9 Product Recommendation Recommendations From Sephora, Zappos and Tory Burch
The most valuable public company in the world, Amazon is practically synonymous with ecommerce. More product searches begin on Amazon than Google now and the company has so much clout, it’s able to create its own Christmas in July-style holiday in Prime Day. The secret to Amazon’s success? Product recommendations.
Amazon’s recommendation engine accounts for 35% of the company’s revenue, which shows that the right product recommendations are invaluable for retailers. That’s not an anomaly, either; in 2017, the National Retail Federation found that more than half of holiday shoppers purchased an item recommended by a retailer. However, during the holiday season, when many retailers make a significant portion of their sales for the year, a strong product recommendations strategy is easier said than done.
For one, people’s buying patterns change drastically. They’re buying more and in different categories than they usually do. With strong data collection practices, you can continue to make relevant product recommendations, while successfully differentiating whether those items are gifts for themselves or others.
Looking to recalibrate your recommendations strategy in time for the holidays? Of course you are. Here are nine winning tactics:
What are your best sellers? How about those from last year? These classic recommendations instill customer confidence. Highlight them, along with your products best known for converting first-time customers. And if your customer experience is great enough, those new shoppers may even by loyalists by February. Tory Burch does this well, with a single beautiful, eye-catching image and just a few words. Though it’s short and sweet, Tory Burch’s copy manages to creates a sense of exclusivity and timeliness.
What do Connect 4, The Very Hungry Caterpillar and the Echo Dot have in common? They were all included in last year’s ranks of most popular gifts on Amazon, a website tab that’s updated every day based on product popularity. Every holiday season has its trending items. They’re a great foundations for product recommendations, especially for those shoppers who don’t know exactly what they want to buy.
Centering product recommendations on new arrivals is a great extension of your segmentation strategy. These items can catch new customers’ eyes, while increasing engagement for existing customers. It’s likely your VIPs already know what’s hot; show them what’s new to keep them shopping during the holidays. Few brands do recommendations as well as Sephora, the first-place finisher on both of our Retail Personalization Indexes. New arrivals are front and center on the beauty giant’s website, right underneath the trending holiday items. Some of the new items even fit in with the above holiday theme; the gingerbread spice eye shadow palette contains shades such as Spiked Eggnog, Frostbite Me, and Reindeer Paws.
Also known as “those who bought this also bought that,” collaborative filtering is similar to making recommendations based on what’s trending. However, there’s a more personalized twist, as your activity ultimately dictates these recommendations. Collaborative filtering is a must for department stores, with their seemingly endless inventories. For example, Bloomingdale’s website sells more than 650 different pairs of men’s jeans, which can be filtered by best sellers, fit, wash and brand, among others. Once a customer clicks a pair he likes, the retailer lets him know what similar browsers bought, including both comparable and complementary items.
Interest-based recommendations are great for those customers you know… and even those you don’t. Marketers need surprisingly little data to pull this strategy off; all it takes is a short browsing session on mobile or a few website clicks. Shopbop customers can explicitly indicate interest by favoriting items. That gives the brand plenty of fodder for interest-based recommendations, while also create a sense of urgency by noting the limited inventory.
Have you ever written a letter to Santa Claus or met him at the mall? Wishlists have always been a staple of the holidays, except as adults, we make them online, communicating these desires directly to retailers instead. Wishlists provide data to the retailers about what people want. That data can also fuel future recommendations. MATCHESFASHION.COM has impressed us with their wishlist strategy in the past, creating a sense of exclusivity and an early demand for products.
Another staple of the holidays: gift guides. On the surface level, they’re typically full of beautiful images. They’re also chock full of potential product recommendations and we love the way Alex and Ani does it. Many brands create generic gift guides “for him” or “for her,” but the jewelry retailer took it a step further, segmenting its gift guides by different customer personas.
Product Recommendations in Abandonment Messaging
About 70% of online shopping carts are abandoned, which means every retailer has to have a solid strategy here. We recommend starting within a few hours, highlighting urgency and inventory limitations. The next message in your stream should be more proactive, like Express does here. The retailer stresses urgency while recommending similar products to those in the customer’s cart. Incentivizing free shipping rather than a discount is also a nice touch.
Triggered Message Cross-Selling
Emails containing order and shipping confirmations have sky high open rates. Capitalize on that by cross-selling. Include recommendations in these emails to facilitate further discovery and conversion, driving incremental holiday revenue in the meantime. This Zappos email could have just said, “Your order has shipped” and left it at that. However, the footwear retailer took advantage of a guaranteed-to-be-opened email, recommending both related and popular products.
This is just a taste. Download Sailthru’s 2019 Holiday Marketing Guide for more tips on recalibrating your recommendations strategy, the new table stakes, how to discount and segment strategically, and more!