What Is Predictive Merchandising?

By business.com editorial staff,
business.com writer
| Updated
Jun 01, 2020
Image Credit: Zephyr18 / Getty Images

Learn the basics about predictive merchandising and what small businesses need to know.

  • Recognizing predictive merchandising on social media is simple: If you search for a product and become immediately bombarded with ads about the same or similar products, the company is likely using predictive merchandising.
  • Some benefits of predictive merchandising are that it provides sales efficiency and effectiveness, it allows for promotions targeting, and makes for better inventory management.
  • Some other benefits of predictive merchandising are that it helps with risk management and increases the accuracy of financial forecasting as well as supply chain cost management.

Evidence of a company's use of predictive merchandising is relatively easy to spot on social media platforms. Search for an item online and suddenly you're bombarded with ads and recommendations on social media offering the same or similar items. But how do so many companies know which product you're likely buying soon? 

What is predictive merchandising?

Predictive merchandising (also known as predictive analytics and automated merchandising) is based on technology that captures and analyzes a wide range of customer data such as purchasing habits and history, browsing patterns, personal preferences, typical spend, purchase timing, and many other customer activities. This data is then used to create personalized marketing and a custom shopping experience for each customer that can build loyalty and increase store revenue. 

Until recently, only the largest companies possessed the resources to invest in what were once company-owned proprietary systems that gathered, analyzed and used customer data to reliably predict buying behaviors. Now, thanks to cloud technology, even small businesses can deliver and benefit from predictive merchandising. 

What are some benefits of predictive merchandising? 

  • Sales efficiency and effectiveness. Marketing success hinges on presenting the right message to the right customer at the right time. Predictive merchandising technologies gather and analyze all the data that companies need to determine who are the best customers and how to keep them.

  • Promotions targeting. Targeting the right promotion to the right customer is one of the big benefits of predictive merchandising. From the customer's perspective, the offers they receive are those that are most personally relevant. Businesses see higher conversion rates from the promotions they run and, ultimately, higher revenue.

  • Better inventory management. Predictive merchandising can enable small businesses to more accurately forecast inventory needs, which helps reduce overstocking and associated costs.

  • More effective advertising strategy. Using predictive models based on your business's customer data, advertising dollars can be spent more effectively to reach and convert prospects that resemble the behaviors of your best customers.

  • Improved positioning over competitors. Predictive merchandising helps companies of all sizes and types compete more effectively in today's marketplace. This crucial tool helps to even the playing field when it comes to building and retaining a larger customer base while also improving business strategy and streamlining operations. 

Predictive merchandising examples

If you are interested in seeing examples of predictive merchandising, according to Acuvate, below are some examples:

  • Behavior analytics: By collecting data on customers, companies are able to better understand their customers in order to create more effective sales campaigns. The data collected can provide insight allowing companies to better recognize their high-value customers, the motives behind their purchases, their buying patterns, and which are the best channels to market to them and why.

  • Personalized in-store experience: By using new people-tracking technology, stores are now able to analyze in-store behavior to better assess the impact of merchandising that has been developed in recent years. This can allow companies to better personalize the in-store experience and encourage loyal customers by providing incentives to frequent shoppers.

  • Customer journey: By using analytics that analyze the customer journey, companies can better understand the best way to reach their customers (including high-value customers and their behavior) and what activities every customer is completing on their journey.

  • Analytics on operation and supply chain: Given that products have much faster life cycles and complex operations, big data analytics are often used to better understand supply chains and to help reduce costs. To gain a competitive edge, companies need to better understand analytics on operations and supply chain.

  • Trade promotion optimization: Reports have shown that businesses can lose up to the money they invested in trade promotions. This is because it can be next to impossible for decision-makers to measure its effectiveness and ROI. However, when used in conjunction with prescriptive analytics, predictive analytics can allow businesses to harness real-time structured and unstructured data from various markets as well as consumer touchpoints. This data can then be used to create actionable recommendations to help businesses find trade promotion methods that actually work.

In addition to improving sales revenue and customer retention, predictive merchandising can aid in other crucial areas of business, such as: 

  • Accuracy of financial forecasting
  • Supply chain cost management
  • Risk management
  • Profitability and revenue growth projections accuracy
  • Overall strategic business decision-making
  • Business intelligence and reporting
  • Data sharing, collaboration and visualization 

Why use predictive merchandising software?

Today, most small businesses collect and store customer data. But a typical small business usually can't keep up interpreting and analyzing the vast amount of information available from the growing number of data sources: emails, site visits, support calls, multiple sales channels, social media and others. 

Moreover, most small businesses don't have the resources or expertise to analyze the data they already gather on a regular basis. Predictive merchandising or predictive analytic applications are incredibly fast. Further, they typically use much broader sets of data and can track and analyze the information that few small businesses can perform in real time. 

Where to start?

As you might expect, there are dozens of software companies that offer predictive merchandising applications. Not all of them provide scalable solutions suited for small business yet. 

The best approach to finding the right solution for your company is to explore several organizations and see how well their offerings match your business's needs. Here are just a few of the companies that advertise small business solutions for a variety of predictive analysis types: 

business.com editorial staff
business.com editorial staff
The purpose of our community is to connect small business owners with experienced industry experts who can address their questions, offer direction, and share best practices. We are always looking for fresh perspectives to join our contributor program. If you're an expert working in your field – whether as an employee, entrepreneur, or consultant – we'd love to help you share your voice with our readers and the business.com community. We work hard to only publish high-quality and relevant content to our small business audience. To help us ensure you are the right fit, we ask that you take the time to complete a short application: https://www.business.com/contributor/apply/ We can't wait to hear what you have to say!
Like the article? Sign up for more great content.Join our communityAlready a member? Sign in.