Contextual Targeting Enables Marketers to Deal with Unpredictable Consumer Behavior

Contextual Targeting Enables Marketers to Deal with Unpredictable Consumer Behavior

  03:17    Silver Push

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Amid the coronavirus pandemic, marketers are witnessing a dramatic shift in the behavior of the consumers. Consumers are not behaving in the way that marketers have expected them to do. Their behavior has become unpredictable, inconsistent and erratic.

For example, consumers have stockpiled grocery items in their pantries during the lockdown period to the extent that demand has surpassed supply. Consumers have either made a large number of visits to grocery stores or frequently procured essential items from e-commerce websites. 

Marketers have observed that consumers are showing less loyalty to brands, as they are filling up their pantries by buying products they require from any brand. They just want to make sure that they have enough goods to meet their requirements for a long time.  

This new behavior pattern exhibited by consumers has a good amount of deviation from the normal consumer behavior that the marketers are accustomed to. Before the coronavirus pandemic, marketers could easily predict consumers’ behavior and show them ads on the basis of the behavioral data tracked and collected by them.

This form of advertising, known as behavioral advertising, makes use of third-party cookies and collects user data such as websites visited, webpages viewed, time spent on website/web pages, visit frequency, clicked links, products viewed, purchase history, etc. This data helps marketers to create rich profile of consumers. But in the difficult times such as the coronavirus pandemic, when consumers do not show consistent behavior, the third-party cookies and consumer profiles created by marketers fail to predict what a consumer will be interested in buying next.

Marketers also rely on geo-targeting for serving ads to users. Geo-targeting refers to the practice of delivering ads to consumers on the basis of their geographical locations. It is often used by marketers for advertising to local prospects and help local businesses that depend on foot traffic such as restaurants and brick-and-mortar stores to increase sales. But during the coronavirus crisis, geo-targeting is also not delivering success to marketers as people are refraining from going out of their homes except for essential items.

Thus, consumers’ behavioral and geographical data, which is considered highly valuable by marketers under normal circumstances, loses its importance during the times of a crisis, as its use fails marketers in achieving targeted results.  

In this scenario, it is the contextual targeting that acts as the savior for marketers. Contextual targeting has emerged as a very effective way of advertising. Contextual targeting involves placement of ads on the basis of the content the user is actively engaging with and has nothing to do with users’ past behavior, purchasing habits, and their locations. It makes use of the context of the digital content that a user is consuming rather than his or her data profile.

Traditional contextual targeting based on keywords and topics has produced results less than optimal as it involves contextual fails. For example, if an ad of a burger appears against the content talking about the harmful effects of fast food, then it will severely harm the image of the burger brand.

But this is not the case now; the advent of new technology has changed contextual targeting radically. AI-powered contextual advertising that makes use of computer vision has emerged as the smartest and the most effective way of using context for targeting audience. Through computer vision, in-video contexts such as faces, emotions, objects, logos, actions and scenes are detected with high accuracy, enabling marketers to serve ads on the basis of what the user is interested in at the moment. With computer vision powered contextual advertising, the chances of user clicking or viewing the ads are very bright. 

During the coronavirus pandemic, not only the consumers’ behavior has become erratic, they are also overwhelmed with the coronavirus content. They do not want to see brand messages appearing next to mortality-related coronavirus content. For marketers, it is a challenge to distinguish between safe and unsafe coronavirus content. Computer vision powered contextual advertising not only provides highly context relevant ad placement, but also accurately filters out harmful, unsafe or unsuitable content such as mortality-related coronavirus news. Apart from the recognized unsafe categories, marketers can custom define unsuitable contexts unique to each brand. Thus, computer vision-based targeting ensures true brand suitability.   

In crisis such as coronavirus pandemic, when consumers’ past behavior data becomes useless for marketers, computer vision-powered contextual targeting serves as the most effective way to serve ads in a truly brand suitable environment.