Retailers are working quickly to implement new technologies to meet consumer demand, enhance efficiency, and make the retail customer experience (CX) as frictionless as possible. With a wide array of use cases across the entire commerce landscape—both on the back and front end—retail technology is changing the industry. 

What is retail technology?

Retail technology refers to digital software, platforms, and innovations that help retailers manage and optimize their operations. Typically, retail tech is used to improve the CX, increase efficiency, and optimize profitability for retailers.

Examples of retail tech 

Retail tech has a variety of uses, including payments, generative AI, virtual reality (VR) and augmented reality (AR), retail CX, and marketing platforms like customer data platforms (CDPs) and composable commerce applications. 


  • Buy now, pay later (BNPL): Since 2019, BNPL adoption has exploded, particularly among Gen Z. Though the post-pandemic growth rate seems to have tapered (growth is forecast to slow from 18.7% in 2023 to 4.8% in 2027), BNPL services are still expanding. However, we think BNPL providers will need to diversify across age and income spectrums if they want to stay relevant.  
  • Digital wallets: More time spent online has increased the viability of digital wallets. Apple Pay’s seamless integration within its operating system has given it an outsized stake in the mobile payment ecosystem, while Google Pay has dominated the broader ecommerce space. Like BNPL, digital wallets have benefited from younger generations. But they also suffer from a lack of consumer loyalty; leaders in the digital wallet space will need to do more to grab consumers’ attention by distinguishing themselves in this relatively new field. 

Generative AI: Since the release of ChatGPT in November 2022, businesses have scrambled to integrate generative AI wherever possible. Marketers have wasted no time in adopting generative AI into their content-writing processes: 58.9% of marketers worldwide said they were using AI to optimize content from as early as November 2022, according to an Aira survey. Retailers are also integrating AI tools into their platforms. Chatbots are one of the most popular use cases, with users ranging from social media platforms like Snapchat and TikTok, to retailers like DoorDash and Shopify. Some use cases, however, haven’t picked up adoption. Due to a lack of a visual interface and questions over data security, for example, voice commerce has been mostly ignored by consumers. 

In-store tech: Starting with the rapid, widespread adoption of cashierless checkout stations, brick-and-mortar retailers have been focused on adopting innovative in-store technologies to draw consumers and generate buzz. Amazon is leading with smart carts, “just walk out” technology, and biometrics being brought to its Fresh and Whole Foods Market locations. However, competitors like The Kroger Co. have begun adopting some of the tools Amazon pioneered, making the space more competitive and its future less certain.


  • VR adoption has been a mixed bag. While the metaverse’s hype has died down considerably, our definition of VR also includes 2D experiences like Google Maps’ Street View and popular virtual worlds like Roblox, which account for nearly half (48%) of VR users, according to Insider Intelligence’s forecast.  
  • AR developments include try-on technology and filters on social media platforms like Snapchat, both of which have remained popular, particularly among younger generations.

Back end: 

  • Headless commerce is a form of ecommerce in which the customer-facing front-end user interface (i.e., website, mobile app, etc.—collectively known as the “head”) is separate from the back-end business data and transactions layer (i.e., customer relationship management, inventory management, checkout, etc.—the “body”), which then communicate via an API.
  • Composable commerce is a fully modular approach that allows retailers to pick and choose among individual service vendors (known as “best in breed”) to suit their specific needs and objectives.
  • CDPs collect and house an advertiser’s or publisher’s first-party data about their own customers to create a single, holistic view of each customer over time (e.g., BlueConic, Segment, and Tealium).
  • Demand forecasting is the method of predicting demand for products or services based on customers’ data. 
  • Retail CX is the sum of interactions a customer has with a given brand, from initial contact to post-purchase.
  • Loyalty programs are marketing tools that offer rewards and discounts to customers every time they engage with a brand, which is meant to entice these customers into becoming repeat buyers. 
  • Customer service provides assistance and support to customers who are engaging with a brand’s product or service. Recent innovations with AI chatbots have been employed by many brands looking to streamline their customer service experience. 

Retail tech can be broken into many different subcategories. Here are a few of the most relevant and applicable examples to marketers (along with how they differ from the broader retail tech definition):

  • Marketing technology (martech): Our definition of martech encompasses technology, software, and services used to support the management and measuring of marketing and advertising. While aspects of the two overlap (particularly on the back end, where products like CDPs and other efficiency-related capabilities are concerned), martech is ultimately just one facet of the greater retail tech whole. 
  • Fintech: The fintech industry merges financial services with technology, and is designed to modernize how individuals and institutions interact with money. Fintech companies harness technology, such as AI and blockchain, to provide more agile, cost-efficient, and user-centric solutions to conduct transactions, manage investments, and provide more seamless alternatives to traditional banking. Similar to martech, fintech is an industry-specific variation of retail tech, focused on the streamlining, optimization, and profitability of the businesses and consumers within the financial services sector (e.g., cryptocurrency and NFTs). 
  • Commerce/ecommerce tech: Unlike martech and fintech, commerce tech is operationally specific, not industry-specific. It refers to the payment- and transaction-processing aspects of retail tech, and therefore has some overlap with fintech. Commerce tech includes tools like cashierless checkout and point-of-sale terminals. 

What should marketers look out for when adopting retail tech?

Marketers should recognize that new technologies, especially those using AI, introduced to their professional space—either as products to sell or tools to use—should be approached with caution. Privacy, security, and safety remain top concerns for consumers, so maintaining a healthy skepticism about the retail tech being adopted is always a good idea. Using tools like generative AI for content creation may be a game changer, but no matter how advanced the technology is, it’s no substitute for keen human oversight.