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Why Retailers Are Losing Ground by Failing to Utilise Big Data

Philip Piletic / 3 min read.
September 11, 2018
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If you aren’t running a business named Amazon, you’re likely to feel the pressure of big data pushing small retailers out of business at an astounding rate.

It’s a bigger issue than the simple existence of Amazon. 2017 was a year to remember for all the wrong reasons as multiple retailers struggled to stay afloat despite already holding healthy market shares or a strong physical presence. If owning a storefront is no longer a guarantee of longevity, how can retailers adapt to the digital age and leverage big data to keep their livelihoods alive?

The digitized storefront era

While a large chunk of retail sales have shifted to digital markets, and everything seems to be moving to a Cloud, there still exists a need for physical storefronts offering goods without the burden of shipping time or the possibility of blindly receiving damaged products with no method of quick recourse. Even storefronts with a foothold in physical retail spaces tend to benefit from maintaining a digital presence, but it’s no longer as simple as selling excess stock on eBay. Putting digital advantages to use means investing in analytics and big data, much like what bigger online-only retailers have been pushing towards for years.

An immediate point of comparison between giants like Amazon and smaller, independent retailers is the ease at which larger players are able to serve a customer exactly what they’re looking for before they seem to know they need it. In reality, data collection and predictive analytics push a customer’s experience towards items they might find interest in when compared to their interests, browsing history, recent purchases and other points of data that are difficult if not impossible to collect manually.

On an even deeper level, many smaller retailers are unable to hone in on affluent repeat customers and tailor their services to meet their expectations without disrupting the flow of their workplace.

It’s no small wonder that larger retailers have turned to collecting data at a point of sales terminals and through public Wi-Fi connections to better build profiles of their customers’ shopping habits to learn exactly what drives foot traffic to their stores and what keeps customers coming back regularly. Combined with product research tools that alert retailers to product trends that should be capitalized upon while popularity is high, putting big data to use is less an option and more a necessity as we march into a future where data collection has reached nearly every aspect of our lives.


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The challenges of implementation

Collecting data is the easy part, all things considered; It’s putting that data to use that poses real issues. Even the simple fact that a customer might pay for an item through two separate methods, such as emptying a gift card and covering the rest with cash, can skew collected data in ways that are difficult to track. Many of the initial hurdles retailers face is dealing with fringe cases that taint their data pool.

Experts are currently extolling the virtues of big data and predictive analytics for good reason: Predicting buying and selling trends before they arise to mitigate risk and issues of overstocking stand to save retailers untold amounts of time and money as seasons pass and buying trends shift wildly. Furthermore, knowing these trends are on the rise allows retailers to craft advertisements and sales that attune closely with a customer’s needs and desires, creating a more personal experience rather than a scattered approach to advertising.

These implementations bring their own issues through ensuring data collected meets regulations and is considered “clean” rather than having personally identifiable data, though this is often mitigated by using reputable data collection services.

It’s worth noting that data collection also requires drawing the right insights from collected data and isn’t an end-all, be-all solution to buying and selling trends. There’s still an element of human input to the process that requires time in the industry and an eye for trends.

Retailers struggling to meet the digital age are only going to drag further behind as analytic tools become more thorough, leaving holes in markets that could have been easily filled with the right safeguards in place. The solutions are easily available and their insights are invaluable. Don’t be left behind.

Categories: Big Data
Tags: Big Data, business, retail, retailer

About Philip Piletic

My primary focus is a fusion of technology, small business, and marketing. I'm a writer, marketing consultant and guest author at several authority websites. In love with startups, the latest tech trends and helping others get their ideas off the ground. You can find me on LinkedIn.

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