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Five Ways Predictive Analytics Helps Retailers On Back To School

Contributed by Adrian Silipo, Marketing Manager at Retalon

At $83.6 billion in spending, back to school/college is retail’s second largest selling season after the winter holidays, but accurately forecasting demand during such sporadic events can be a challenge for retailers. Predictive Analytics helps retailers forecast the demand of products, discover which products could see growth in sales, allocate the right products to the right sales channels and stores, and optimize their timing, pricing, and promotions.  It takes away much of the guesswork and tough choices retailers face, which helps them overcome these five challenges:

Recognizing Products With Back To School Sales Uplift Potential

Retailers already know that school supplies, computers, and clothing will see a huge sales uplift around back to school time. Other categories may not see a significant sales uplift, but hidden within these categories are items with high back to school sales uplift potential. The issue is that most retailers will miss these would-be top-sellers because they don’t have the ability to look at data at a SKU/store level.

Even retailers taking a more detailed look at last year’s sales can miss a product’s full potential because sales don’t represent a product’s true demand. Example: Families want to gear up for football and hockey season when school starts, but retailers won’t see an overall spike in sporting equipment sales so they won’t recognize the back to school potential of football cleats and hockey skates. A Predictive Analytics system proactively recommends the additional inventory needed to help retailers maximize their sales by meeting the true demand they never knew they had.

Getting The Right Order Quantities For Back To School

Now that you know which items have back to school sales uplift potential, you’ll want to have additional inventory in place to meet the demand. How much more is too much more?

A retailer selling school bags needs to consider product attributes such as color, style, capacity, and features to decide how many units to bring in. The assortment must be in line with demand to avoid facing overstocks and markdowns at the end of the back to school event. Not all school bags will perform equally well at all stores, and not all stores will perform the same. A Predictive Analytics solution can forecast a highly accurate breakdown across different styles and colors for each location. Moreover, the system can measure the effects of cannibalization, for example telling you how new school bags introduced this year will affect the demand of previous models.

A Predictive Analytics engine examines data from a retailer’s entire business to determine dozens of influencing factors and their interrelations, create a highly accurate demand forecast, and make optimal purchase order quantity recommendations. The solution intelligently and proactively identifies shifts in demand and builds optimal size curves while accounting for assortment depth and diversity.

Omni-Channel Allocation Of Back To School Merchandise

Knowing how many units will sell is only the first step, the next step is knowing where, and how those units will sell. Some retailers will only fulfill through their retail locations, while others fulfill orders through Distribution Centers, or even ship to customers from store locations.

Given the short window retailers have to make back to school sales, they don’t have time to correct their allocation. Retailers need to allocate inventory in order to offer flexible fulfillment options within business rules, constraints, and policies. A Predictive Analytics engine will proactively recommend inventory allocation at a SKU/store level to maximize sales while decreasing inventory costs.

Maximizing Time Benefits Of Seasonal Events

The start date, growth, and peak of back to school shopping will vary by location and channel. Retailers need to understand event timing in order to capitalize on early/late back to school shopping.

Inventory analysts that solely base decisions on last year’s data will often miss potential spikes in demand in the days before/after they usually bring in their inventory because these items weren’t previously stocked at the right quantity or promotional levels. By forecasting based on true demand, not just past sales, Predictive Analytics help retailers maximize event profitability by accurately forecasting demand not just during the event but before and after.

Acing Back To School Pricing And Promotions

Not all products react to changes in price the same way. Predictive Analytics leverages machine learning to determine what triggers sales of the product, for example, optimal price versus discount. The engine can understand and recommend the optimal promotional pricing, timing, and media types.

Moreover, most retailers run promotions with minimal visibility to inventory levels because traditionally these are two different business functions. A top-notch retail Predictive Analytics platform integrates inventory management with pricing and promotions. This gives visibility to inventory data such as items on-hand, in-transit, or on-order. The Predictive Analytics engine then takes into consideration potential sales uplifts from upcoming promotions or price changes and will proactively suggest the incremental inventory needed to maximize a promotion’s profitability.

Be Proactive & Reap The Rewards

Retailers can maximize their back to school profitability by leveraging a Predictive Analytics solution to have the right products, in the right places, at the right time. By using a unified Predictive Analytics platform, retailers will benefit from proactive recommendations made with considerations and data from all areas of their business. Implementation of such a platform typically comes with a boost in sales due to an optimized product assortment, as well as a significant decrease in inventory costs. Whether it’s back to school or any other event, Predictive Analytics can help retailers optimize their business.

Contributed by Adrian Silipo is the Marketing Manager at Retalon, an award-winning provider of retail Predictive Analytics solutions for planning, inventory management, merchandising, pricing, and promotions. Retalon’s solutions are built one unified platform to account for all factors influencing your business. Learn more at retalon.com.

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