How Retail Analytics Can Better Inform Pricing Decisions

A strategic and optimized pricing and merchandising strategy is essential to staying ahead of the competition. Retailers are continuously trying to increase revenues, and find new ways to achieve incremental margin gains. Unfortunately, problems such as incomplete data, a reactive pricing strategy, and limited analytical capabilities often hold them back.

By providing insights to factors such as perceived product value, historic sales performance, purchase trends, and more, big data analytics can help retailers optimize pricing decisions. As you can imagine, curating such insights can be a complex task when a large retailer has hundreds, or thousands, of products.

Big Data with a Simple Solution

Optimal prices are easy to determine if a retailer only has a few products to sell, but the job can be overwhelming if they are looking at everything from pricing variables to constantly changing data insights for a large number of products. The key to success is not only access to big data, but also the ability to easily identify and pull actionable insights quickly to make decisions. In today's environment, buyers and category managers are often managing a large range of items, spread thin for time and aren't data miners by trade. Access to a retail analytics solution that can deliver simple navigation and insightful analytics without the headache of deep data mining is crucial to the success of putting big data to work.

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Look Beyond Simplistic Factors to Determine Optimal Prices

The overwhelming nature of determining optimal pricing means that many retailers choose to turn a blind eye to the situation, instead of taking a proactive approach. They stick to existing pricing strategies based on simplistic factors, such as the prices of competitive products, traditional margins of the business, and adding a standard annual price hike across the board each year. Often times this leaves money on the table or missed opportunities in sales. Retailers need to look beyond these factors to get to the optimal prices of their products, and that’s exactly what retail analytics are capable of.

Base Pricing Decisions on Data and Science

Thanks to retail analytics, companies now have the information they need at their fingertips to make informed pricing decisions, not only for consumer retail price, but also optimal promotional pricing as well as further up the distribution chain. 

The incorrect pricing of items can often times be counter productive in achieving the end goal of sales growth. Retail analytics can provide straightforward insights to optimal pricing. Because these decisions are not based on the data and science, products are either discounted too heavily and sales increase does not make up for the margin loss, or products are priced too high and customers are lost. The right retail analytics solution will help identify that pricing sweet spot.