The competition for consumer attention is saturated. The average person is barraged with 1,700 banner adverts online per month, but they see only half of them. Brands are using cutting-edge predictive visual analytics tools to win the competition for attention – but what exactly is predictive visual analytics and how do brands use them?

Put simply, predictive visual analytics is the use of data to gift us foresight on performance. With significant innovations in the field, we can use this data to make informed decisions, and to be pro-active, rather than reactive.

Visual analytics vs predictive visual analytics

At its core, visual analytics is the integration of data-analysis processes with visual representation. This has opened the door for businesses to decipher complex information, previously a daunting task for many people who are not data-scientists by trade. Products in this market are generally concerned with visualising datasets to effectively gathered data to spot patterns and test approaches so actionable insights can be made.

In contrast, predictive visual analytics is the formation of future results. In essence, it extends from visual analytics use of historical data and combines it with dynamic algorithms so we can accurately predict performance without only being able to act on insights once data is obtained. Commercial uses are most common within marketing optimisation, where designers and marketers make data-informed decisions on content and customer journeys in pre-publishing stage. In the next section, we will look at just how this works.

Using predictive visual analytics in design

Dragonfly AI harnesses predictive visual analytics to provide real-time, actionable insights which predicts the effectiveness of content with extreme accuracy. By running any form of marketing content through Dragonfly AI’s products, marketers and designers can effortlessly fore-see performance, prior to publishing.

The product uncovers what is grabbing consumers attention, using cutting-edge neuroscience technology. By running content through our product you can visualise what is gaining attention via our predictive heatmaps.

The example below is the Dragonfly AI Chrome extension analysing competing products in an online marketplace in real-time to accurately predict which is optimally capturing consumers attention.

From the heatmap, it is visible what regions of this e-commerce marketplace is grabbing consumer attention the most effectively. Using the Dragonfly AI Chrome extension to specifically analyse the competing product images, we can quantitively conclude which product is optimally winning consumer attention.

Rather than using and reacting to historical data on performance to optimise this content, brands can test and optimise their content pre-publishing, to generate accurate insights and win against competitors.

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