For retailers, product recommendations may seem like a self-serving tactic – they want to offer relevant items to customers to garner more sales. However, as it turns out, customers also find product recommendations useful. One study conducted by marketing platform provider Listrak found that as many as 80 percent of customers find product suggestions they receive via email and other communication channels valuable. In that regard, if merchants are sending relevant recommendations to their customers, it’s really a win-win situation for both parties, with retailers selling more goods and customers discovering new and interesting items.

However, personalization is key to these efforts. Customers do not want to receive irrelevant product recommendations – in fact, that may lower shoppers’ perceptions of their favorite retail brands. If people spend a lot of money at a particular store, they want that merchant to be able to show the company cares about their business and understand their needs. This is why personalization is so important – fine-tuning suggestions based on customers’ specific interests will not only generate better recommendations, it will also show customers they are more than just numbers in the system.

How to execute personalized recommendations

Personalization is critical when it comes to product suggestions, but what are the critical factors merchants should be looking at to customize their recommendations to shoppers? There are actually a variety of different elements retailers can use, giving them even more ways to personalize offers for their customers. Here are a few key factors to capitalize on:

• Purchase history: This is the obvious one – retailers can use purchase history to identify items that customers may potentially be interested in. By combining order history with trend data about what other customers also bought after purchasing the same items, retailers can identify meaningful add-on and supplementary purchases. For example, if a shopper buys a winter coat, he or she may also be interested in a scarf or gloves.
• Referral source: However, order history may not always be available or relevant. For example, say the previously mentioned customer’s last purchase was the winter coat. Scarves and gloves are relevant follow​-ups, but not if six months have passed since that purchase and it’s the middle of summer. The referral source can be a great personalization tip off, as it gives context for the shopper’s visit. For example, say the prospect clicked an ad for the retailer that was displayed on a computer hardware blog – that person may be interested in buying computer technology or software. Other relevant referral sources may include Pinterest and social media traffic, or search engine queries. Retailers can glean even more information about their customers by using Google Analytics to understand where their customers are coming from. This may provide even more insight into shoppers’ interests, which may further fuel personalization initiatives.
• Location-based suggestions: The advent of mobile devices has given retailers yet another tool to fine-tune product recommendations in the form of location. In the past, customers tended to browse retail sites from specific locations – mainly their homes or their workplaces. However, with mobile devices, they can browse retail stores from anywhere at any time, giving merchants more information with which to fine-tune their recommendations. For example, say a retailer determines a prospect is accessing its site from a concert hall. The merchant could then opt to recommend goods based on that information, perhaps by suggesting CDs or other merchandise by the artist playing at that specific time. More broadly, retailers could use location information to eliminate irrelevant recommendations as well. For instance, a customer located in New York City might not have much use for a lawn mower, even if it is in the middle of summer.

Knowing the audience

While there are several different factors that retailers can use to fuel their product recommendations, Practical eCommerce makes another valid point – it is crucial merchants can also differentiate between first-time and repeat buyers. This will put merchants’ omnichannel retail initiatives to the test.

“Browser cookies tell the server if someone has shopped the store before,” Practical eCommerce contributor Pamela Hazelton added. “If your shopping cart supports it, the cookies may also log whether or not the returning shopper has previously placed an order. You can harness this data to present customized messages, login prompts (for returning customers), and even make special offers to help seal the deal.”

Personalization can be a huge tool for retailers that helps merchants rack in more sales. However, it needs to be executed effectively and in a relevant fashion. Customers are deft – they can see through shallow attempts at trying to make them buy more goods and are able to differentiate between meaningful suggestions and cash-grab attempts.