There are countless ways businesses can use personalization to succeed. However, one of the most effective and engaging ways to use personalization throughout your customer experience is through 1:1 product recommendations, just looking at the data. According to a salesforce survey, 56% of customers are more likely to return to an e-commerce site that provides product recommendations and 74% of customers are frustrated when website content is not personalized. To fully understand the importance of personalized product recommendations, let’s first take a look at the principles they borrow from actual interactions between sales reps and customers.
What is product recommendation in e-commerce?
The brick-and-mortar stores have a clear advantage when it comes to establishing a relationship between the customer and the brand. Salespeople can learn about customer preferences, intentions, and needs through live chat. They can make a real connection with the consumer and then make recommendations from that interaction. Product recommendation engines allow your business to have these types of interactions with customers throughout their online shopping journey.
Using digital touchpoints your audience has with your brands like your eCommerce store, your website homepage, or email campaigns you can provide relevant recommendations for products and inspire customers to make additional purchases.
What is an eCommerce product recommendation engine?
The product recommendation engine filters and sorts your online store’s product offers based on a set of rules. This process uses data about your products, such as views, sales, or even reviews, to recommend the most popular products.
Presentation of these results can be as simple as the order in which products appear on category pages. But you can also use them to influence buyers at every stage of the customer journey.
User-specific data, such as your customers’ most viewed categories, products, and purchase history, allows recommendation engines to find the most relevant recommendations for your customers. The recommendations obtained have the potential to drive countless aspects of your customer experience, including:
- Your home page, product page, or cart page
- Category page
- Personalized social or display advertising
- Email marketing campaign
- Special offer in search results
Benefits of product recommendation
Offering relevant products is a win-win scenario for both the customer and the e-commerce retailer. These are the key benefits you will see when your business uses an eCommerce product recommendation engine:
Better user experience. Your business should make helping customers find the products they’re looking for and product recommendations that personalize the buying experience to make it easier for you to navigate products.
Interact with customers more. Customer relationships are built on trust. Your audience wants to feel like your business understands them and recommends the right products that will help foster brand loyalty, inspire more website visits, and encourage more interactions. more with your brand.
Increase revenue. The more valuable opportunities you provide your customers to browse and purchase products, the higher your sales will be. Product recommendations can help strengthen your customer’s lifetime value.
How to use eCommerce product recommendations to get new customers
Recommend top sellers
Customers crave a shopping experience that allows them to come across relevant products without having to search to find them. Personalized, AI-powered recommendations achieve this by continuously identifying best-selling items and curating them for new shoppers to know your brand. With the right AI and automation, you can give your customers the best your brand has to offer and bring them closer to conversion.
The theory driving this commercial strategy is the Pareto 80/20 rule of marketing. This rule states that 20% of your products are most likely to drive 80% of your sales, and so these top 20% of your products are most likely to talk (and promote). brand preference for) with new customers.
A/B test different recommendation models, each using a different combination and weight of input parameters, such as views, purchases, time spent on a page, visits clicks, add-to-cart events, etc. will help you determine which model will drive sales most effectively.
Recommendations based on ratings
Nothing your marketing team can write will be as convincing as 5-star reviews from your customers. When customers share previous buying experiences, they can play a huge role in the buying journey. That’s why user-generated recommendations are some of the best ways to convince new customers of your positive brand reputation, solid customer experience, and product quality. Using the highest customer reviews as the basis for product recommendations will bring the product to life in your customer’s minds and also answer key questions or concerns they have. possible about the product.
Cross-selling is the practice of selling complementary items that complement a customer’s purchase goal. This is important because it’s simple. It mimics the common offline experience one would get from a salesperson through recommendation engines. Cross-selling banners capitalize on this sales opportunity by presenting relevant items in the customer’s shopping journey based on cart page content, brand preferences, or last-seen items. their. The most successful cross-sell recommendation models use collaborative filtering.
Simply put, product recommendations not only improve the overall customer experience but are also the catalyst you need to increase revenue for your business. But today’s businesses must weigh carefully between thoughtful personalization and intimidating customization. To do this, search, web, and marketing teams must work with ethical technology providers to understand which suggested strategy will build consumer trust rather than scared.