Using Facial Recognition To Personalize Ads

Using Facial Recognition To Personalize Ads – In the words of Malcolm Gladwell, marketers in 2020 have finally reached the ‘tipping point’ where scalable hyper-personalization of marketing activities is not only possible, but is rapidly becoming a requirement in order to stay up with evolving consumer trends.

The shift to more towards personalized, targeted shopping experiences is largely due to the advancements in marketing technology, with elements of machine learning, artificial intelligence and biometric identification all becoming more integrated with one another in order to deliver customized promotional opportunities.

An example of this can be found at the Westfield shopping complex in Shepherd’s Bush, London – the complex now has cameras in and around the mall which use facial recognition technology to determine the age, sex, and even the mood of the shoppers as they move through the buildings.

Based on what the system learns, it can then display different ads on the various digital billboards around the mall in order to maximize consumer response.

In today’s digital era, with the advent of such engagement technologies, we are now at a stage where account-based marketing (ABM) and personalization have become more practical and scalable than ever before.

With automation and machine learning tools working in tandem, even a small company can run a comprehensive ABM operation, serving the largest possible clients.

As a digital B2B and B2C marketer, I find this very interesting, and have been pondering how these same types of technologies and ideas can be used to hyper-personalize digital marketing communications using the combination of internet and mobile technologies.

For the past few years I’ve been entrenched in personalized email campaigns, cart abandonment email programs, Facebook custom audience ads, and other forms of personalized marketing strategies, but so many brands are running these same campaigns that they’re beginning to lose their luster.

RELATED: Tracking Facebook Ads With URL Parameters

Think about the recommendation engines that both Amazon and Netflix have built – these engines work so well that they’ve catapulted these companies ahead of the rest, because of the way in which they’re able to personalize your experience so well when you use these platforms.

They know almost exactly what I want to buy or watch next, and can be so accurate that, at times, it feels like they’re reading my mind. That’s the type of hyper-personalized marketing that all companies need to aspire to, in some way.

Many companies are, indeed, improving their efforts on this front. A recent Gartner study revealed that companies which are investing in online personalization technology are outselling their counterparts by approximately 30%.

The buzzword for 2020 should be ‘hyper-personalization’ – the harnessing of all forms of data being used in unison across all marketing channels and customer journey stages. Embracing this approach is going to move customers from top of funnel awareness to post-purchase happiness in record time through higher and more effective engagement at every stage.

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