From The Huffington Post.
Grocery stores run price promotions all the time. You see them when a particular brand of spaghetti sauce is $1 off or your favorite coffee is buy one get one free. Promotions are used for a variety of reasons from increasing traffic in stores to boosting sales of a particular brand. They are responsible for a lot of revenue, as a 2009 A.C. Nielsen study found that 42.8% of grocery store sales in the U.S. are made during promotions. This raises an important question: How much money does a retailer leave on the table by using current pricing practices as opposed to a more scientific, data-driven approach in order to determine optimal promotional prices?
The promotion planning tools currently available in the industry are mostly manual and based on “what-if” scenarios. In other words, supermarkets tend to use intuition and habit to decide when, how deep, and how often to promote products. Yet promotion pricing is very complicated. Product managers have to solve problems like whether or not to promote an item in a particular week, whether or not to promote two items together, and how to order upcoming discounts ― not to mention incorporating seasonality issues in their decision-making process.
There are plenty of people in the industry with years of experience who are good at this, but their brains are not computers. They can’t process the massive amounts of data available to determine optimal pricing. As a result, lots of money is left on the table.
To revolutionize the field of promotion pricing, my team of PhD students from the Operations Research Center at MIT, our collaborators from Oracle, and I sought to build a model based on several goals. It had to be simple and realistic. It had to be easy to estimate directly from the data, but also computationally easy and scalable. In addition, it had to lead to interesting and valuable results for retailers in practice.
Read the full post at The Huffington Post.
Georgia Perakis is the William F. Pounds Professor of Management and a Professor of Operations Research and Operations Management at the MIT Sloan School of Management.