Those findings just skim the surface of the power of a personalization strategy not only as a way for e-commerce businesses to enhance their customer experiences, but to increase revenues, too.
Here are five trends that are currently changing the game.
1. Businesses Are Immersed In Omnichannel Personalization
Previously, brands were focused on forcing consumers down a narrowly defined sales funnel, which often failed to connect with them. In a June 20 study, 62% of respondents said they love the in-store buying experience because it allows them to get exactly what they want, yet 31% said brick-and-mortar stores fail to provide the easy access to in-depth product information they can get online.
Through omnichannel personalization, retailers are combining offline and online data in real time to build comprehensive customer profiles that deliver better, more personalized experiences across all touch points. This helps ensure that customer experiences and relationships remain consistent regardless of where and how consumers interact with the brand.
For example, Sears Hometown and Outlet Stores are using local inventory ads to drive in-store visits. These ads show nearby store locations and store hours to customers who are conducting an online search for a particular product.
As a result of these local inventory ads, the company has seen in-store visits increase by 122% compared to when they only used product listing ads that did not include information about local stores.
2. Machine Learning Is Improving Personalization Efforts
Over the past few years, we have seen massive improvements in machine-learning technology, making it easier for marketers to automate their personalization efforts and anticipate the support needs of their customers.
Although 83% of marketers said in a 2017 study that they were familiar with machine-learning solutions, application remains low, with only 14% of respondents saying they were using them. But 33% have confirmed that they will be investing in machine learning in their communications, with more than half acknowledging that these solutions will help with real-time personalized advertising and optimizing their message targeting.
Sites like Spotify have leveraged machine learning to provide highly personalized experiences to their users. For instance, each listener has a personalized playlist created by Spotify based on the person’s listening history and music preferences.
3. Businesses Are Providing Personalized Pricing
Consumers have a diverse range of preferences—not just limited to their differing needs for products and features, but also in terms of pricing. As a result, many more e-commerce retailers are offering personalized pricing and deals to suit the demands of each customer.
Retailers are getting better at analyzing their customers’ purchase behavior and price sensitivity as well as their propensity to buy. They then use this data effectively with their CRM to create customized promotions and attractive incentive offers suited to each customer in an effort to improve their chances of driving conversions.
4. Businesses Are Making Smarter Recommendations In Social Retargeting
With the growth in retargeting solutions, e-commerce retailers are re-engaging their audiences with smart product recommendations based on customers’ previous interactions with brands. Instead of posting generic social ads, for example, retailers can showcase products with ads that are highly relevant to each customer. And retailers can keep track of purchases made by the customer through other channels and avoid using those products in their retargeting ads.
Many retailers also are using retargeting to showcase ads for products that customers have left in their shopping carts, offering exclusive deals to drive conversions.
5. Retailers Allow Customers To Continue Shopping Where They Left Off
Websites like Netflix have revolutionized personalization with features like Continue Watching, which allows users to continue a movie or show that they’ve partially watched. It also provides easy access to the next episode of a show that they have been binge watching.
This approach also is being leveraged for e-commerce personalization to enhance the experiences of retailers’ returning customers. By remembering the preferences of shoppers based on their previous sessions, retailers allow customers to pick up exactly where they left off when they return to a site.
For example, a shopper who has mainly looked at men’s sportswear in a specific size range will get to see a page displaying similar products when the person revisits.
E-commerce personalization has seen significant improvements, with more and more businesses offering hyper-personalized recommendations and shopping experiences on multiple channels and at every touch point.
As e-commerce businesses increasingly take advantage of machine learning technology, they are bound to see even greater improvements in their personalization efforts in the near future.