Article | September 27, 2018

5 Surprising Ways Predictive Analytics Helps Retailers

By Adrian Silipo, Marketing Manager at Retalon

How To Improve CRO Oversight With Data & Analytics

Modern retailers understand the core benefits of leveraging the power of Predictive Analytics and Artificial Intelligence. Predictive Analytics accounts for all of your company’s relevant data at a micro-level, identifies your business’ trends, opportunities, and influencing factors. It makes recommendations to retailers that will help them increase forecast accuracy, reduce inventory costs, increase in sales, and maintain high customer satisfaction levels.

This software is becoming more intelligent, more critical to retail success, and more common in the retail space, yet there are still many important things that Predictive Analytics can do that surprises retailers. Here are five of them:

Superior Demand Forecast That Accounts for Dozens of Influencing Factors

Demand affect every element of a retail business, from planning and open to buys, to inventory assortment, distribution, pricing, and promotions. Anticipating demand is critical. Retailers live and die by their forecasts, and an accurate forecast enables you to be proactive, improves ROI, and gives you more consistency in your business.

Traditionally, merchants relied solely on past history, human input, and guesswork. This resulted in low forecast accuracy and high labor cost because so many things change from year to year. Heavily relying on past sales leads to repeating the previous year’s mistakes and missed opportunities.

Instead of just looking at previous sales, you might be surprised to learn that Predictive Analytics looks at dozens of influencing factors to build a highly accurate forecast of true demand, such as:

  • New products could cannibalize sales of other products
  • The size curves (size distribution) of your every store/SKU in your business
  • Seasonality and effect of promotions on demand

Demand-based forecasting is less concerned with what you sold last year, and more concerned with what you could have sold, had the right sizes/colors/styles been in stock. By identifying true past demand retailers avoid repeating costly mistakes in the future, as forecasts will be more accurate. Your In-Stock Percentage will increase and be maintained at a very high level as will your sales. Meanwhile, your cost of inventory will decrease because you’ll only be carrying the right assortment at each location.

Integrating Inventory and Promotions

An integrated Predictive Analytics platform unifies critical functions in your business. This approach leads to higher forecast accuracy, consistency in workflow, and automation that reduces time and resource costs. Let’s look at an example:

Many retailers are still running promotions with only partial visibility to their inventory levels, because Inventory and Promotions were traditionally two separate business functions. Retailers are surprised to learn that best-in-class Predictive Analytics platforms will integrate the two. The system calculates future promotional uplift and recommends the additional inventory that you need at each location to run a successful promotion.

Proactive Inter-Store Inventory and Assortment Balancing

Retailers are too familiar with scenarios of inventory imbalances, for example, after holidays or major unexpected events. An unforeseeable snowstorm in a tepid climate could leave you sold out of snow shovels and send your customers to competitors. A vendor’s PR nightmare could turn a hot-seller into an overstocked item overnight, making it difficult for a retailer to maintain their margin.

Fortunately, Predictive Analytics can proactively tell when a product stagnating in one location may still sell for full price in other locations at risk of running low on stock.

Inter-store inventory balancing calibrates inventory and assortment in line with demand. The system accounts for all associated costs including freight and labor costs to proactively recommend the most profitable transfers. This results in retailers reducing needless purchases, markdowns, and lost sales, while also increase customer service levels and maintaining a high In-Stock Percent.

Automatically Measuring Cannibalization Effect

Dropping a price or introducing a new product in your retail business can create butterfly effects across your business that retailers often find challenging to accurately detect or quantify. One such example is cannibalization effect, which causes shifts in demand from product(s) to product(s).

Here’s an example of cannibalization due to a retailer running a promotion:

Imagine an 60% profit margin on jeans.
Pair A retails for $125, costs $50, and nets $75.
Pair B retails for $100, costs $40, and nets $60.

If you discount Pair A from $125 to $100, people will buy it rather than Pair B, but now you’re only making a $50 margin, so this promotion will cost you $10/unit in margin. Moreover, now you’ll be overstocked on Pair B because demand will be less than what was initially forecasted.

Predictive Analytics will automatically calculate what effect on demand a promotion or new product introduction, giving retailers one less thing to worry about.

Determining Whether or Not a Product Should be on Promotion

A Predictive Analytics engine looks at an unimaginable amount of data and determines what factors impact sales at a SKU/store level, and how these factors influence each other. It can even help retailers to understand what products do or don’t need to be on promotion.

Say you have snowsuits on sale. Do you need to also offer a discount on matching hats and gloves? A Predictive Analytics engine could determine, given a sale price, if customers would buy the matching accessories anyway.

Predictive Analytics will give you proactive recommendations and warnings to help retailers maximize their profitability by retaining their margins rather than offering discounts that won’t help the bottom line. Moreover, the system will recommend the optimal media types, promotion types, and even ideal timelines for promotions.

A Winning Combination

Retailers know that Predictive Analytics can benefit their businesses in many ways, but the impact of a truly unified Predictive Analytics platform are both surprising and impressive. When integrated with your business, retailers leveraging this technology are seeing increases in forecast accuracy, reductions in inventory costs, increases in sales, more visibility across their business, consistency in their workflow, and an automation of their business that reduces manual labor.

About the author

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 www.retalon.com.