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How retailers can use predictive analytics to prepare for the holiday season

(Image credit: Image Credit: Sergey Nivens / Shutterstock)

Retailers can utilise the power of big data to make better business decisions, also known as using predictive analytics. Although predictive analytics cannot forecast with 100 per cent accuracy, its use can help companies reduce risk and uncertainty in the decision-making process. Being able to predict the behaviour of customers is a powerful tool for any retailer, but especially during the holiday season, predictive analytics are crucial.

For some retailers, the holiday season can be as much as 30 per cent (opens in new tab) of annual sales. Though most retailers make about 20 per cent (opens in new tab) of annual sales during the holidays, jewellers average a high of 27.4 per cent (opens in new tab). With that kind of finances at stake, trying to get buyer’s attention is incredibly important.

Retailers running online ads see a surge during the holiday season. Click-through-rates (CTRs) increased 22.6 per cent (opens in new tab) last year, meaning buyers are clicking on many more ads during those winter months. Furthermore, last year, nine out of 10 (opens in new tab) holiday shoppers said something convinced them to make a purchase they were hesitant about, and over 50 per cent (opens in new tab) bought an item that was recommended to them by the retailer online. This means that retailers that use data to predict what the buyer will want come this holiday season will certainly see high sales.

So what can retailers do to harness the power of predictive analytics this holiday season? Here are some up and coming trends to watch out for when prepping for holiday sales.

Predictive algorithms mean better targeting

Since it’s clear buyers click on more ads during the holiday season, retailers will want the right buyer to click, instead of just anyone. Using predictive algorithms, retailers can collect demographic data and match that information with past campaign performance. Both of these items combined allow retailers to create highly effective messages for these individuals with deals or discounts for the holidays.

Furthermore, predictive analytics allows marketers to make offers in real-time, enticing the buyer even more. 59 per cent (opens in new tab) of online shoppers think it’s easier to find interesting products on personalised online retail stores, so if retailers can highly target those consumers with personalised suggestions and holiday deals, they are more likely to have success.

Predictive tools aid price optimisation

Retailers want to make money during the holiday season, which means they need to sell items at the optimal price. To do this, they must implement predictive pricing analytics, which reviews historical product pricing, product interest, inventory, competitor pricing, margins, etc. From there, real-time, optimal prices can be set that will give retailers maximum profit. The price remains at a level that the buyer is comfortable with, since the algorithms know when an item is priced too high.

During the holidays, the demand for certain products can change, especially as December 25th approaches. Instead of having to adjust prices manually, predictive analytics can update costs in real-time for retailers, making sure items are sold and consumers are happy.

Predictive data helps plan holiday offers

Using consumer data, such as online and in-store habits, retailers can understand and predict buyer behaviour. Data tools can showcase insights into this behaviour and prediction tools can anticipate what they will buy and when. With this information, retailers can strategically plan promotions for each type of customer - returning, new, etc. If retailers know that their returning customers are likely to buy at a certain time, they can run personalised campaigns with suggestions and discounts to push them down the sales funnel.

During the holidays, individuals spend hundreds on gifts, so retailers that know when these people are going to buy will have a huge advantage over the competition.

Inventory management automated

During the holidays, inventory management can be difficult. Since everyone wants their gifts available before a certain day, making sure to have enough product is a tenuous task. Retailers certainly don’t want to run out of a product, but they don’t want to be completely overstocked, having then to discount the item after the holidays end.

Predictive analytics provide retailers with smart inventory management. These tools can consider current inventory, future need, promotional activity, markdowns, and more in order to forecast inventory needs. Retailers can then ensure they have enough stock to get through the holiday season in the right place (i.e., in appropriate warehouses). Predictive analytics can also help ensure retailers don’t end up with too much inventory after the holiday season, since they usually will then have to discount the item and potentially lose sales. Predictive tools allow retailers to learn how much they need to order and when.

More accurate revenue forecasting

Predictive analytics can better estimate a retailer’s success during the holiday season. Buyer habits can change, so retailers that forecast massive sales may find themselves in the red come January. Using predictive analytics, retailers can view much more accurate sales forecasts, so they can better prepare for the new year. Instead of wishful thinking, predictive analytics allow data-driven insights that take into consideration buyer behaviour, giving a better look at future sales and helping to begin new year planning.

Predictive analytics reduce downtime

During the holiday rush, there really isn’t time for machine malfunctions. Customers want products quickly, which means supply chain logistics cannot fail. Though predictive analytics are usually used in large-scale manufacturing operations, they have begun to improve the packing and shipping operations for everyday retailers. By monitoring vehicles and machines, predictive models can alert a human when a problem might occur. Doing this means the problem can be fixed quickly without machine or vehicle downtime. Especially when it comes to making deliveries around the holiday season, this feature is crucial for retailers trying to maintain happy customers.

Retailers that use big data this holiday season can gain a much-needed edge over the competition. Predictive analytics can help maximise productivity and allow retailers to more effectively reach their target market anytime of the year. However, since a significant portion of annual sales come during this time of the year, retailers should use every advantage possible and invest in predictive analytics tools. Not only will this have a positive impact on sales, but consumers will receive more personalised suggestions, making them happier customers.

Jennifer Roubaud is the VP of UK and Ireland for Dataiku (opens in new tab)
Image Credit: Sergey Nivens / Shutterstock

Jennifer Roubaud is the VP of UK and Ireland for Dataiku, the maker of the all-in-one data science software platform Dataiku Data Science Studio (DSS), a unique advanced analytics software solution that enables companies to build and deliver their own data products more efficiently.