Monitoring hundreds of millions of events daily, Euclid’s solution is built for scalability. With new customers being added every day, the number of daily events continues to grow. How can these events be leveraged to enhance customer knowledge and provide powerful insights never before seen by a brick and mortar business? Can this enormous dataset be used to predict shopper behavior? What is the future of Euclid's data network?
I was tasked with designing an interface and user experience that would act as the foundation for the future product offerings at Euclid.
In order to better understand the value that Euclid can provide for our customers and help shape the future of the Euclid network, in-depth interviews were conducted with both existing and potential customers. These interviews were crafted to help gain a better understanding of the limitation of the existing product and provide unique insights into the growing needs and desires of each customer.
What can customers learn about their shoppers that add value above and beyond the basic data provided in the current product? We conducted in-person interviews that led to powerful discussions of features we had not yet thought of. These discussions were fluid in nature, allowing for our customers to help us think outside the box to what the future may hold. We also leveraged our internal customer support and business development groups better understand customers' needs and desires.
We listened to our customer’s needs and desires, and began the important step of brainstorming potential new features through lengthy whiteboard sessions. We asked ourselves: Were there any common themes that developed throughout our interviews? How/why do our customer look at their data differently? How can we add value in the short-term? What concepts would be achievable far down the road?
An important member of these brainstorming sessions were with our data science team. They were able to provide input into the difficulty of some of these concepts and what it would take to build the data models for these features now and in the future. Of course, they also provided input on the sobering reality that some of these features are simply not achievable.
Walking out of these brainstorming sessions, we had a much better understanding of what features will have the most impact for our customers. We were also able to create a general roadmap for how/when these features could be built. But first, they needed to be designed.
How does a retailer know if their marketing campaigns are working? Are they bringing customers to their locations?
Location analytics can provide detailed information about customer behavior including trends based on marketing locations and impressions.
How long are customers shopping in retail locations? What type of customer duration segments are there for a given location?
Duration analytics is a powerful new tool that can give important insights into customer behavior. Duration segments can determine staffing needs, show effectiveness of promotions, and provide information about multi-floor layouts.
What do retailers know about their customer's loyalty and behavior? How often do customers return to a location and where do they go within that location?
Customer retention is critical to the success of a business. Loyalty and retention metrics can be used to create a detailed shopper profile of customers, providing important analytics for brick-and-mortar businesses.
