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Weekly Roundup: Best Buy Media Network, Keyword Blacklists, Audience Networks.

Adtech Weekly Roundup
“Ultimately, we want to move away from keywords [blacklists] entirely. But we get that not everyone will trust Mantis overnight. We want to prove the concept to the market.”

Best Buy Aims to Take a Swing at Amazon

Best Buy is next on the line after Target to go head-on-head with Amazon advertising. We’ve discussed Target’s rebranded media company ‘Roundel’ and how it capitalizes on the first-party data to run campaigns on its own media network. Precisely, we wrote:

“From TV to channels, Target’s Roundel offers a well-rounded advertising tool for marketers. Most importantly, Target will capitalize on its in-house first-party data to deliver better results for the brands and agencies.”

And, here’s something for you to ponder this week –  Best Buy Media Network, a media buying wing from Best Buy has begun to increase its efforts to roll in advertisers recently. And, guess what’s the value proposition – First-party data. 

Best Buy claims to use its first-party data gathered from 1.5 billion customer interactions, 2 million daily web visits, purchases, etc. to help advertisers to set up, run, and optimize campaigns for delivering the best ROAS (Return on Ad Spend).

What’s the deal with first-party data?

If you read last week’s roundup, you can see that almost all the news is related to first-party data and how the declining third-party cookies across different environments are posing a serious threat to digital advertising (especially, for the open web).

While the consortiums and regulators are coming up with frameworks and advertising technologies are adapting to either use unified IDs or utilize first-party cookies to measure and attribute, there’s no complete cookie-less solution yet. So, user data is becoming scarce and retailers like Amazon, Target, and now Best Buy are capitalizing on the situation – with customer behavior and purchase data. 

Takeaway:

While marketers and agency directors agree that Best Buy wouldn’t be able to attract many advertisers like Amazon, it can help media buyers who’re looking to target the niche audience that it has access to. More and more agencies and programmatic buyers are looking for first-party data to support the campaigns and the trend is likely to continue in the upcoming years. See how you can accumulate your audience data and use it as leverage.  

Social Platforms and Audience Networks

We know that publishers can become a part of an ‘audience network’ ran by social media platforms (for instance, Facebook/Twitter). The idea is quite simple. The walled gardens would like to lock-in as many advertisers as possible to their platforms. Though they can reach billions of users, advertisers will likely run ads on the open web too. In order to help them target the users off their platforms, social networks build audience networks. 

An eligible publisher can join the network and then allow Facebook’s or Twitter’s advertisers to run ads on its website. For example, Facebook Audience Network (FAN) is one of the well-known audience networks that can be added to your header bidding wrapper directly. This, in turn, allows Facebook advertisers to bid on your impressions and run ads on your property. 

Opportunity. But for whom? 

A recent AdWeek piece highlights one of the drawbacks of audience networks. Typically, a publisher looking to intensify the auction will indeed add, as many demand partners as possible. But, who’s actually benefitting? 

It is apparent that social platforms are extending their reach into the open web (our ads.txt study proved the same) and it helps them to retain advertisers.

However, advertisers wouldn’t be able to get past the audience network and connect directly to the supply (web publishers or apps) if they want to. The social platforms don’t disclose the third-party sites and apps on which the ads are being run. 

In addition, publishers wouldn’t be able to access granular reports as they typically would on other networks. Audience networks reporting API won’t reveal the brands that bought the impressions, preventing sellers from identifying opportunities to ink a direct deal. 

Most importantly, it is has been observed that the cost of acquiring the targeted audience is way less on publishers’ sites as compared to the cost incurred on these social media sites. So, your CPMs from the audience networks stay more or less the same. 

Takeaway:

It’s better to carve out the efficient route to demand yourself. Publishers shouldn’t flock towards audience networks without analyzing the long-term impacts on revenues. That being said, if you would like to have them as a backfill, then start prioritizing the ones that provide you better transparency and deeper insights, and data. 

ITP Starts to Impact Affiliate Revenues

Tracking prevention features from browsers have started to affect the publishers’ affiliate revenues. As you know, browsers including Safari and Firefox have updated their tracking prevention features to block third-party cookies by default and prevent any technology to track users across the sites. 

It’s been preventing both advertisers and publishers to run personalized ads and now, publishers who rely on affiliate revenues seem to get the heat.

Digiday talked to several publishers last week and most of them have no answer to how they’re going to attribute and earn revenue for the sale in the cookie-less (third-party) environments. 

Background:

Publishers plug into affiliate networks to pull in the products and use affiliate links to earn a commission for whatever they sold within the specified timeframe. When a user clicks on an affiliate link to get to the advertiser’s site, a third-party cookie will be dropped. The cookie will help the affiliate networks to attribute the sale to the publisher. As ITP blocks all sorts of third-party cookies, there’s basically no way to attribute a sale. 

Alternatives to third-party cookies:

Sometimes, a publisher can’t utilize the first-party cookie as Safari’s ITP 2.2 shortened the persistence of 1st party cookie to 24 hours from seven days. 

“A 24-hour window is not enough, and even if the user, inspired by the article or review, made the purchase on the advertiser site, our technology wouldn’t be able to track it. The publisher wouldn’t receive the commission they deserve.”

– Adam Ross, chief operating officer at Awin.

So far, a few affiliate networks are offering ways to still send the information to the advertisers’ servers to make it feasible for publishers to get attribution. But there’s no clear picture yet. Similar to advertising, everyone knows the direction and lacks the technology or accepted protocol.

Takeaway:

As affiliate is still a small portion of the overall revenue, publishers don’t have the scale to implement an alternative, compare the numbers, and get to a conclusion. If we are certain about one thing, the impact of ITP isn’t restricted to the advertising industry. 

Time to Cleanup Keyword Blacklists

One of the prevailing issues of online advertising is how the keyword blacklists are used without understanding the context. As a publisher, you might not be able to monetize a chunky portion of your traffic because of the usage of blacklisted keywords on the pages.

Blunt and Inefficient

Blocking keywords to ensure that the ads aren’t appearing in the non-brand-safe environment is not at all efficient for both buyers and sellers.

Several agencies and publishing executives have raised concerns regarding how the credible and brand-safe pages are blocked from serving any ads – just because they’ve used one of the keywords in the blacklist in a completely different context. 

Previously, news publishers were getting affected due to the use of political keywords, but recently content creators spanning across sports, entertainment, art & culture, etc. are also experiencing the loss of revenue. For instance, a sports article mentioning ‘shoot a goal’ will be blocked as ‘shoot’ is a blacklisted keyword. Similarly, in the past, ‘Manchester City’ was blocked for months because of the bomb blast happened in the city. 

Meet, Mantis.

Reach (formerly known as Trinity Mirror) partnered with IBM’s Watson to create a tool called ‘Mantis’. Watson will use machine learning, natural language processing, and visual recognition to identify whether the article is appropriate for advertising and flag the ones that have been blocked. 

Takeaway:

“Ultimately, we want to move away from keywords [blacklists] entirely. But we get that not everyone will trust Mantis overnight. We want to prove the concept to the market.”

– Terry Hornsby, digital solutions director at Reach.

The majority in the industry acknowledge the fact that keyword blacklists aren’t effective and it can block 30% to 60% of the traffic. In fact, one publisher revealed almost 90% of the campaign impression can be blocked depending on the keywords and the tech used.

Short-term strategy: Analyze your content and try to avoid the blacklisted keywords. Long-term: Push your advertisers to move beyond standard blacklists and embrace the tools that are proven to help you convey the context. 

Moments that matter

California AG Drops Highly-Anticipated First Draft Of CCPA Implementation Regs – AdExchanger. 

The News Revenue Hub is launching a pilot project to help news orgs increase their readers’ loyalty – NiemanLab

To reduce auction duplication, buyers start to enforce sellers.json – Digiday

Ad-Tech Experts Call for Third-Party Verification After the Death of the Cookie – AdWeek.

Automatad Team

At Automatad, we help publishers to monetize better without hampering the user experience. Our products are live across hundreds of publishers, earning them incremental ad revenue with every passing second. You can request a free audit to get an estimated revenue uplift today.

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