By all accounts, the adoption of eCommerce is accelerating—a result of COVID lockdowns, closings, and a very real fear of exposure to the virus. To combat supply chain disruptions and other uncertainty, consumers of all ages turned to digital channels to purchase goods across every retail category. In 2020, online spending represented over 21% of total retail sales—that’s more than $861 billion dollars spent online, up 44% compared with 2019—an astonishing shift.
Digital commerce, already an important part of the retail ecosystem, has become even more essential in 2021, with eMarketer forecasting that US consumers will spend over $933 billion online, up nearly 18% compared with 2020.
Brick-and-mortar spending remains comparatively modest, with eMarketer predicting a 6.3% increase in 2021 versus 2020, although this still represents the strongest growth since 2011.
There’s no question that eCommerce has become essential for consumers and retailers alike. The staggering growth in eCommerce spending is itself, a trend. But one of the essential “trends within a trend” is the rapid adoption of eCommerce Personalization, a key technology that consumers are increasingly demanding and retailers are increasingly embracing. Personalized product recommendations across all customer touchpoints and channels are fueling eCommerce growth and continuing to evolve as the technology that powers personalization evolves.
Below, we discuss three exciting and key trends in eCommerce personalization that retailers are adopting now (or planning to adopt in the near-distant future). These include AI-powered product recommendations, advanced personalization with image recognition, and end-to-end personalization with native order management.
Trend 1: AI-Powered Product Recommendations
AI and Machine Learning topped our 2021 eCommerce personalization trends list, and they’re enjoying a well-deserved moment in the spotlight. According to research firm SPD Group, nearly 30% of retailers currently use AI and machine learning, up from just 4% in 2016.
Monetate uses AI to help predict changing consumer intent which fuels personalized product recommendations, content placement, and product and home page designs and layouts. AI-powered product recommendations facilitate one-to-one segmented messaging across all consumer touchpoints, making individualized personalization scalable regardless of the audience size. Here are a few ways AI enables retailers to scale personalized recommendations:
- AI technology dynamically updates product details pages based on historical data, third-party insights, and real-time visitor behavior.
- AI-fueled recommendations encourage personalized cross-sells and push high-margin products to the consumers most likely to respond.
- AI-driven recommendations combined with testing and personalization across touchpoints enable retailers to rapidly refine offers and content for optimal performance.
Consumers are willing to share their data in exchange for better, more personalized shopping experiences, but building trust is an incredibly important part of delivering a good eCommerce experience. To this end, retailers can leverage AI to provide more transparency to shoppers who may be concerned about how merchants use their data by labeling product recommendations with explanations such as “it’s in your size” and “it’s a similar style to what you’ve previously purchased, etc.
Trend 2: Advanced Personalization with Image Recognition Technology
Another important eCommerce personalization trend for 2021 was the adoption of image recognition technology within the product recommendations ecosystem. Retailers can use image recognition technology to identify products within images and videos, then use that data to refine product recommendations further and customize content.
From the customer’s perspective, this could appear as a “shop the look” recommendation on the retailer’s website or an email notifying someone about items they’ll love (based on past browsing and/or purchase behavior.) Image recognition technology essentially gives retailers the ability to create richer online experiences with shoppable content.
Image recognition tools use AI and machine learning technology to automate the process of image analysis, assessing a wide range of image characteristics and combinations (colors, sizes, patterns, styles, etc.) which can be combined with other customer signals, behaviors, and attributes to enable more accurate product recommendations targeted to each individual customer.
AI-driven product recommendations enable retailers to provide 1-to-1 recommendations, for example, by notifying a customer that there are new arrivals in their favorite color or fabric. Image recognition can also enhance the shopping experience for consumers by making it easier for shoppers to search for products with similar styles, patterns, and colors.
Trend 3: End-To-End Ecommerce Personalization with Integrated Personalized Search & Order Management
End-to-end eCommerce personalization with native order management is one of those trends that’s become a necessity for retailers in the past 18 months since the pandemic disrupted the normal flow of how we buy and sell things.
Extensive eCommerce personalization is only possible when eCommerce is integrated with native order management technology.
What this essentially means for eCommerce personalization is that the entire customer buying journey is optimized and personalized regardless of what touchpoints customers use to interact with a retailer or where they are in the buying journey. End-to-end personalization gives customers access to a retailer’s full product catalogue and inventory, enabling personalized offers based on search results and even connecting these offers to shipping times.
Personalized search, in particular, is integral to the digital shopping journey, driving high ROI and creating relevant shopping experiences that customers demand. Our own research has shown personalized search to be the most substantial driver of ROI. Over 30% of the 400 eCommerce executives we surveyed for our 2021 Unified Commerce Report said that personalized search drove an ROI of 200% or more.
Throughout the pandemic, retailers and customers have been embracing frictionless fulfillment options including buy-online-pickup-in-store (BOPIS) and buy-online-pickup-curbside (BOPAC). End-to-end eCommerce personalization with order management enables retailers to personalize these newly popular fulfillment options, creating a seamless (and customized) shopping experience for each customer.
Ramping Up Ecommerce Personalization for 2022
Our top three trends—AI-powered product recommendations, image recognition technology, and end-to-end personalization with end-to-end eCommerce personalization with integrated personalized search and order management all work together to deliver better overall shopping experiences. But these are just a few ways that eCommerce personalization is ramping up in 2022 (and beyond).
As eCommerce personalization technology evolves, we predict that personalized product recommendations will become even more relevant, customized, and highly personalized, becoming an essential way to deliver outstanding eCommerce shopping experiences.
Accelerating this trend is the technology that powers it all, connecting online and offline channels, and enabling companies to personalize content across all touchpoints (at scale!)
We invite you to take a deeper dive into our platform to learn more about how Monetate’s personalization platform works or learn about the more than 1000 brands that have helped make Monetate the #1 personalization platform.