IBM Takes the Guesswork out of Holiday Shopping 

Shopping season may be stressful for shoppers hoping to beat the crowds and find the lowest price, but retailers are far from immune from the stresses of the holidays. Historically, the pressure has been to wait and see which items sell and then react as quickly as possible to adjust prices and keep them in stock. But as IBM has pointed out, predictive analytics are working to change that.

In the video below, IBM demonstrates just what some of its retail customers are doing to stay ahead of the curve. Rather than waiting until November to see what’s in demand, more companies are starting their planning six months ahead of time to anticipate which items they should expect to fly off the shelves.

To do this, retailers are gathering data from, web browsing patterns, advertising presence, and popularity in social media on top of their own sales history to create a predictive model of holiday demand. From this, retailers can see not only which item will be in demand, but will be able to estimate how much of it and every other item they can expect to sell over the holidays.

For companies with stores with multiple locations, they can look at local demographic and shopping trends to see which brick and mortar stores will have greater and lower demand for specific gifts, as well as how they will fare relative to an online store.

In the end, customers should spend less time hunting around for a store that has their gift idea in stock, while retailers can avoid wasting money to stock up on items that aren’t expected to sell. And once a store has the right inventory for demand, they can then continue to take advantage of the tool to create a price optimization model based on demand and competitor prices to make the greatest profit given their expected sales.

If necessary, a retailer can even turn to real-time analytics to synchronize their prices to match demand, inventory and competition by the hour.

But if that isn’t enough to guarantee that your target demographic will shop with you, the tool can also be used to reach out to these shoppers through social media or mobile alerts through personalized offers, and bundles of products that are commonly bought together.