Retailers collect a wealth of information from their stores every day. Point-of-sale (POS) data can show merchandise conversions and identify peak sales periods, while an employee scanning or stocking shelves can tell when inventory is low. Traffic counters can indicate movement patterns and popular areas of the store. The list goes on.
The challenge is this: Most of these data points are being gathered independently — only showing retailers a portion of what really goes on in the store.
For example, POS data alone can’t track how many times an item was tried on in comparison to how often it was purchased. Retailers might be able to use POS data to manage workforce staffing based on peak periods for sales, but what about peak periods for store traffic in general?
Additionally, data collected to determine bestselling items is vague and shopper-behavior insights are virtually non-existent. Retailers can’t afford to make assumptions in an increasingly competitive marketplace. Without being able to view the whole picture, retailers run the risk of missing opportunities to improve their business and boost conversions.
Digital natives are ahead of the game
Native online stores have been capable of collecting valuable data throughout a customer’s shopping journey for as long as they have existed. Because shoppers leave a digital trail, retailers can see items viewed, added to a cart and purchased. They can identify popular items, colors and sizes in real time. The data enables retailers to quickly adjust their merchandise mix and recognize opportunities to improve profits.
Because of this ability to modify strategy on the fly in the digital world, online stores that are moving into brick-and-mortar have high expectations for physical store insights. And, in many cases, they’re leading the move toward adoption of integrated, emerging technologies that help mirror the customer experience in the physical store, as well collect, analyze and report on rich data sets.
IoT goes mainstream
One example is the use of IoT technology to create connectivity and gather store data. Until recently, deploying IoT systems in stores was viewed as complex, cumbersome and expensive because it required the right mix of hardware, software and networks (while ensuring that each piece was highly scalable, rapidly deployable and easily adaptable).
But now, technology innovations have simplified the process, and often existing in-store systems can be used and connected to create a basic foundation for IoT. By using new or existing sensor networks, retailers can connect multiple disparate systems and get a single view across a wide segment of data sources. Now, they can capture and organize data, access rich and actionable insights based on the data, modify processes on the fly and help employees adjust their behaviors based on real-time input.
Here’s an example of an actual deployment. RFID sensors placed on apparel collect data on merchandise movement from showroom to fitting room and back. Using a combination of data captured through the RFID sensors, overhead traffic counters and POS data, sales managers can determine which items, sizes and styles are being tried on, compared to which are purchased. This data is used by an apparel retailer to optimize inventory by identifying bestsellers and items that can be reduced due to low demand. In addition, by understanding what merchandise is tried but not purchased, the retailer is training staff to better identify what guests want, and their sizes, when they enter the store. This reduces try-ons, improves the customer experience and improves the conversation rate.
Traffic data combined with POS transaction and labor allocation data can also help retailers determine if a store is staffed properly. If retailers know when fitting rooms are busiest, they can schedule more sales associates to help shoppers during those times. The insight can also be used to train employees on how to interact with shoppers and guide their path to purchase. For example, while POS data can tell you the time of day when you have the highest conversions, it can’t tell you if customers tried on and abandoned merchandise due to a lack of sales assistance. IoT can give you the data to make those kinds of conclusions.
By tapping into sources of data that have existed outside of reach of physical stores, retailers can finally uncover the root cause of common challenges that erode brand loyalty, customer satisfaction and revenue streams. IoT brings new sources of information together that allow retailers to uncover missed opportunities — and provide the insights needed to turn these opportunities into outcomes.
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