When thinking about e-commerce personalization, product recommendations are often the first thing to come to mind. One-to-one product recommendations are incredibly important to any retail site, but they are only one small piece of a personalized experience. Anything from featured brands and categories, site navigation, search results, and more can be personalized using a combination of machine-learning algorithms and rule-based personalization.
To implement personalization across the site, rather than in just a few predetermined slots on the homepage and PDPs, marketers must make personalization a fundamental component of their e-commerce strategies. Use this infographic to give you some ideas to get started.
Machine Learning for E-Commerce Examples
Let’s take a look at a few examples.
Not all recommendations are for products. Any place on your website that promotes specific brands can be personalized for individual preferences to help shoppers find their favorites. This gives you the opportunity to show the brands that are more likely to catch the attention of each shopper to encourage further exploration of your site.
Individualized product sorting
The way that products are sorted on a category page is often determined by the marketer. While options to allow shoppers to sort by price or filter by color are often included, the pages are not personalized until the shoppers sort and filter for themselves. In addition to providing these self-sort capabilities, you can also leverage algorithms to automatically sort the products on the page for each shopper based on their unique tastes and preferences. This helps them quickly find products for them to explore.
Personalized incentive messages on the cart page
The cart page is a great place to provide that one last touch to help the shopper make the decision to purchase. Cost of shipping has been cited as the top reason for cart abandonment among shoppers, so it’s a good time to provide personalized inventive messages to make the cost of shipping seem worth it for the shopper. For example, you could provide an individualized product recommendation that a shopper could add to the cart to get free shipping.
E-commerce sites can leverage rules and machine learning to create personalized experiences across the site, beyond product recommendations.
If you’re interested in learning more about how Evergage can help personalize your e-commerce experience, request a demo today.