Setting the attractive price for a specific customer is possible through predictive analytics.

Improving retail pricing through predictive analytics

As retail businesses grow and diversify, pricing becomes an especially important consideration. Whether a company wants to dynamically price merchandise based on the sales channel, maintain the same pricing across all avenues or use both strategies simultaneously, they need data to accurately set price points.

Without the reliable intelligence and forecasting provided by predictive analytics, determining competitive prices and making sure merchandise is sold in the most effective way possible is a difficult and time-consuming endeavor. When retailers have business intelligence software like the IBM Cognos suite of products in place, however, they can make sure pricing is accurately determined and reflected across all sales channels.

"Predictive analytics gives retailers powerful insight into their pricing strategies."

Optimization and differentiation both benefit retailers
The market for nearly any product or good is significantly more diverse now than any at time in the past. The rise of e-commerce and the ability to quickly analyze and communicate information across an entire business mean different prices can be used in a variety of contexts. Whether dealing with the differences between online customers and those who visit a brick and mortar store, or shoppers from different regions of the country, dynamic pricing can lead to more sales and more satisfied buyers.

The Harvard Business Review highlighted improved pricing as one of the areas where predictive analytics is making the most positive change for businesses. The article discussed how rapid changes in pricing in e-commerce have benefited retailers. By drawing on the large amounts of customer information that are stored and utilized, retailers can determine the best possible cost to display.

By using predictive analytics, businesses can gain this advantage in both digital and physical sales channels. Having that kind of flexibility – derived in physical stores from developing effective customer segments through tracking mobile device use and related behaviors – means significantly better outcomes in terms of encouraging the next purchase

Aviana has plenty of history developing successful projects in the retail world, partnering with retailers like Patagonia and Columbia Sportswear to take full advantage of big data and predictive analytics. Our experience in the industry means we understand the unique challenges faced by merchants and how to best apply predictive analytics to a variety of concerns and opportunities. Want to learn more about how Aviana can help your retail brand grow? Visit our dedicated industry page.

This entry was posted in Predictive Analytics by John Martin.
John Martin

About John Martin

After several years of continued excellence in performance as a top producer at Aviana, John Martin is now the Vice President of Sales. As the founder of three prior startups, Mr. Martin has applied his entrepreneurial experience and background in marketing and technology to help organizations evaluate and implement enterprise software solutions for the last 20 years. Mr. Martin’s success can be credited in part to his dedication to putting the customer first and relentlessly striving to deliver excellence in all areas. Mr. Martin earned his bachelor’s degree in speech communications with a minor in computer programming from Point Loma Nazarene University. John lives in Carlsbad, California with his wife and two children.