While personalization is not a new concept and has increasingly become a pillar of e-commerce business strategies, many companies are just scratching the surface of deploying a fully personalized shopping experience. For example, when considering personalized recommendations, most people think of carousels on the homepage that recommend new products, popular items, or reminders of what the user has purchased or browsed before. However, there are numerous e-commerce personalization examples that may hold untapped potential for online retailers. To maximize the ROI of personalization, a business will need three things:
Here are 15 examples of personalization in e-commerce.
E-commerce stores and marketplaces with hundreds or thousands of SKUs and many product categories are faced with a tough challenge: helping customers find products they’ll like. Greater discoverability of items customers leads to greater conversion rates, while poor discoverability inhibits customers from making the purchase.
To increase discoverability, many e-commerce sites recommend categories on their homepage, paired with smart headlines. Examples of recommended categories include by style or type, brand, size, color, and so forth. Being able to cut through the noise sooner and recommend relevant items to a user based on their preferences can prevent them from feeling overwhelmed or frustrated by a large catalog, eventually leading to a website bounce.
“Personalization is a powerful tool for e-commerce stores to create a more engaging and relevant shopping experience,” says Nick Hurst, Head of Product at We Make Websites. “When implemented correctly, personalization can work seamlessly to enhance the overall shopping experience.”
We Make Websites enabled an attractive category personalization deployment for Frame Clothing. When a customer selects men’s or women’s clothing and then goes back to the homepage, the carousel and image blocks are all customized to the user’s choice. This simple but effective form of category recommendation leads to more opportunities for natural product discovery.
Another e-commerce personalization example is recommending products while a user is searching. When a customer clicks or taps a search bar, they are either searching for a specific product or hoping to discover new products they haven’t seen yet. If their intent is new product discovery, a personalized recommendation can be extremely useful next to the search bar.
Additionally, some search engines have mechanisms in place to enable predictive text when a user is searching for a specific keyword or product, which enhances the user experience of discoverability. For example, the search term “women’s hats” would result in a quick preview of womens hats that are recommended for that individual user.
The concept of personalized recommendations has varied over the years. Some think of recommending previously viewed or purchased items, alongside new or widely popular ones, is a form of personalization. However, this doesn’t truly take into account a person’s current interest in something. If they just bought something, or they viewed something without purchasing it, they’re unlikely to do so on a follow-up visit. Many e-commerce vendors supplement this form of personalization with recommendation engines that leverage third-party cookies to serve up items to users based on their demographic information. This also has limited capability around catering to a user’s tastes, though.
Behavior-based recommendations are an e-commerce personalization example that represents a paradigm shift in the concept of personalization. Because they based solely on first-party data and user actions on-site (clicks, scrolls, likes, etc.), the recommendations a behavior-based method serves to users are a much better representation of what the person is interested in. In addition to being a more sophisticated way of achieving personalization, behavior-based recommendations also enable greater success in other examples of e-commerce personalization, such as on other webpages, via email and SMS, and so forth.
Email and SMS are important channels for e-commerce marketers focused on retention and loyalty. Bringing thoughtful personalization to email and SMS is among the most effective ways to re-engage customers. Most modern e-commerce companies already deliver personalized recommendations via email or SMS. This enables businesses to stay top of mind for their customers when they’re off-site, but also increase the likelihood of a delayed conversion through reminders of cart abandonment, previously bought items, and re-stocks.
With behavior-based recommendations, emails and SMS messages can be personalized to an even more effective degree. By taking the actions made on-site by a user, follow-up emails or texts can include item recommendations based on what they interacted with. These recommendations would not be limited solely to things that a user clicked on or added to their cart, but rather other items that bare similarities to those products. This enhanced discoverability via email and SMS is more likely to get customers back on a store’s website.
Recommendations on a product detail page, or PDP, can be a particularly valuable yet often overlooked place to deploy personalization. A user clicking on an item to learn more about it, examine its specs, and read reviews is an extremely strong signal of interest in a specific type of item.
With the right recommendation engine, you can make relevant recommendations to the user viewing the PDP based on the items’ similarity to the item on the PDP. This ease of discoverability for the user can have several positive outcomes for the store as well, including reduced bounce rates and an increase in average order value (AOV).
In some e-commerce scenarios, location can be used as a helpful factor in personalization. Retailers often use location targeting to locate nearby physical stores or auto-calculate shipping costs.
But for some types of commerce, location can also be used to filter products. In the example below, Eventbrite uses location targeting to auto-filter nearby events for each user. Since location is a determining factor for event attendance, this is a particularly useful feature for ticketing and events.
Upselling at the checkout or cart view stage is another example of e-commerce personalization. The idea is to take an item that has already been added to a customer’s cart and make them relevant recommendations of other similar products that may be of a higher quality or simply higher price point. The obvious benefit here is a greater AOV.
One best practice for upsell is to create a dedicated upsell page. Clicking "Add to Cart" then directs the user to an upsell page, where they will see the current product confirmed in the cart, along with products that would offer the merchant a greater gross profit.
Bundle or cross-sell recommendations are a counterpart to upsell recommendations. Instead of recommending replacement items of higher quality or cost to the customer, bundle recommendations are meant to encourage a user to buy more items overall so that the AOV increases.
Bundle recommendations might include recommending items that intuitively complement whatever is already in the user’s cart. For example, if someone is buying soccer cleats, the store might recommend shin guards and a soccer ball to go along with it. In other instances, a bundle might include multiples of the same item at a discounted price, which will save the customer money on the purchase but make the order value higher for the e-commerce business. Depending on the recommendation engine or platform used, the store may have to manually set these bundles as recommendations, or rely on the engine’s ability to match items by their similarity.
Many e-commerce companies encourage their customers to purchase new items by offering personalized coupons and discounts. Customers are more likely to re-engage and make a purchase if they feel that they are receiving a special deal.
There are several ways to operationalize personalized discounts. Here are two common examples:
Another consideration for personalized coupons and discounts is who is being targeted. Of course, this tactic is often used to re-engage dormant customers or those who have abandoned carts. However, a business can incentivize loyal customers with special offers, as well. This will keep them happy and feeling appreciated, and has an added benefit for the store in that the most loyal customers bring a much higher AOV than a typical customer.
Although it’s less common, it’s also possible to personalize a site by showing the consumer’s employer. This is done through IP matching. The idea behind it is to show something familiar & personalized to the consumer in an effort to grab their attention and reflect their uniqueness back to them.
B2B e-commerce companies may be tempted to implement this type of personalization. However, all types of e-commerce should be very cautious before implementing this method. This form of personalization requires collecting personally identifiable information (PII) and directly communicates to the consumer that they’re in a database that you own. This can often be perceived as “creepy” or an infringement on privacy. That’s why, for most instances, this method is not recommendable.
Additionally, this type of technology is slowly being phased out, and new tech that leverages first-party data is widely perceived as preferable.
Reformation made waves in the retail community when it unveiled a special feature in its fitting rooms: personalized recommendations for garments that can be requested directly from the fitting room.
Each fitting room was equipped with a tablet, where the customer could request new garments to try on. Of course, the system made smart predictions about the customer’s taste, giving Reformation a leg up by surfacing the most relevant products for each customer.
This is a case-in-point example of how omnichannel personalization can benefit the in-person shopping experience.
There are several e-commerce personalization examples that include next-gen tech not typically found in e-commerce. Brands like Warby Parker have revolutionized the experience of shopping for apparel and accessories online by introducing a virtual try-on app to simulate what it would be like to try glasses on in-store, all from the comfort of your home. Similarly, home decor outlets like Crate & Barrel have taken to implementing augmented reality (AR) solutions in-app to allow consumers to check out how a piece of furniture might look in their own room.
