What are Personalized Product Recommendations?

First, businesses collect data from various sources, such as online transactions or other relevant website parameters, including website activity, purchase history, social media interactions, email marketing campaigns, etc.

They then analyze this data to understand customer behavior, preferences, and interests. This information is used to create customer profiles, segment customers into different groups based on their characteristics, and eventually personalized product recommendations tailored to each individual’s interests and preferences.

For example, a customer who has previously purchased running shoes might receive targeted emails promoting new running gear, while a customer who has shown interest in yoga might receive emails promoting yoga equipment.

More concretely, if a customer purchases a table, after a few days they may receive a marketing email with product recommendations, such as tableware or tablecloths.

In essence, those products represent a personalized recommendation, since the tableware and tablecloths were purchased before by other customers in connection with that table.

When it comes to personalized product recommendations, marketers can use various criteria to select the products displayed, such as:

• Similar products - recommending products that are similar to ones the user has already viewed or purchased;
• Complementary products - recommending products that match the ones the customer has already viewed or purchased according to the historical data gathered from all the website’s customers;
• Recently viewed - reminding customers of products they recently viewed but did not purchase;
• You may also like - recommending products that other customers with similar behavior have purchased;
• Popular products - recommending the top-selling products on the website;
• Latest addition - recommending the newest products added to the website catalog.

80% of customers are more likely to make a purchase from a business that provides personalized content and recommendations. In fact, product personalization delivers a higher ROI and influences people to purchase more than what they had originally planned.

A personalized approach improves the customer retention rate and increases the chance for visitors to convert during the same website sessions, therefore reducing also the number of abandoned carts.

This marketing feature can also be integrated at any stage in the marketing funnel and it represents an effective way to stand out in a crowded digital landscape and build a strong relationship with customers. When used correctly, personalized product recommendations can reduce costs and improve consumer loyalty.

In conclusion, personalized product recommendations are an effective way to connect with customers on a personal level and drive conversions. By collecting and analyzing data, businesses can make relevant recommendations that engage and convert prospects into customers.