Big Data Makes Shopping Better – Here’s How
Published on Apr 28, 2016 by Sean Kantrowitz
We’re far removed from a time when the online shopping experience could be considered new or revolutionary – in fact, most consumers would be caught off-guard to discover that a modern business didn’t offer an online option in addition to (or even in place of) a traditional brick-and-mortar store. As online retail has grown, the implementation of big data and business intelligence methodologies has added a new element that benefits consumers and retailers alike.
Today, thanks to the wealth of data available, online retailers have the ability to determine what their customers are looking for and steer them towards choices that not only will leave them satisfied, but also benefit the business. Retailers use sophisticated analytical tools to measure everything that happens online, often well before the first purchase is made. This allows them to optimize the likelihood that a potential customer will find what they’re looking for, starting at the very beginning with the search for their products or services.
“Helping organizations rank well on search engines is a big business that is heavily driven by data,” says internet marketing consultant Rob Croll. “Information like what keywords were used in a search, what device was used, geographic area, and much more can all help organizations make informed decisions about how best to reach their customers.” As organizations continuously expand and refine their reach, they increase the probability of being found by the right consumer, and of putting the right product in front of them.
Each and every online interaction provides more data to enhance the process. “Perhaps you signed up to receive special offers from a company based on a friend’s glowing recommendation. Now the company has, at minimum, your email address,” says Croll, who is also the Program Director for Full Sail University’s Business Intelligence Master’s degree program. “If they then send you an email with several promotions and you click on a specific offer, they now have a second piece of data – a possible preference.”
This click behavior, coupled with historical data from other customers, provides further information that businesses can use to predict other possible interests – enter the “related items” that have become all too familiar for those who have spent even a small amount of time on an online store. These related items can steer customers to a better option they didn’t know existed, additional items that could supplement their purchase, or an entirely new item that just happens to suit their needs and tastes.
As software engineer/big data expert Dr. Horn-yeu Shiaw explains, even if someone steps into a potential transaction with their mind set on one thing only, using analytics to find like-minded matches can potentially change the customer’s mind to the retailer’s benefit. “At the end of the day, retailers don’t have the whole world to sell. If I only want you to drink Coca Cola, I don’t care that there are hundreds of other drinks out there. I’m selling you Coca Cola.”
Online merchants like Amazon – which has built its reputation as being the place where consumers can find everything – also utilize big data to squeeze out unwanted results and provide consumers with a purposefully constricted array of options. This can sometimes be influenced by the percentage of commission that a vendor provides Amazon; after all, the company has more incentive to push potential sales from which they will see a larger monetary return. However, the consumer’s best interests also play a big role. Collected data can be used to process ratings, reviews and even returns, presenting a potential consumer with the most reputable sellers and products.
“If I’m an Amazon executive, I don’t really want to give you all of the choices that we offer through our service because not every seller is as reputable as some of the top contenders. I want to give you the top sellers so I know that you as a customer will be happy,” says Dr. Shiaw, who also teaches the fundamentals of big data as a Course Director in Full Sail University’s Business Intelligence Master’s degree program.
These business intelligence practices aren’t solely used to cater to engaged customers either. Big data analytics can also be useful in illuminating where in the shopping experience companies may be losing business, and also shed some light on why.
“One of the biggest problems faced by online retailers is shopping cart abandonment – when a customer has added something to the cart but then does not complete the purchase,” says Croll, who notes that this can stem from a variety of causes, including unexpected shipping or other costs or price comparisons with competitors. “Retailers use the data to analyze the reasons for abandonment and then make adjustments accordingly. For instance, many consumers today expect free shipping, so a retailer who charged for shipping might test what happens if they don’t. They can then analyze the abandonment data to see if the change was a net positive.”
Regardless of the purchase outcome, every step of the online process has given the retailer a wealth of data to improve on the overall shopping experience, which can’t be matched with information received in a brick-and-mortar location. Leveraged effectively, both customer and retailer reap the benefits.
Full Sail University’s Business Intelligence Master’s program provides students with the tools to manage, understand, and strategically utilize the wealth of data collected by modern businesses. To learn more, click here.
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