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Black Friday makes it official: ‘Tis the season for companies to wade through big data

Big data is a trendy topic these days but it’s left most business owners scratching their heads wondering: how does this apply to me? Large enterprises are already finding ways to use insights on their customers—take Tesco’s innovative approaches which allows them to send targeted coupons or the well-known story of how Target intuited a Midwest teenager’s pregnancy before her parents knew. It’s time for small and medium-sized businesses to profit from using big data strategy. With the holiday shopping season upon, online commerce is projected to reach a staggering $224.2 billion in the US this year.

Here are three best practices we drew from studying customers use cases from Meijer to Target at SiSense:

History is destined to repeat itself

While we might never understand why platform sneakers or colored leather jackets become trendy must-haves, there are some trends that repeat year after year.

Online Commerce Group, a retail leader whose use of big data analytics helped it grow by 174% last year, is planning on tapping its data history to win bigger this year.  In a world where most of its competitors can barely sift through a year’s worth of data with ease, Online Commerce uses SiSense’s big data analytics solution, Prism, to quickly analyze the last five years of its retail history to make better decisions. The Alabama-based retailer will be introducing a holiday line for the first time this year and they’ll be using Prism to track sales and revenue of the stockings and tree skirts to ultimately determine consumer interest and decide whether to continue offering the line in the future.

Historical data can help online retailers understand when their holiday shoppers do the most spending, which offers encourage larger purchases, and how to clear the shelves of as many stocking stuffers as possible before New Years. Retailers can also leverage the data to determine which products to highlight on their websites for Cyber Monday sales and how to stock appropriately. Find the insights in last year’s data, the year before, and the year before that…and you’re almost guaranteed to beat performance before the ball drops this year!

Your customer is not your only target

One of the easiest traps to get caught in is to assume that the people making purchases are the only people you need to target.  On the contrary, there’s probably a much larger and more anonymous group of people you need to think about—the people who visit your site and/or locations without making a purchase.

That’s why mashing up data to understand the intersection points that define customers and their behaviors is critical.  The people who buy things from you are important, but understanding buying patterns before the buying occurs is just as critical.  For most companies, storing and interpreting millions of data points from visitor behavior might seem like a daunting task, but if you have the right analytics toolbox, you can start to understand who visits your site just to look, who fills a virtual shopping cart but fails to buy, and who agonizes over nearly-identical ceramic crockery.

When in doubt, ask a teenage girl

Ask a high school sophomore if she’s hoping to get a new pair of 70’s-inspired flared jeans this year, and she’ll probably scoff at you. Fortunately, holiday season strategy doesn’t have to be shaped by the whims of what might be the most unimpressed consumer audience in history.

If you’re hoping to boost sales, look beyond individual product numbers or brands.  What you need to see are categories—is designer denim consistently hot?  Have watches replaced vintage tees as the ironic nod to yesteryear in the men’s department?  A product number or SKU is handy if you sell the same product year after year, or for looking at short-term trends.  But in the longer term, knowing that watches or upscale jeans are generally hot items will help you more than would knowing which watch, specifically, is a top seller.

We welcome your comments at ideas@qz.com.

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