Retail

Black Friday or black hole Friday? IoT and retail

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We all know that Black Friday can make or break a year in retail. It is estimated that this year, a record of over $3B in on line sales were generated ($1B from mobile devices). And for those who follow this space, the battle continues over how best to engage potential shoppers both in store and online. Over the past decade we have seen many advances in online retailing ranging from dynamic pricing to predictive buyer behavior, all with the goal of providing better service and driving increased revenue. All of this has been achieved through the creative use of data captured through the experience.

But have in store experiences kept pace with the online experience? Is the in store data that is being captured falling into a black hole? Is the potential data being captured at all?

Retail and IoT

If you look at a traditional retail store as a “shopper laboratory” and approach it through a lens for IoT, you can start to envision the possibilities. Many, like Media-Saturn-Holdings, are taking steps to merge their online and in store shopping experience. A few examples of places to start:

Shopping carts

Upon checkout, you will know what they purchased which then goes into your customer database. Would you like know more about the order in which they purchased their items and see if there is a pattern? How about knowing what they almost purchased? With key sensors in the right locations you could start to uncover this. Start with the shopping cart, placing a sensor that can scan the RFID tags on each item and keep track of the order in which they were placed in the cart. Then move onto motion sensors on the shelves. This way you can track the movement in front of each item on display and correlate that with the shopping cart. You can start gathering data around the products the shopper looked at, maybe just for periods longer than 10 seconds, but did not select the item. What made them move on? Was there more you could have done with the display? Was the price point wrong?

This is the kind of insight that allows a retail to start looking for trends. Is there a connection between certain offerings, in the order in which they are purchased, in the price points?

People flow

Ever wonder if there is an ideal way to have your customer to walk through the aisles of your store? With IoT you can model this. With motion sensors connected to a platform with deep analytics, one can start to correlate the current flow of customers with check out receipts. Much the same way online retails can track a customer’s digital journey of page views and their shopping cart at checkout. Then you can tease out where opportunities lie to not only increase sales, but increase customer satisfaction.

Weather data

Ever wonder how the weather outside your store may be impacting the sales inside the store? Maybe you should. Depending on the business you are in, there can be a strong correlation. For example, working with some coffee shop retailers we have found that a significant change in the weather (both warming or cooling as well as precipitation) can have a strong impact on the more popular choices of beverage. By accurately mapping weather data with specific retail locations, you can start to predict what are about to be a very popular items, ensuring you have them in stock and promoting accordingly.

These are just a few examples of how in store retails can leverage IoT to capture the nuggets of insight from their shoppers this holiday season. We can all agree that the goal is to capture these insights to help improve the bottom line vs. letting them be lost to the bottom of a black hole.

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