For retailers, remodeling is in vogue. Target is in the process of remodeling more than 1,000 stores across USA by 2020. Walmart is spending $11 billion to remodel 500 stores, build 20 new stores, and expand programs such as online grocery pickup. The ‘remodel’ includes changes such as wider aisles, shorter shelving, new signs and flooring, interactive displays, and self-checkout among other upgrades.
To top it all off, pioneered by beauty retail, there is the emergence of experiential retail which involves offering customers the option to try out products in their environment before making a purchase. Key points to note here are the scale of remodeling (more than 50% of stores for Target and a multi-billion dollar investment for Walmart), the high number of components that a remodeling involves (aisle, shelves, signs, displays, experience zones etc.), and an outlook of more than two years.
With an investment of such scale, it is vital to identify which stores not only benefit from a remodel by driving maximum ROI but are also representative of all stores and can thus serve as a test bed. The ‘representation’ here needs to be after consideration of all factors – demographics, weather, region, sales trends, and many more. This is a complex engineering problem to solve.
Then to extrapolate results of one store to others, understanding causation is key. With the number of components as high as it is in a typical remodel, it is important to know exactly which component is driving the ‘lift’. It is possible that most of the lift was a result of more informative displays and the expensive new shelves were of not much consequence. It is also possible that neither of the components worked, and the lift was a result of increase in demographic of the catchment area. These are correlations that are not obvious but easily recognized by algorithms.
And then there is the number of years it takes for a remodeling overhaul. With a timeframe of anywhere between two and five years depending on the number of stores and ability to execute, it is critical for retailers to maintain a knowledge center and keep learning about past remodels. This is especially true in remodels where there is not enough historical data to fall back on, such as creating experience zones.
Let’s assume you are creating an augmented reality experience zone in 2018. Very few retailers have attempted it in the past and those who have attempted would obviously not disclose their experience in the public domain. So, it is not possible to ‘predict’ the success of the zone. But maybe you had attempted something similar in 2016, such as high definition screens to simulate an augmented reality-like effect. What was the result of that attempt? Was it successful? What were the factors that drove this success, or failure as the case maybe? Was it perhaps the young demographic around that store that contributed to the success? Has the demographic changed in 2018? Maybe you should experiment with augmented reality in areas with this demographic? Answers to these questions will help make a better decision today and likely generate a higher ROI. Maintaining such a knowledge library, while a huge task in human hands, is efficiently and effectively accomplished by testing and experimentation software.
Maximization of return, attribution of the return to each component accurately, and creation of a knowledge repository – utilizing the right technology can solve major hurdles of a remodel. Really, with billions at stake, among the first investments that a retailer should make when undertaking a remodeling exercise is simply in a technology designed to make remodeling profitable through rapid experimentation.
About Trial Run: Trial Run is a cloud-based product that lets companies conduct business experiments on sites, markets and individuals. It helps companies scale their experimentation capability efficiently and affordably.