“It’s IMPOSSIBLE to manage the business down at the product level.” I heard this statement last year from the head merchant of a retailer who is now in Chapter 11. It’s sobering.
Retail, like any industry, has its own language. When talking about a retail product’s performance, we hear terms like “Gems and Dogs” or “Winners and Losers,” typically referring to the amount of revenue that product is producing. Every retailer looks for the next big breakout products — items that are going to fly off the shelves and help them make their number.
Many “Dog” products are labeled as such because the retailer doesn’t have the time or framework to sort through all of the data to get to the root cause of the conversion or sales issue. Data silos and organizational barriers don’t easily give up the real issue impacting performance. It could be internal exposure, external exposure, pricing parity, fragmented sizes, poor content, or operational issues, just to name a few. With traditional systems, sorting through hundreds of under-performing products and identify the underlying issues requires a massive amount of time and analysis across several data silos, some of which merchandisers might not be able to easily access. Even when armed with a litany of reports, negotiating spreadsheets from varying time frames and differing units such as Order IDs, Product IDs, Customer IDs, Store IDs, Marketing Campaign IDs and more that live in some systems — but not others — is maddening and oftentimes fruitless.
But, without understanding all of the inputs for the performance and profit picture associated with each product, we are seeing retailers miss critical marginal gains that would quickly add up to massive profit increases and instead see a future that is “going to the dogs.”
However, it is possible to see and capitalize on marginal gains on hundreds of thousands of products. Amazon has proven that they not only manage close to 500 million products at a discrete level, but they are rumored to manage up to 500 associated attributes, per product.
Understanding and managing at a product and attribute level may be impossible with strictly human efforts. But it is very possible with Amazon-inspired retail analytics solution called DynamicAction.
Built specifically for retail merchandising teams by a former retail CEO, big data experts, and the former chief scientist of Amazon, DynamicAction is leveling the playing field for other retailers.