Less BS, More Facts, Some Opinions
Here’s today’s AdExchanger.com news round-up… Want it by email? Sign up here. Amazon Prime(s) Its SSP Play Based on its job listings, Amazon is getting ready to launch a supply-side
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On the surface, the verdict on made-for-advertising sites (MFAs) seems obvious. These sites flood users with disruptive ads, masquerading their intentions behind a thin veil of valuable content.
Yet, scratching beneath the surface reveals a more complicated picture. Marketers, surprisingly, argue that these sites can serve a purpose, as long as there are effective mechanisms in place to ensure transparency and quality control.
But before we unpick this rationale, let’s rewind and remember what MFAs are: Imagine a webpage drowning in towering banner ads and strategically placed video players, transforming browsing into a chaotic commercial nightmare. To a critical observer, this mishmash of intrusive ads and dubious content might seem like a digital apocalypse. However, lurking in the background, the algorithms responsible for ad placements consider these sites to be prime opportunities. They’re more visible and budget-friendly compared to other ad options. Naturally, advertisers would jump at the chance to purchase such ads.
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Artificial intelligence has the advertising industry bewitched, with agencies and clients alike clamoring to understand what AI can do for their strategies and marketing stunts.
While provocative, the industry doesn’t seem to have a standard or definition of AI and what it all entails. “I haven’t come across anything that says, ‘This is the standard on what AI is,’” said Annmarie Turpin, chief technology officer for Ocean Media’s analytics team. “People read lots of definitions of AI and then infer, ‘Well, this is tangentially related.’”
To help give some understanding, Digiday compiled a list of some of the key terms in AI that are frequently used in the ad industry. This is by no means an exhaustive list, but provides a glimpse into some of the words that are either new or increasingly prominent in the marketing lexicon.
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With games media at a crossroads, two journalists who cut their teeth in esports are leveraging their organic connections to the gaming community to kickstart a collectively owned media operation.
As the games media space has contracted over the past year, many observers have speculated about the viability of a collectively owned publication staffed by leading games journalists — in other words, a “Defector for gaming.” As of today, Jacob Wolf and Mikhail Klimentov are giving it their best shot.
Both journalists have made a name for themselves within the industry — Wolf through his reporting at ESPN and his production company, Overcome, and Klimentov through his editorial work for the Washington Post’s Launcher gaming vertical and his newsletter, ReaderGrev.
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As publishers develop generative AI tools for their newsrooms, they have two primary choices when deciding what to build upon: open-source or private large language models (LLMs).
Chatbots like OpenAI’s ChatGPT and Google’s Bard are built using private and proprietary LLMs, or systems that are trained on large amounts of data that learn to generate text.
On the other hand, open source is computer code that can be freely used and modified by anyone on the internet. Open-source LLMs allow publishers to download that code and fine-tune the models for specific tasks using their own data, as well as see what the model was initially trained on and examine the model for any potential limitations and biases.
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Football season is upon us, which makes every sports media buyer — and fans across the U.S. — jump for joy, given the relative paucity of other sports to watch in the summer (sorry, baseball, you’re still too slow).
But this summer, a few developments in secondary sports (notably, the other football) have given marketers and their media agencies some alternatives to consider investing in — ones that are more cost-effective, draw more passionate and engaged audiences and are rising in popularity.
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Prior to 2020, Prudential’s ad spending was erratic. The brand would spend for a short period around a campaign and then stop when said campaign period was over. Then it would rinse and repeat that process.
In recent years, Prudential has retooled its approach to be more even with spend which in turn has led to efficiencies, according to chief brand officer Richard Parkinson, who credits the shift to the brand’s in-house media team.
“The one biggest change we’ve made is consistency,” said Parkinson. “If you look at our spend, previous to 2020, it was very on/off, on/off, on/off and what we’ve brought is a much more consistent spend to our media. You’ve got to be there when people may need you. Consistency has worked in our favor.”
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