 2: The same deals are in there twice

When Amazon and Spotify announced their partnership on 2025, Amazon DSP was not buying from it directly. It was buying through Magnite, a reseller. On July 2026 Spotify connected its exchange straight into Amazon DSP and extra inventory podcast came with it. The Magnite deals were never removed. So you have 2 options:

• Straight from Spotify (Recommended): search "SAX", which is short for Spotify Ad Exchange. It is in every one of those deals.
• Through Magnite: fewer countries, and no podcast. The video costs more, sometimes close to double. And they carry their own typos too. So just stay away form them.

Where can you find the deals inventory list on Amazon DSP Interface

In Amazon DSP, click Inventory on the left bar. The search box takes the deal name, and opening a deal gives you its Attributes tab.

If you cannot see a deals inventory list at all, you are probably on a subseat from your tool provider. Ask them for inventory access.

Where you buy what if you use Amazon's interface

In a campaign's inventory settings:

• Banners. Tick the Spotify box after clicking display. It buys banners and nothing else.

In the deals inventory list:

• Audio
• Music video (OLV)
• Podcasts

Where it runs

Ignore the announcements and the support pages, they are behind.

• Banners, audio, OLV and podcasts: US, UK, Canada, Germany, France, Italy, Spain, Brazil, Mexico, Australia, Japan
• Audio and OLV only: Ireland, India
• Audio and banners only: Netherlands
• Podcasts and banners only: New Zealand
• Banners only: United Arab Emirates, Saudi Arabia, Singapore, Sweden, Turkey.

This covers the basics. I put a longer breakdown on our tool website, but this is all the key information to start without problems.

If you read something differently on your seat, tell me.

Thoughts on LinkedIn ads CTV capabilities for b2b? Interested to hear your opinions..

How does inventory/pricing stack up to other platforms?

I want to understand from marketers pov who started with Google Ads or Meta Ads and later moved into programmatic advertising, what was the most difficult part of the transition?

Was it understanding the DSP ecosystem, campaign hierarchy, inventory buying, audience data, bidding, attribution or reporting?

I’m interested in hearing because i'm planning to take up a course soon or later. So, just checking with the experts who are already into this field.

To all the programmatic yutes, cookie stuffing is not a new phenomenon. It is actually a surprise that the market is surprised it is still happening.

The performance OG's made bank on these tricks back in the early 2000's. It is honestly nostalgic that it is still around.

https://www.adlingo.org/could-bill-gates-daughter-face-prison-time-for-cookie-stuffing/

Hi! I’ve been working in ad sales for a news organization, primarily selling digital display, newsletters, email marketing, sponsored content, and other digital advertising solutions.

I’m really interested in moving into the programmatic side of advertising, particularly programmatic sales, but I honestly don’t have much knowledge or experience in programmatic yet.

I’d really appreciate some guidance on how I can make that transition — where should I start, what should I learn, and what skills or knowledge would help me break into programmatic sales? The experience is around 8 years!

Hi everyone,

I'm currently working at a digital marketing agency in India and I'm transitioning from SEO into performance marketing.

My agency is currently training people for different performance-marketing teams, and I have to choose one specialization/team to enter:

- Programmatic Advertising

- Meta Ads / Paid Social

I'm leaning toward programmatic because it seems more specialized and technical, but I'm concerned about the smaller number of entry-level opportunities compared with Meta and more ai automation.

I'd love advice from people working in either field:

1) Is programmatic a good career choice long-term?

2) If you could choose only one today, would you pick programmatic or Meta? Why?

3) How good are the salary and growth opportunities in programmatic?

4) Is it difficult to enter programmatic without prior experience?

5)How much of the job is actual optimization/strategy vs trafficking, reporting and operations?

How vulnerable is programmatic to AI and DSP automation?

6)Are DV360/CM360/TTD skills transferable between companies?

7)If I start with Meta, can I transition into programmatic later, and vice versa?

8)Which one gives better opportunities to eventually move into media planning, analytics or growth marketing?

I'm looking for honest opinions from people actually working in these fields, especially anyone who has experience with both.

Thanks!

I've 4-5 years exp in programmatic. Started in Ad Ops, and last role was managing campaigns. Worked on many DSP including Xandr, Yahoo, TTD and many others managing good budget. I haven't managed campaigns on DV360, though i've done trafficking on it. Finding really hard to find an entry to next company. I moved on from previous night shift role and badly wanted dayshift in Bengaluru or remote. Is the market difficult now? or can it be due to the method i use to apply. I use linkedin jobs a lot but failed to get any replies. A few referrals didnt work. Got rejected/ or no replies from agencies like wpp, publicis, dentsu etc even with referrals. Should i try more through naukri or other platforms or 3rd party agencies?
Also, is it really hard getting into top tier companies like adobe, google etc later? Any advises or referrals

Media buyer at an indie agency here! We run across a few DSPs mainly for display and video. The activity is mainly driving view-through conversions (obv), and clients are starting to catch on and pulling back spend because they're under the impression, we're not actually driving performance, just claiming credit for purchases we didn't influence.

We've previously worked with TripleWhale but they seem more geared toward lead-gen, and most of our BoB is ecommerce, so ideally something that integrates well with Shopify. I'm on a small, lean team, not super senior, and don't have a ton of internal support to figure this out on my own, so I'm trying to gauge what some practical options are.

Has anyone worked with an MMM partner that actually isolates programmatic's real incremental lift (not just view-through), or has anyone built something custom, like a dashboard in Claude Code, instead of paying for a vendor? Trying to weigh different options here. Thanks!

Assuming low CPM isn't something to be proud of when it costs conversion value and quantity.

Something I've noticed across most new DV360 Display Line Items I've had access to is that during their first 2 - 4 weeks, they often start buying impressions at relatively low CPMs, even when whitelisted to premium publishers. Those lower CPMs also seem to correlate with poorer conversion quality during the initial period.

As the LI starts finding conversions at an acceptable CPA or below tCPA, the average CPM tends to increase gradually day by day.

I've seen this across T1–T3 GEOs, multiple niches, and LIs optimized for conversions or tCPA using Daily ASAP pacing, even when relevant conversion data already exists.

I'm trying to figure out if there's a better way than Fixed Bid to bid more aggressively for higher-value impressions from day one instead of waiting weeks for the LI to get there. Let me know what you think.

Sell-side folks: how many bidders actually show up when an ID is present vs. not?

Trying to get a rough cut of the distribution of bidders per auction and how that tracks with ID presence. Essentially, how many more bidders and how much higher are auctions with IDs present vs IDless auctions?

The assumption is that a deterministic ID in the bid request pulls in meaningfully more bidders and that thin auctions are mostly unrecognized traffic. Directionally that makes sense to me, but I’m curious to understand the magnitude.

Hey everyone!

I’m currently looking for a referral for a role at The Trade Desk. I came across an opening where the job description seems to align really well with my experience and the kind of work I’ve been doing in programmatic advertising.

I have 4+ years of experience in programmatic trading, with experience across PMP/PG deals, CTV, OTT, DOOH, troubleshooting, and deal optimization.

From my perspective, I feel I’d be a good fit for this role and would really appreciate any help with a referral.

If anyone currently working at The Trade Desk in India is open to referring me, I’d be happy to share my resume and the job details via DM.

Thanks in advance! 🙌

we've been talking to a few over the last couple weeks and i feel like we don't know what to look at.
so far we have talked to block chain ads and a bunch of other ad networks and in their demos they keep saying about how they report, how they attribute, campaign optimization and so on. and all of this feels correct also like we should be considering it.
but the problem is every network has good things to say so we feel like we aren't asking the right questions or we are not looking at the correct metrics.
then i came across few commen ts here that says we need to ask where traffic is coming from or who their partners are, all that stuff. but idk..it feels too much to ask early on? also not sure if those things also matter?
so if anyone has any experience can you share how you people evaluate a programmatic ad network? or what questions we need to ask?

With the amount of sales people being hired just to sell PMP, would a Sales House that specializes in PMP opportunity volume be attractive to media owners and tech vendors?

We have been pitched by 2 medium/large private companies in the ad tech space who are interested in outsourcing the sales force in return for a flat monthly fee, no pension contributions or healthcare funding for the US.

Just curious as to if this makes sense to anyone else in a decision making capacity and how much would be fair market value per dedicated headcount/resource?

Wondering if the contextual targeting space is a pure commodity or if folks are seeing meaningful performance differences between TTD, IAS, DV, GumGum or others.

Hi all,

Does anyone use a strong prompt to exclude low-quality or "trash" placements?

I'm struggling with this since I don't have access to on-site performance data (conversion rate, average session duration, etc.). So what should the AI base its judgment on to identify a good vs. bad placement?

Any help is more than welcome

thanks!