With the advancement of AI and machine learning, new digital technologies are moving from the realm of concept to reality. One such technology is computer vision.
Only a few years ago, computer vision was considered by some to be in its “nascent stage” but the technology clearly had potential. Now, we see its use extend to a wide range of applications in the retail market. And retailers are using computer vision to gather customer data in new and exciting ways.
What is computer vision exactly?
The basic definition of computer vision is “a field of computer science that works on enabling computers to see, identify and process images in the same way that human vision does, and then provide appropriate output.” Human eyes work in coordination with the brain in a dazzlingly complex process. Until recently, computers struggled to recreate that process at anywhere near the speed of their human counterparts.
However, the technology has made great strides in recent years, with the ability of computer vision to replicate a complex human process at scale.
Microsoft CEO Satya Nadella urged retailers at NRF 2020 to harness the ever-growing access to customer data. As Deborah Weinswig mentioned in her post-NRF notes for Coresight Research, “One large generator of and compelling application for data is computer vision, which was demonstrated by numerous vendors at the show.”
Because of technological advancements (namely in AI and machine learning), retailers can operate and maintain computer vision with relatively little technical support. That’s leading to an array of new uses in retail settings.
Gathering customer data to improve experiential moments
In addition to powering unstaffed retail stores and enabling real-time inventory tracking on shelves, computer vision is being used in intriguing ways to gather customer data and provide unique customer experiences.
For example, cameras (which often look like traditional security cameras) can monitor customers of clothing retailers to track metrics like dwell time, items picked up off the racks, items tried on, etc. And if an item is frequently tried on, but not purchased, that information can also provide invaluable insight that can be used to increase future conversions. Meanwhile, customers are going about their shopping normally, with no intrusions.
As another example, smart kiosks leveraging this technology can determine the gender age of visitors, then show unique videos based on that data or provide a custom coupon to be used in the store. The retailer is able to collect customer data, and the customer gets a tailored shopping experience.
How can companies make the most out of the data they gather?
With retailers exploring new technologies specifically intended to gather customer data and wield it to provide more personalized experiences, systems to organize and manage that data are becoming even more important. Organizations need both a foundation for advanced master data management (MDM), as well as an open architecture capable of enabling future technology.
MDM will be crucial to powering these huge data sets and ensuring the data being collected will actually result in differentiated experiences that are personalized for customers. Another crucial factor will be the organization’s ability to manage an “insight ecosystem.”
For example, the EnterWorks Multi-domain MDM platform, with Combinatorial Intelligence reporting, allows companies to combine master data for customers, products, locations, assets, etc. to glean contextual insights. This type of cross-domain intelligence can be used to gain greater analytics and deliver the right product/offer, to the right customer, at the right place, at the right time.
To learn more, download our White Paper: Cross-Domain Intelligence with Multidomain MDM.