Now that the Big Data mindset has permeated the business world, company decision-makers have learned to expect quick and ready access to the valuable insights created by data analytics. But no matter how great the volume or velocity of data, those insights simply aren’t available if the information is unintelligible. The strength of a retail analytics platform depends on the quality of its presentation.

Consequently, progress in the realm of retail intelligence has naturally focused on the ability of analytics programs to provide dynamic visuals on multiple platforms. Whether it’s sales agents in the field, supply chain managers, or company executives, competitive retailers and their product suppliers need vivid and intuitive data graphics in order to keep pace with the demands of a fast-paced and constantly evolving industry.

Power to the People: The example of Photoshop

A good way to understand the practical value of interactive visualization for retail analytics is to think about one of the most popular and useful image-processing tools: Photoshop. By letting photographers manipulate the information within the image, that program has revolutionized photography, and retailers are experiencing a similar transformation. There’s a strong analogy between the rise of digital photography and the rise of Big Data, because, of course, images are just another form of data. In both cases, the most catalytic outcome from the change in technology was the change in price.

Viktor Mayer-Schonberger and Kenneth Cukier explain this point out in their best-selling book Big Data: A Revolution that Will Transform How We Live, Work, and Think: “Over the past half-century, the cost of digital storage has been roughly cut in half every two years, while storage density has increased 50 million-fold.” Even when taking a picture meant buying a roll of film and paying to get it developed (often with poor results), photography was a popular pastime: many shots were taken, many albums were filled, many negatives were stuffed into paper envelopes and shoved into desk drawers.

But once digital technology allowed anyone with a simple camera to take unlimited pictures at no extra cost, people discovered an insatiable appetite to document their lives. In 2000, 86 billion photos were taken. Since then, the figures have skyrocketed—it’s estimated that humans will take 880 billion photos in 2014. Likewise with Big Data, the exponential increases are staggering.

Back in 2000, roughly a quarter of the world’s information was digital. Now, as we produce 2.5 quintillion bytes of data every day, less than two percent is non-digital. As RJMetrics CEO Robert Moore put it, “23 exabytes of information was recorded and replicated in 2002. Now we record and transfer that much information every seven days.”

Image-layering and the enduring value of data

So going back to the Photoshop example, one of the first benefits of digital technology that shutterbugs enjoyed was control. They could change the exposure, adjust the saturation, and bump up the brightness in a matter of seconds. You could fix it, crop it, and send it to your friends, all in just a few clicks. This newfound opportunity for manipulation was created by the conversion of images into bits of information. But there was a downside: every time an adjustment was made to the image, some of that information was lost. One could easily get carried away messing with the levels, and after playing with it to the point of perfection, suddenly discover that the image had become grainy and unprintable. Photoshop solved this problem by creating adjustment layers. Taking the principle that there’s no limit to data storage, the program allows users to continually multiply the data onto overlapping layers, and so to make visible changes that can be toggled on and off without affecting the raw data. This innovation had the positive outcome that it allowed photographers to make surprising innovations, such as bringing in elements from different pictures (the classic head-switch, for example), and countless other artistic possibilities.

The opportunity for retailers

Interactive visualization in retail analytics offers companies the same potential for control and innovation. Just as photo editors can move between layers and even bring in unexpected elements to create the best possible image, business decision-makers can navigate swiftly and easily between levels of data to get the most accurate picture of what their products are doing in any particular store or region, over any amount of time.

Since retail intelligence programs are built to integrate data streams from multiple sources, companies can now compare any relevant variable and map those correlations onto their existing data sets.

To see how Big Data analytics can give your company the control it needs to power better insights and fresh innovation, try a demo of Askuity’s Retail Intelligence platform.