How Price Optimization Solves a Host of Retail Challenges
Special Tech Coverage
In some cases, rather than an altogether new approach to a business function, technologies that have been around for a while are becoming increasingly effective doing what they’ve always done, thanks to the application of artificial intelligence (AI), machine learning and related advances that are making them more effective in operation. Grocers may be well served reviewing how, for example, pricing technology has evolved. In a pandemic-related development, the current bout of inflation roiling markets certainly encourages some action on pricing.
“Inflation is fundamentally a pricing challenge,” asserts Matt Pavich, senior director of retail innovation at Austin, Texas-based Revionics, an Aptos company. “Pricing is the answer to inflation.”
In fact, pricing is a way to solve a host of retail challenges ranging from competition to image, given that other elements of a retail business, from store portfolio to merchandising, can’t be frequently adjusted. Increasingly sophisticated tools offer an even more effective way of addressing multiple business challenges.
“Price optimization is a good way to address challenges quickly, efficiently and effectively, if you’re using the right analytics,” counsels Pavich.
Yet pricing can be a tough tool to use because of its inherent complexity. What’s inelastic today may be more malleable in a month as seasonal and situational circumstances change. Subsequently, solutions that once were state of the art may be antiquated, and those relying on them may become less competitive versus rivals employing more sophisticated solutions. The sophistication today is, in large part, driven by AI.
Revionics has been developing capacities including AI, and has been advancing its approach to pricing even through the last period of inflationary creep in relation to the Great Recession.
According to Pavich, AI aids in advancing price optimization by continually re-evaluating procedures based on actual developments and making connections across categories in ways that would be hard to do without the technology. Although it might not otherwise be apparent, AI can work when a pricing action that might sell more cheese will lower hot dog sales, for example. When a lot of relationships that might be difficult or impossible for traditional systems to reveal get compiled and analyzed, pricing can become a more effective tool.
Pavich points out that such sophistication can be critical for grocers, since a food retailer offering 20,000 SKUs can have 1 million individual items in the store at any time. As such, price optimization at its best can drive the investment that’s sitting on store shelves more effectively, in part by helping grocers set priorities about how to handle the investment residing in the store aisle.
Yet beyond that, price optimization allows for more effective forecasting, which can have multiple benefits, according to Pavich. Retailers can run scenarios that take into account various pricing structures as applied to different expected occasions and circumstances, and even some that might be extraordinary, such as what might occur if a post-pandemic supply chain becomes clogged. Forecasting not only makes the grocery operation more effective, but it can also enhance and improve relationships with vendors that can work with the retailer on pricing adjustments based on a deeper understanding and effective forecasting, which can improve the supplier’s efficiency.
“It lets both find a common ground, and you can find it’s a win/win for the retailer and the vendor,” notes Pavich.
Sophisticated price optimization also can help retailers deal with another circumstance that challenges them today: labor. Price changes have to be made on the sales floor; however, if a grocer makes a price move but doesn’t have the labor in store to execute it, the entire initiative can go haywire. AI has helped create a level of proficiency that allows grocers to accommodate labor realities, in part by prioritizing price moves so the most important are executed first, and so on down the line, as labor permits.
Price optimization can also help brick-and-mortar stores, or those that primarily sell from physical locations, compete with online operators. Pricing in the e-commerce world is based on sophisticated algorithms that continually update what consumers pay for goods, optimizing prices in something like real time with the aid of functionalities like AI. As such, greater sophistication applied in the real world can make physical stores more effective in competing with digital, and can even suggest solutions to strategic considerations in omnichannel operations.
