Steve Wilkes, Striim Founder and CTO, walks through the Striim application that makes real-time offers to customers while they’re in a store by combining beacon, sales, and inventory information.
Today we’re going to take a look at an application that makes real-time offers to customers while they’re in a store. By combining beacon sales and inventory information. Imagine you’re a retailer, you have many stores and you want to track the sales in those stores. Additionally, you want to make offers to your customers while they’re still in the store. To do this, you provide your customers with a phone app and place beacons around the store that are able to track the movement of that app using Striim. You then built an application to monitor that beacon data and sales data through change data capture from the original database. You can enrich all of this with the inventory product and customer information to give that data context and that will enable you to send offers to your customers and monitor activity on the dashboard.
The logic to send the offers is customizable by, in this case we’re sending the offer if the customer stays close to a certain product for a certain amount of time or if they look at a product and leave and then come back and do that a certain number of times and we’ll only send the offer if we have sufficient inventory to actually allow them to purchase it. The application itself has a dashboard that allows you to track the sales per store and look at the sales traffic over time so you can see how it varies depending on the time of day and also track the types of the items that are actually being sold and the offers that are being made to customers in real time. In addition to this chart, each offer will result in an alert that is sent to the dashboard and in that alert you can see details of the customer that was sending the offer, what a store they were in and what the offer was. If you drill down to a particular store, then you can see a heat map of where the customers actually are in real time so you can see which isles are traffic the most and how that varies over time. You can also see the sales for that particular store over time and what offers were actually being made to customers in that particular store and crucially we’re also showing the difference that making these realtime offers make to how much customers actually spend.
Then it’s take a look at how this was built at the backend. All of the processing is through the streaming data flow. We have sources at the top for the beacon information and the sales data pulled from a database using change data, capture the inventory information products and customers are loaded into in memory caches so that they can be joined in real time. If we look at one of the processing flows, you can see the processing is done through a query and this is a query that’s checking for customers staying in one place for too long or coming back to the same place multiple times. If either of those queries are met, we might make the customer an offer, but first we need to check to see if the inventory is sufficient. So you can see that 20% mark there, the dashboards that are built on this data flow, I fully customizable. Each visualization is powered by a query and configured through a very simple drag and drop configuration that enables you to map the query to the visualization. If you’d like this application, subscribe to our channel to see more interesting ways of using a streaming integration and intelligence.