Imagine you could increase your e-commerce revenue, improve your users’ customer experience, and incentivise recurring purchases without having to drastically change your strategy. The key to achieving these goals could be a single move: product recommendations.
An effective product recommendation strategy is one of the most powerful solutions available to e-commerce. By offering personalised recommendations to customers, you can increase your online shop’s conversions and at the same time improve your customers’ loyalty and retention.
In the following paragraphs we will take a look at best practices for creating a winning recommendation strategy, with practical examples that will help you increase conversions and revenue, and most importantly, how to implement them with Blendee.
What are Product Recommendations?
Product recommendations are, as the word suggests, buying recommendations in which products are dynamically populated for each user who is browsing a web page, app or email, based on data about their buying behaviour or the occurrence of particular events, thus offering a personalised shopping experience.
The selection of products to be shown to the customer is usually handled by a product recommendation engine that takes care, based on input data, to choose the most appropriate products to display. Product recommendations should be considered as the basic activity for all companies that want to offer a personalised shopping experience to their customers.
We know that personalising the user shopping experience is fundamental in the e-commerce world: suffice it to say that, according to a study carried out by Accenture, 91% of consumers are more likely to buy products from brands that are recognised and remembered and that offer relevant product recommendations.
But what are the usually recommended product categories?
Among the main products are:
- best-selling products;
- similar products;
- trending products;
- products frequently purchased together;
- recently viewed products.
Why are Product Recommendations essential for E-Commerce?
The use of dynamic product recommendations becomes essential not only to make users aware of the products in the catalogue, but to show them at the most opportune moment. Moreover, being an indispensable element of any personalisation strategy, they are a real lever to improve the customer experience and increase the value of sales. Here’s how recommendations can make a difference:
Optimise Inventory
Smart recommendations can also help optimise inventory management by highlighting the products most in demand, helping you make more informed decisions about what to stock.
Improve the Customer Experience
Personalised recommendations make it easier for customers to discover new products by improving navigation. If a customer easily finds what they are looking for or feels supported in their purchase journey, they are much more likely to complete the purchase and/or return in the future.
Increase Engagement
Showing customers the right products at the right time increases their engagement. By analysing data such as past searches and purchase behaviour, you can suggest items that meet customer preferences, improving the likelihood of conversion.
Increase Conversion Rates
If you know exactly what to show each individual customer, you increase the likelihood that they will complete a purchase. Targeted recommendations lead to a direct increase in conversions by showing only those products that have the highest potential to interest each user.
They foster loyalty
Customers like to feel ‘understood’. Personalised recommendations create a sense of connection with the brand and encourage repeat purchases, thus promoting loyalty and positive word-of-mouth.
Best Product Recommendation Tactics
There are several recommendation strategies that you can implement to improve the effectiveness of your e-commerce. Each tactic has the potential to maximize revenue and improve the customer experience. Here are the most effective:
Bestsellers
Recommendations that show best-selling products are ideal for attracting the attention of new users and maximizing revenue. Showcasing the most popular items in your catalog boosts confidence and a desire to buy.
Similar Products
This type of recommendation suggests articles that share characteristics with the ones the user is viewing. For example, if a customer is looking at a ski jacket, they may be interested in seeing other ski jackets from different brands, but similar in quality or price.
Products Purchased Together
Recommendations based on frequent purchases offer a great opportunity for cross-selling. If a customer buys a laptop, suggesting a compatible case or mouse can significantly increase the value of the order.
Social Proof
User reviews and ratings play a crucial role in purchasing decisions. Including customer reviews and showcasing top-rated products can encourage new users to complete their purchase. People trust the opinions of others, and this can make all the difference in the final stage of the buying process.
Product recommendation with Blendee: some useful tips
Blendee provides its users with its product recommendation engine which, combined with the ability to segment audiences, allows you to customize product recommendations at any level.
Recommendations can then be inserted in various sections of your e-commerce: Home;
product detail page; category page; cart page; search page; landing page; user registration page; checkout page; other page.
You can, when creating the recommendation, select the type of algorithm you want to use to choose the products to show to the user.
Blendee allows the ability to configure product recommendations based on multiple algorithms.
Here are the main ones:
trending recommendation: the most popular products in the catalog are shown by click and view;
personalized recommendation: selected products are suggested to the user based on his/her recent browsing history within the site;
Personalized Trending Recommendation: in this case the algorithm shows products by mixing the previous two;
browsing history recommendation: products are shown starting from those that the user has seen;
personalized recommendation by sales: the algorithm allows you to show suggested products starting from those that the user has recently purchased;
Shopping cart recommendation: products are recommended starting from those that the user has placed in the cart;
Remarketing Recommendation: Products that the user has viewed in the last few days but has not purchased are shown.
Choice of algorithm but not only: during the configuration phase it is essential to also select the page of the site where you want to show them: Home; category page; product sheet; blog page;
account page; page 404; Cart page.
Blocks of the pages of the Website/eCommerce but not only: Blendee allows you to insert dynamic product recommendations also within behavioral messages (warnings, popups…) and within emails and newsletters (email widgets).
Conclusion: How to Implement Product Recommendations in Your E-Commerce.
Investing in product recommendations is a key step in staying competitive in the e-commerce landscape. Not only do these tactics improve the user experience, but they’re also crucial for optimizing conversions and maximizing order value.
To be successful, it’s essential to choose the right technology to handle recommendations. Use recommendation algorithms to continuously refine your bids, tracking results to optimize your strategies.
Start implementing these tactics in your e-commerce with Blendee today and prepare your business to thrive in an increasingly competitive market.
