Despite Google delaying the end of third-party cookies due to the protests of an unprepared industry, plans are still very much underway, with major website browsers announcing they are disengaging altogether from third-party cookies.

This new turn of events in the Internet world is causing digital marketers some angst. With the prospect of losing sight of a fundamental method of understanding consumers, marketers are now searching hard for new innovative and sophisticated ways to understand and reach their target customers without the use of third-party cookies. Setting aside the challenges of banning cookies, there are glimmers of hope, if we take recent research from Deloitte for example:

Consumers align trustworthiness (83%), integrity (79%) and honesty (77%) with their favorite brands, three factors not attainable through the use of cookies. In fact, according to Deloitte, the removal of cookies can enable businesses to actually strengthen their customer relationships and drive future growth with long-term results.

While all that sounds fine, the question that remains is “how`’?

Read on to find out how Dragonfly AI can be used to help fill some of the data gaps produced by the removal of third-party cookies.

Attention is the New Currency

Now that brands will have to position their marketing efforts in a way that is privacy-friendly, they must explore other tools to help understand the behavior of their online customers. The competition for consumer attention is more significant than ever, given the average consumer is bombarded with around 1,700 banner adverts online per month it perhaps comes as no surprise that they only really see half of them.

So, what exactly determines whether your ads are going to get spotted and what sets these adverts apart from their peers? Part of the answer lies in predictive visual analytics – A new generation of AI-powered tools has emerged, designed to predict creative performance before anything gets published; which have become hugely valuable in the wake of our post pandemic digital behaviors.

Put simply, predictive visual analytics uses data to provide us with instant human equivalent foresight on performance. With the help of AI technology based on the system one neuroscience used by the human brain, we can then apply this data to understand predicted performance and make better informed creative decisions.

Predicting performance

Traditionally, historical data has been used by brands to gather performance insight into how many users had viewed, clicked, and purchased their content. With Dragonfly AI, marketers can instantly assess the saliency and impact of designs way before they reach a user interaction, ensuring brands deliver optimum visibility and sales.

This is carried out using a feature known as predictive heatmaps, these heatmaps provide a clear visual representation of where attention is being grabbed and where distractions may be diverting attention, helping designers to optimise their designs to be as effective as possible, without long and costly user testing cycles.

Testing, testing, testing

So, in a cookie-less world brands will have to rely more on rigorous testing to identify what resonates with their audience. Current testing processes rely on historical or real-time data to understand how content is performing in the real world.

With Dragonfly AI, however, we provide predictive A/B test before the launch. Brands can test as many as 26 different design variants, simultaneously, to optimise their performances way ahead of launching ads into the real world. This is without the need of any tracking analytics.

We don’t know what the future will hold for the end of third-party cookies, but we do know that marketers need to embrace new privacy-centric strategies if they want to build trusted relationships with their audience.


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