I don’t know about you, but when I walk by a vending machine and see one of my favorite snacks, I immediately have a snack attack. Often times these attacks go unanswered because I typically don’t carry cash in my pocket, or for the times when I do, the machine is broken.
Well, enter smart vending -- and the answer to my vending machine woes!
Today, thanks to recent developments in what’s called the Internet of Things (or IoT), I will now be able to use my smartphone to satisfy my Doritos craving -- from a machine that is almost always working and fully replenished with my favorite snacks.
Using big data, cloud, mobile and analytics technologies, a smart vending machine scans my smartphone and wirelessly bills me for my chips. Sensors embedded in the machine will collect a wide array of data, not only about my choices and preferences, but also about the machine’s inventory and working status. This data can then be analyzed by operators to create a better, more engaging experience for me, as well as other customers, in the future.
And, for the operators, insights into this data will help increase operational efficiencies and drive greater profits.
Real Time Response to Customer Demands
Traditional vending machines have never been able to track what has been sold, what a customer prefers or if it is broken, so vending machine operators typically replenish and service machines on a set schedule. Not only does this disappoint customers like me when our favorite brands are out or if a machine is not working, but it also results in costly operational waste and ineffective inventory management.
A smart machine collects a tremendous amount of data -- such as customer purchases, inventory levels, machine temperatures and operating functions -- that operators can use for real time decision making.
The consumer purchasing information alone is highly valuable, as operators now have the opportunity to proactively engage with customers in highly personalized ways. With data that is collected via smartphones, operators can build extensive profiles based on personal preferences and transaction histories.