Read about how Computer Vision technology can provide efficient face recognition to identify known and potential offenders in retail stores.
With the advance of technologies and online shopping, customer behavior has rapidly evolved into a completely new animal. By joining the vast pool of already existing customers, Millennials and Generation Z have further added to the diversification of spending habits and purchasing power of consumers around the world.
As reported in a recent rescearch by interaction management firm Epsilon, the older generations still prefer shopping in brick-and-mortar stores, Millennials shop in-store and online equally and Generation Z are twice more likely to use an online-only store than any other generation. According to Epsilon’s proprietary transactional data on the 12-month spend of 85 million US consumers, Generation Z shop most often, while baby boomers spend the most in a year.
In a world where consumers increasingly differ in shopping habits, household income and propensity to spend, retailers and marketers need to be much further ahead of the game than before. If they want to understand which products and campaigns excite which segment of their buyers, they need to change their approach radically.
Marketers face a unique challenge trying to engage a diverse pool of consumers across generations at any given time. To stand out, brands must own every interaction with their customers and deliver more human experiences that are driven by data, says Stacey Hawes, President, Data at Epsilon.
To be able to understand customer segments better and to be more on target with their marketing and promotional campaigns, retailers have a pressing need to acquire deep, data-driven insights into their increasingly diverse customer base.
Regardless of generation and purchasing power, the top three reasons for consumers to pick a particular retailer are: great deals, availability of products and convenience to shop, the Deloitte Consumer Change Study 2018 showed.
And while there is no silver bullet that can solve all these challenges, more and more companies are turning to computer vision technology to aggregate customer videos in order to analyze shopping behavior at their stores. This approach allows retailers to follow unobtrusively general demographic patterns, adapt inventory layouts at their stores and fine-tune promotional offers targeting specific customer segments.
Armored with such smart customer demographic analysis, marketing teams have a reliable tool to gauge campaign effectiveness, while merchandise teams have a clear picture of sales per demographic segment. Thus, retail companies can boost up-selling and complementary sales, spend marketing investments better and increase their return of investment.
Ontotext’s customer demographic analysis solution is based on computer vision technology, developed within Sirma Group since 2013 and now complementing Ontotext’s portfolio within Sirma AI. It helps retailers track and analyze customer traffic and behavior in stores by identifying different consumer profiles based on demographic characteristics. The system can collect and analyze data from both brick-and-mortar and online visits to give companies an all-round view of all customers and their behavior by demographic segment.
With an increasingly diverse consumer base, having a deeper insight into shopping behavior gives retail stores huge advantages in improving the overall customer experience. Click To Tweet It allows them to tailor themselves better to their high-value customers, offer richer assortment of goods and have more focused advertising and marketing. As a result, their customers have more reasons to choose them over other options and to come back.
This Intelligent Customer Demographic Analysis solution was developed for a big Bulgarian retail chain.