Why Intent Plus Sentiment Powered Contextual Targeting Is Winning the Battle Against Memory Clutter
Humans have a wealth of information at their fingertips, and having this ease of access has transformed the way that people retain knowledge and memories. Consumers are bombarded with content, making it more difficult than ever for brands to have an impact and increase awareness of the products or services they provide.
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As a result, consumer attention is at a premium, so brands need to find ways to engage people and stand out from the crowd. Attempting to target people with content that isn’t relevant to them will only result in businesses failing to capture the hearts and minds of consumers and, ultimately, lose out on ROI. So, how can brands gain the full attention of consumers?
The answer? Next-generation contextual targeting.
Unlocking Contextual Targeting’s Full Power
AI-powered next-gen contextual targeting enables advertisers to go beyond traditional targeting through the use of advanced, on-page semantic and sentiment analysis, as well as in-the-moment factors, such as location and device type. This provides advertisers with the means to holistically target consumers with content that is hyper-relevant, aligned to brand safe content, and respectful of the privacy of consumers, because no identifiable user information has been used.
The power of context cannot be ignored. In fact, research from IAB Europe found 69% of consumers would be more likely to read an ad if it was relevant to the content they were reading. In addition to that, 44% of them also revealed that they had tried a new brand based on the contextually relevant ad they had viewed.
By gaining a true understanding of where the advert will be placed, and the language that’s present, advertisers can develop a greater understanding of the mindset of the consumers visiting that page. This enables the delivery of ads that resonate with the consumer at a far deeper level, and in turn increases brand awareness, and purchase intent as a result.
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Considering Sentiment
Machine learning means we’re now able to accurately match the content on the page to the message being delivered. Natural language processing or NLP can be used to analyze the content based on sentiment, and help to determine how ads might be received by consumers who visit similar pages. Considering intent can further boost this sentiment analysis further.
Consumers are most receptive to brand messaging when they are being served relevant ads in the moment they are expressing intent. AI and machine learning can combine multiple live intent signals, including how users are finding their way to a web page, where they are, or the device they’re using.
This, combined with information about sentiment, and historical performance data about ads served in the same slot in the past, informs the technology on whether it’s suitable to serve a certain ad in that location at that time.
Perhaps the most important aspect of all of this data is that it doesn’t rely on third-party cookies, or any other personal identifiers. As a result, contextual targeting powered by live intent and sentiment is perfect for the present and future of digital advertising as it respects user privacy.
While ensuring privacy, next-gen contextual targeting also provides an elevated online experience for consumers. Users are only served ads that are relevant to them at the moment they are expressing intent, which supports a more streamlined online experience.
You’ve got my attention
So, we’ve ensured that ads are reaching the right people at the right time in a privacy-first, identity-free manner. But, in the privacy-focused world, an additional critical element is going to be in how consumers engage and pay attention to your ads.
When the consumer attention window is so finite, an effective approach for resonating with them is through emotion. The emotional resonance is delivered by targeting based on the sentiment and mood of a particular editorial environment.Both of these aspects of contextual analysis can now be reliably mapped to user mood allowing us to plan and target activity accordingly. Early tests of these techniques have shown clear campaign performance differences based only on inferred user mood.
Qualifying this attention will also help the measurement challenges being faced by the industry by the upcoming deprecation of third-party cookies. It presents the opportunity to turn away from the measurement metrics advertisers have become accustomed to, and start looking at more meaningful, brand-focused metrics. Indeed, these newer, attention-based metrics provide a better picture of the levels of engagement ads are actually achieving.
And whilst Google has further delayed the deprecation of third-party cookies, advertisers should still use this time to test cookie-less solutions, ensuring they are putting the privacy of a consumer first.
This doesn’t need to be a challenge, as a popular gaming company recently discovered. The campaign delivered a 62% increase in prompted brand awareness, while positive brand perception increased by 58% and brand consideration saw an increase of 121%, far more than what is achievable by optimizing click through rates.
Next-gen contextual targeting, powered by sentiment analysis and live intent signals, provides the perfect platform for any company to do this, while ensuring the right message is delivered, at the right time, in the right places. It’s all done with the added layer of reaching consumers in the right frame of mind, resulting in far more memorable campaigns.
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