In a world where companies are trying to promote their products to an audience whose needs are changing rapidly, contextual advertising serves as a launchpad to convey brand stories. They help companies seamlessly integrate their ads with the website content and context, eliminate wastage of impressions, yield better results, and enable brands to meet their marketing objectives while respecting the data privacy needs of users.
Let us imagine a situation: It is a Saturday morning and you have a long day ahead of yourself. You want to try a delicious cookie recipe but have not found the time. So you start browsing for a recipe and an ad of a ready-to-make cookie brand catches your eye. What could be better than such a delightful quick fix for your sweet tooth?
Well, good luck with your cooking experiments but, what you saw there was not a mere coincidence. It was a well-thought-out contextual advertising strategy. This strategy placesan ad on a website where it blends well with its surrounding content, thereby optimizing messaging, audience selection, and the overall ad placement. The flow between the content and the ad helps grab a user’s attention without being intrusive.
Acing the marketing game: Contextual vs. Behavioural
Sans contextual advertising, non-intrusive ad experience would not have been the same. A mere click on one ad or a harmless search for cookie brands would have meant an ad following you around as you jumped from one website to another. So, if you searched for a recipe, you might end up seeing the ad everywhere, including irrelevant places like websites related to books, computers, or clothing etc. This is called behavioural targeting.
Behavioural targeting uses cookies that track a user’s browsing history details like pages visited, web searches, links accessed or past purchases. So, these ads are usually displayed without any thought on placement based on the assumption that the computer and user remain the same, which may not always be true.
“Contextual advertising helps identify trending keywords and reach customers through a human-like analysis of the content (including text, video, and imagery), their combination, and placement to be able to embed an ad that matches the content and environment of a page.”
It elevates the ad experience and relevancy by additionally looking at sentiments, sub-categories, brand suitability, and brand safety. This makes it a better fit as the likelihood of a person responding to an ad increases with improved relevance, context, and storytelling. It also increases ad recall and purchases intent through enhanced sentiment analysis. Another key factor it ensures is brand safety by keeping ads away from blacklisted sites and inappropriate content.
Why cookies might not cut it anymore
While cookies help advertisers understand behavioral data and browsing history to display ads, this strategy might not bear fruit in the long run as the fight for data privacy increases. Customers are becoming increasingly aware and companies are taking steps to ensure customers have better control over their data.
Google plans to phase out the use of third-party cookies by 2022 with other companies likely to follow suit as well.
“A 2020 McKinsey report saw 71% respondents say that they would stop doing business with a company if they felt their data was being compromised. ”
The world is being pushed to adopt a cookie-free future and this is where contextual advertising emerges as the true winner. With zero reliance on customer data and increased focus on creativity, relevance, and context, contextual advertising is the perfect answer to advertisers in a cookie-less world!
How has contextual advertising evolved and where is it going?
Contextual advertising has really come a long way. Earlier, the act of placing an ad was a one-time exercise based on certain matching criteria. But now, ads can be dynamically updated based on any changes made to the content and context of the page. New pages or websites can be targeted and the relevant ad format can be updated. With the power of Artificial Intelligence (AI) and Machine Learning (ML), the overall context can now be understood in real-time with human-like precision.
“The meaning of ‘context’ has also transformed over the years. Today, sentiment analysis and advanced algorithms can ensure that negative connotations are understood well.”
AI and Natural Language Processing (NLP) technologies help companies to:
- Look beyond keywords and consider aspects like avoiding negative associations.
- Filtering out competitors.
- Targeting specific locations.
- Distinguishing between homonyms, resulting in optimal budget usage.
By leveraging ML technology, today, ads can adapt themselves to suit different sentiments. The ads can be changed dynamically as per different formats like image, video, and in-screento look appealing to end-users, without any dependencies on user data, increasing brand safety as well. With this, advertisers can create ads that are relevant, compelling, smart, and rate high on user experience.
