Spot Hot Shopping Trends Using Big Data
Imagine having your store stocked with exactly the right products that your customers desire in the precise quantities that they wish to buy. You are completely unburdened by slow sellers. Your website contains all the right keywords. And drastic markdowns are a thing of yesteryear. Unless you are a master psychic or you have access to each of your customers’ personal shopping lists, achieving this degree of inventory perfection seems like an impossibility.
“I see a small elf and it sits on a shelf.”
While the flawless inventory remains elusive, retailers are able to much more accurately predict hot products and shopping trends thanks to Big Data.
What is “Big Data?”
“Big Data” refers to the huge volume of data that is collected by businesses. It is generated instantaneously, sorted by data integration tools, and converted into meaningful information that can help said companies improve their customer service, product lines, marketing efforts, supply channels, and many other aspects of their business. And, yes, it can also be a valuable ally in your quest for the perfect inventory–and ideally designed website to sell it.
Forecasting the next hot item.
A toy retailer who failed to foresee the demand for the highly creepy, but extremely popular Elf on the Shelf is likely kicking themselves in the derriere. Not only did they lose that sale, but they likely lost out on valuable add-on sales opportunities. Plus, their disappointed customers were forced to enter another retailer’s doors or visit another site. That’s bad news.
Big Data, however, can help retailers predict future demand–yes, even for a timeframe as far off as the next holiday season. By collecting statistics on what customers are searching for online, what they are discussing on social media, what manufacturers are advertising, and other relevant data, the aforementioned toy retailer will be better equipped to identify and stock the future big sellers.
For instance, if a huge segment of your online shoppers are using your search tool to find “Rainbow Loom,” and you are not currently carrying that item, you may wish to add that to your inventory. Likewise, if a Brick and Mortar store discovers that the hashtag “#rainbowloom” is trending on Twitter, they will be better equipped to meet in-store demands.
Identifying local differences.
Nationwide retailers need to be able to pinpoint the variances found in regional and local markets. The biggest seller in downtown Los Angeles may be quite different from that of small town Nebraska. Thanks to the demographic information collected by Big Data, toy retailers can better identify the products that will appeal to shoppers within their own marketplace.
For example, a brick and mortar bookstore that also has an online store may discover that most of the customers searching for a specific title on their website are from Watertown, NY, the home of the author. This would motivate them to increase their inventory of this item at their Watertown location, enabling them to better meet customer demand.
Assessing a product’s performance.
Retailers need to be able to assess how well a product is performing in order to determine optimum restocking levels. If that Elf on the Shelf isn’t selling as well as anticipated, the toy retailer needs to know before they submit a hefty new order.
Thanks to Big Data, retailers can examine a product’s success almost immediately after its launch date. If a new product is proving to be a flop, they can make changes to its placement within the store and on websites, its price point, and their marketing efforts. And, they can better ensure that their future orders reflect the product’s actual success and not simply rely on traditional industry buzz.
Determining individual needs.
What if you could read a customer’s mind? You would know that their son collects Lego figures, their daughter craves a Rainbow loom, and their husband–who is really a big kid at heart–loves building model planes. You would be able to give this customer exactly what they need at the price points they can afford. It’s a retailer’s dream realized–and Big Data is striving to accomplish exactly that.
Thanks to Big Data, retailers are better equipped to determine what products will appeal to consumers who fall within certain demographic categories. The purchasing habits of an empty-nester, for example, will be quite different from those of a single mother of four. Armed with the right information, retailers can present personalized promotions and special offers based on the similarities (including keyword searches) exhibited by members of certain groups of people.
Big Data can also identify popular product groupings. A prime example of this is Amazon’s famous “customers who bought this item also bought…” feature. Based on the information extracted from Big Data, Amazon may determine, for instance, that people who buy Elf on the Shelf also frequently purchase a faux fur elf skirt–they do exist–and recommend that as an add-on.
Big Data also allows retailers to customize offers and recommendations based on completely individual preferences. Many retailers, including Amazon, regularly present customers with a sampling of products that they may like. These offerings are selected based on their previous purchases and searches. For instance, the shopper who purchased the Elf of the Shelf may be presented with the Dwarf in the Drawer–and, yes, this really exists as well–as a suggested purchase.
“Perhaps I should have foreseen that Big Data would make my psychic services redundant.”
Big Data has taken the guesswork out of many aspects of the retail business. Consumers can now enjoy a more personalized and pleasurable shopping experience. They are better assured of getting exactly what they are looking for. And Elf on the Shelf seekers are going home happy.
What product did you have problems finding this holiday season?
Kimberley Laws is a freelance writer and avid blogger who thinks that the Elf on the Shelf is the creepiest creation to hit toy store shelves since the Troll Doll, Baby Alive, and the Jack-in-the-box. You can follow her at and Searching for Barry Weiss.
Images courtesy of photos.com.