Home Daily News Roundup For Attribution, Approach With Caution; Do RMNs Secretly Hate Standards?

For Attribution, Approach With Caution; Do RMNs Secretly Hate Standards?

SHARE:
Comic: Stop Setting Money On Fire

Here’s today’s AdExchanger.com news round-up… Want it by email? Sign up here.

General Attribution

Not all brand operators have the time – or inclination – to wade into the technical thickets of attribution.

So here are a few useful, loose rules that brands at various stages of development can follow, courtesy of Alex Greifeld’s ecommerce marketing newsletter, No Best Practices.

So-called “level 0” brands don’t even need to worry about attribution, because they’re too green to even know how to drive new customer orders profitably and predictably.

Moving on, “level 1” brands rely on one channel for customer acquisition. It might be YouTube or TikTok, but most of the time it’s one of the apps in Meta’s fleet. These brands should use in-platform reporting to track their business results.

“Level 2” brands have at least one solid support channel – like influencers or YouTube – driving the core of their advertising on Meta.

“You can then pick ONE attribution methodology to help you make that decision,” Greifeld writes, whether it’s a plug-and-play model, custom model or experiments. And then stick with it for at least six months to a year.

And lastly, you’ve got “level 3” brands, which are rarely DTC. They involve store distribution and more complex physical supply chains, not to mention brand ecosystems built around diverse media.

“Level 3 brands probably should pick ONE attribution methodology and stick to it, but that rarely happens,” Greifeld laments.

We Stan For Standards

What’s stopping retail media standardization? 

It isn’t such a massive technical lift, after all. But many retail media networks (RMNs) aren’t particularly interested in standards, because they do quite well by operating as walled garden black boxes.

“Marketers need to be able to make apples-to-apples comparisons between RMNs,” writes ANA EVP Bill Duggan at Ad Age. “That could potentially lead to greater spending for the overall category, with a rising tide lifting all boats if RMN spending drives business outcomes.”

But that “if” is carrying a heavy weight.

There is a common bad practice whereby RMNs tag users or cookie IDs on garbage-y made-for-advertising sites or other cheap, low-level inventory that doesn’t drive results for the brand. But the retailer can then claim credit on any purchase within an attribution window.

In that way, retailers can effectively take credit for organic sales – which a brand would have made anyway – because RMNs get paid by conversions.

Not all RMNs take advantage of this easy malfeasance. But retail media standards may not be a rising tide for all boats, which is why change has been slow.

Putting the “Rizz” in Plagiarism

If you can’t beat ’em, pay ’em.

That’s the strategy AI company Perplexity seems to be using to stem the tide of recent plagiarism accusations lobbied at its large language model.

The Verge reports that Perplexity is launching a “Publisher’s Program” that will share ad revenue whenever one of its products features content from its partners.

Those partners, which so far include Time, Fortune, Automattic and Entrepreneur, will also get a free one-year subscription to Perplexity’s Enterprise Pro tier in addition to some other perks (if you consider access to AI products a perk).

No word on whether this crop of publishers will also include Forbes or Wired, both of which very publicly accused Perplexity of plagiarism. (In Wired’s case, it was alleged plagiarism of a Wired article about Perplexity’s history of plagiarism!)

But for those pubs that are participating, something is better than nothing.

In the words of Automattic CEO Matt Mullenweg: “It’s a much better revenue split than Google, which is zero.”

But Wait, There’s More!

Yahoo will start selling programmatic ads for Disney and Spotify podcasts. [Axios]

Meta is running ads for illegal drugs on Facebook and Instagram. [WSJ]

Songwriters are getting screwed over by streaming media. [Variety]

The Senate passed new kid-focused online privacy bills, KOSA and COPPA 2.0, by a 91-3 vote. [WaPo] After the Senate vote, presumptive Democratic presidential nominee Kamala Harris voiced her support for the bills and urged the House to pass them, too. [tweet]

Must Read

Single continuous line drawing robot riding pencil rocket flying in the sky. Tech education and creativity. Future technology development. Artificial intelligence. One line design vector illustration

Q3: Omnicom’s Media Business Is Growing, But Is It Agent-Proof?

If AI agents can plan and buy media, who needs a holding company? Good question. It came up during Omnicom’s Q3 earnings on Thursday.

Netflix Touts New Measurement Capabilities As It Struggles With “Modest” Engagement Growth

Netflix’s revenue grew 12% YOY to $12.9 billion in Q3, which it maintains is in line with its forecast. Its ads business, however, is lagging slightly compared with expectations, causing Netflix to tweak its forecast for the rest of the year.

Apple Publishes Its Plan To Wipe Out Web Tracking

Apple is coming for identity resolution. WebKit’s latest tracking crackdown targets the infrastructure behind post-cookie IDs – and switching to a first-party setup won’t necessarily spare vendors.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

AI Slop Sites Are On The Rise. Is Ad Tech Ready For Its New MFA Challenge?

Advertising supply chain intelligence company DecryptAds uncovered more than 2,100 AI-generated recipe sites that are monetized with programmatic ads and feature fabricated author profiles.

How Australian Home Lender Lendi Measures The Invisible Work Of AI

Most brands and businesses are trying to figure out how to improve their metrics when it comes to AI – and also what those metrics even are.

AI Startup Minerva Built An Agentic CDP, But Don’t Call It That

Minerva wants to turn fragmented customer data into something marketers can use, with AI agents doing the work behind the scenes.