Jessica Powers | Sep 21, 2022

With online sales steadily increasing every year, tech companies are finding new ways to optimize the e-commerce and retail industry. Big data in retail is one such example, as startups implement technologies like artificial intelligence and machine learning for consumer insights and predictive analytics that transform the shopping experience for both consumers and merchants.

What Is Big Data in Retail?

Big data in retail refers to retail companies collecting large amounts of personal, preferential and behavioral information from shoppers, including purchase history, often to influence future purchasing decisions.

From style preferences and fits to overall purchase behaviors, big data helps businesses learn more about consumers and how to retain them as customers by offering an enhanced and more personalized shopping experience.


How Retailers Collect Data 

There are a variety of ways retailers can collect consumer data, both for brick-and-mortar shopping and online shopping. Perhaps the most important tool when it comes to collecting consumer data is the point-of-sale system a retailer uses. A POS system collects the baseline of information for every customer: personal information, payment data and purchase history. Retailers use POS systems to create reports and by exporting raw data and analyzing it. 

Another way retailers can collect consumer data is through surveys. Surveys may be a highlighted link at the bottom of a physical receipt, but they are also easy for retailers to conduct online — especially when consumer emails are attached to the purchase. Surveys are often used to collect customer feedback and sentiment about a brand, sometimes with a discount offered to the customer upon completion of the survey. 

Retailer websites and apps are another easy way for retailers to collect information, sometimes through cookies or ad-tracking. These features can track consumer preferences, what they click on or search for. Retailers might also use third party companies to help them collect consumer data, track purchase behavior and implement SMS or email marketing campaigns. 


Big Data Retail Companies

The e-commerce industry and the amount of online retailers are constantly growing, but there are some companies that specialize in providing consumer insights through big data. Retailers and brands can utilize these companies and their tools to grow their customer base. Here are a few companies using big detail in retail to change the way we shop online.


Location: New York, New York

Bluecore is a marketing platform using customer data to create email campaigns for brands and retailers. The platform combines website, product and customer data to help brands understand customer interests and behaviors. Unifying artificial intelligence and real-time data, Bluecore optimizes the timing of campaigns to boost revenue and offer a more relevant shopping experience.


Location: Anaheim, California

Da Vicni offers cloud-based warehouse management systems for e-commerce, brick-and-mortar retail as well as wholesale distribution. Da Vicni’s WMS handles orders, inventory, fulfillment and shipping. The WMS also organizes small parcel label printing and tracks shipping schedules. Organizations can use the company’s cloud-based software to compile inventory data, scan barcodes in remote settings and locate the best online shipping rates.


Location: New York, New York

Yotpo is an e-commerce marketing platform that retailers and  direct-to-consumer brands use to increase growth through SMS marketing, subscription programs and customized loyalty programs. The platform also helps businesses display reviews and ratings from consumers who post their photos and videos. 


Location: New York, New York

Retailers use AB Tasty’s AI-driven platform to create personalized experiences, like campaigns tailored to consumer’s interests using natural language processing, or tracking consumer engagement levels. AB Tasty creates data lakes for retailers that they can easily pull from to inform their personalization campaign decisions. AB Tasty’s client base has included L’Oreal, USA Today and Ashley HomeStore.


Location: New York, New York

Cuebiq makes location intelligence technology using a huge database of U.S. location data. It uses opt-in location data from consumers to provide insights into offline shopping behaviors and help retailers make more informed inventory decisions. Cuebiq’s technology helps brick and mortar locations map out customer journeys and make decisions based on data.


Location: Chicago, Illinois

Fit Analytics uses a massive dataset of sizing information to provide accurate size recommendations for apparel brands around the world. The data platform offers a suite of solutions that give customers data-driven sizing recommendations that lead to return customers and decreased return rates. After using Fit Analytics, Simons, a Canadian fashion brand, saw a conversion rate increase of two percent.


Location: New York, New York

Linc is a customer care platform for e-commerce businesses. In addition to its automated customer service interactions, the company provides marketers and customer success teams with better insight into customer intent. Integrated with multiple channels, Linc uses data from sources like communication history, profile details and order history to give customers a more engaging experience.


Location: Boston, Massachusetts

True Fit is a personalization platform for apparel retailers. It provides consumer preference data, fit ratings, sizing recommendations, style ranking and merchandising analytics. True Fit’s Fashion Genome Project is a comprehensive collection of fashion and apparel-related data sourced from a network of brands, retailers and consumers, which the platform uses to understand shoppers and predict what they will like.


Location: Boston, Massachusetts

Optimizely provides B2B, B2C and shopping solutions for retailers to utilize. Some of the company’s shopping solutions include targeting software that tracks historical behavior data and cart solutions that streamline the checkout process. Optimizely closes the gap between customer data and marketing systems, integrating data from various APIs and e-commerce platforms.

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