When looking at POS data and sell-through reports, Melissa the merchandiser noticed widely varying sales results for her three biggest hopes for the spring fashion season. Dress #1 is steadily selling and meeting her expectations, but dresses #2 and #3 are not, with dress #3 actually having dreadful sell-through performance.
A cursory glance at store traffic metrics showed the store is experiencing relatively flat traffic compared to historical patterns, and well within recent expectations.
So, now what?
In years past, Melissa might have jumped to price markdowns on dresses #2 and #3, a move to the back of the store and the deeply discounted bins, or perhaps even shuffled the dresses off to the outlet store.
Other than that, she could always go “tin cupping” to Marketing and look for promotional assistance. Or, perhaps a hard push with the store manager and sales associates could breath new life into the merchandise?
That was years past. This year, Melissa has few new tools and new data streams to more accurately identify root causes before jumping to problem-solving and corrective actions.
To gain greater clarity on the roots of her disappointing sell-through, Melissa first looks at RFID data and its chronicle of the movement of the dresses within the store. It’s in that data where her first revelation is made.
Melissa notices dress #1, her bestseller, and dress #2 are often taken to the fitting rooms. But, once at the fitting room, their journeys begin to differ. More often than not, dress #1 next goes from the fitting room to the POS terminal and is purchased. Dress #2, on the other hand, more often sits on the re-stock rack at the fitting room before finding its way back to the sales floor.
Now, Melissa feels she’s able to refine her decision-making process. Dress #2 engages shoppers and entices them to try it on. As it’s not converting into sales from the fitting room, perhaps there is an issue with fit, color, or another style issue. It might just be time for a markdown on dress #2.
But, what about dress #3?
Diving even deeper into data, the Melissa now integrates video data streams with the RFID stream and identifies a lack of foot traffic to the display fixture that hosts dress #3 – front door traffic is good, but traffic seems to be diverted away from dress #3’s display.
Much to Melissa’s surprise, on a percentage basis of shoppers passing by, dress #3 actually outperforms dress #1 in engagement at the display and trips to the fitting room. In fact, dress #3, once in the fitting room, converts at an even higher percentage than dress #1.
No way dress #3 is getting marked down! Price isn’t the issue, so why give away valuable points of margin when it’s not absolutely necessary?
Instead, Melissa has discovered that the issue with dress #3 is its location in the store and the display’s attractiveness to shoppers from a distance. A clearly defined root cause now leads to a more effective potential solution.
Data-based decision-making is great, but if data is incomplete, less than optimal decisions are all too often quite possible. It’s for that reason that the future of retail analytics is moving toward sensor fusion and the integration of previously disparate data streams.
RFID and the Internet of Things (IoT) is sweeping through retail, and the applications are potential game-changers, not only allowing retailers to operate more effectively and efficiently, but also create customer-centric shopping experiences that truly differentiate.
Earlier this year, RetailNext announced its charter founding membership in the Acuitas Digital alliance, featuring fellow founders BT, Intel, NexGen and Sato Solutions. The fully integrated solution provides retailers with a comprehensive, cloud-based and future-proof solution provides retailers insights throughout their entire supply chain, and to and through the physical store where customers shop.
The “future of retail” is more and more often already in stores now, and it’s a good thing for retail professionals like Melissa the merchandiser. Better data makes for better decisions and better shopping experiences, and what’s best for shoppers is best for the business. Always.