Why the Future of Ad Measurement Will be Attention-First
This article originally appeared in ExchangeWire.
We live in a world where there are distractions and entertainment everywhere. As soon as you wake up and check your phone or turn on the TV, you’ve already been engaged with brands and advertisers before you’ve even had your first cup of coffee.
For advertisers, there’s a constant battle to stand out. As consumers get used to ads, they don’t even see them in the first place. Most of the time, ad budgets are spent in the hope that someone will pay attention to an ad, but with very little guarantee that the ad will get noticed.
For digital ad campaigns, this means optimising ads for “viewability” so that they will appear on websites, channels, and platforms where there’s as much traffic as possible. But better viewability doesn’t necessarily mean better results: at Lumen, our data shows that only 30% of viewable ads are actually seen. That means that about 70% of your advertising budget is wasted on ads that may have rendered on a website but still didn’t actually attract any real attention.
This is why one of the most exciting areas of advertising innovation is all about attention technology that can help advertisers better optimise for what consumers will actually see. With biometric attention datasets based on real-world eye-tracking technology and predictive attention models, it’s possible to integrate attention technology into your existing advertising technology tools to drive higher ad efficiency, brand lift, and return on ad spend – and, at the end of the day, waste a lot less money on unseen ads.
That’s all because attention technology is based on a context-first measurement model, no cookies needed – and by changing the way we measure advertising, we can change the way we optimise every campaign and user experience.
Going beyond cookies
Traditionally, digital advertising has been powered by third-party cookies. The easiest way to understand cookies is if you go shopping on a website for shoes and, later, see those same shoes in an ad on a different website. Cookies enable tracking across websites, channels, and platforms. Many marketplaces also sold and repurposed user data such as demographics, buying behaviour, and location to create more personalised ads for different audiences.
Today, Apple’s Safari browser and Firefox both block third-party cookies by default. Google Chrome, which dominates the market, is expected to discontinue cookies within the next few years. This new focus on privacy isn’t limited to desktop browsers and mobile browsers – identifiers are getting blocked on apps as well.
When apps can’t track behaviour beyond the app environment, it makes it harder for companies like Meta to measure whether an Instagram ad drove a purchase on a different channel. Mobile privacy updates from Apple are estimated to have cost Facebook, YouTube, Twitter, and Snap $10 billion in lost revenue just by adding a pop-up for app users that asks whether those users want to be tracked. If users decline tracking, it’s impossible for companies to create a unique identifier that builds up specific user profiles and target them with more personalized ads.
When attribution becomes difficult, personalization gets harder, so ads become less relevant. That’s why it’s time for advertisers to focus again on the context of the ads, rather than the identity of the user. And that all starts with understanding how consumers pay attention in different environments.
Context vs. Cookies: A Case Study
Contextual advertising is all about the user experience in a particular domain. When you can make the user experience better, they pay more attention to both the content and the ads around the content. With attention technology, companies can create media planning strategies based on attention metrics, including average view time, views, attention per impression, and attentive cost per impression. Rather than paying for impressions based on whether they get delivered to a website, these solutions help ensure you are paying for the cost of attention itself based on the likelihood someone will actually see and focus on the ad on different domains.
In this way, attention technology offers a new layer of measurement that can help advertisers optimize their campaigns without tracking users.
When Kia wanted to launch a new car in the Netherlands, the company decided to try both cookies-based and contextual advertising. By advertising with partners Seedtag, Havas, and Lumen, the team found that contextual advertising drove +43% higher brand awareness compared to +18% for cookie-based ads and scored +29% higher digital ad recall. By optimizing for the factors that drove higher attention scores, rather than audience identifiers or pure viewability, Kia was able to prove out a contextual advertising model that didn’t depend on cookies and drove better results.
Without the ability to track users across partners or measure the impact of ads based across fragmented systems, companies will have to prioritize a context-first approach to both measurement and optimization. By powering contextual advertising with attention technology, advertisers can build campaigns that actually put the user experience front and center simply by understanding what really gets consumers to focus on an ad in a specific environment. And when the user experience is better, consumers pay more attention to everything within that experience – offering better outcomes for publishers, advertisers, and the future of the internet itself.