Today, almost every online store makes use of some type of recommendation engine, which does not come as a surprise, since these systems, when configured correctly can significantly improve click-through rates (CTRs), boost revenues, and increase conversion rates.
How recommendation engines benefit websites
Increasing revenue is the ultimate goal of any marketing strategy and this is why it is also the key objective of any recommendation engine. It is obvious that a visitor will feel more comfortable and more eager to purchase something from a website where they are getting the maximum possible assistance in finding what they are looking for.
In fact, statistics by Invesp show that 53% of online shoppers believe that retailers who offer a personalized shopping experience provide a valuable service.
While there are numerous other things that contribute to building this type of customer experience, implementing an advanced recommendation engine is the foundation for providing such a personalized journey to the visitor.
To further illustrate our point, let us share a few statistics with you. According to VentureBeat, 77% of the digital natives actually expect a personalized online shopping experience which basically means that making use of personalization technologies is a precondition for running a successful business online.
Two of the most popular success stories of recommendation engines come from Amazon and Netflix. Statistics by Mckinsey state that 35% of the what consumers purchase on Amazon and 75% of what users watch on Netflix come from product recommendation engines! Consult an eCommerce developer, if you are planning on implementing a recommendation engine to take your business to the next level.
This just goes to show how prolific these product recommendation engines can be when you have them set up properly.
Making use of product recommendations to improve conversion
Now that you have an understanding of how important product recommendations are for a business, let us take a look at how you can increase conversion by making use of this personalization tool:
- PROMOTE POPULAR PRODUCTS
A powerful but pretty straightforward recommendation logic is to promote the popular products on your website. This simple technique has a proven success record in almost all eCommerce websites. It is easy to determine how reputed a product is – simply weighing the number of times has been bought with how long it has been available will let you define the popularity of a product on your website.
However, more complicated recommendation systems include other event data such as add to carts, clicks, and views into their logics as well. This leads to more accurate recommendations and ensures a better conversion rate.
In the case of content websites such as news sites, factors like time spent on the page or percentage of page scrolled are also important considerations for calculating popularity.
Getting this particular bit right is essentially important because of Pareto’s rule of marketing states that 80% of the product sales actually come from 20% of the products! Hence, it is important that you are aware of the right metrics for determining the popularity of items on your website.
- USING SOCIAL PROOF
High user ratings and customer reviews are another important indicators of how popular products on your website are.Social proof is effective in today’s post-modern internet generation because it allows customers to read what others say about a product.
According to SmartInsights, content sharing can influence customers more than brand or price and can motivate people to spend up to 9.5% more than they would usually.
Not just this but social proof increases the visitor’s trust in your products, as well. This is illustrated with a statistic by BrightLocal which concludes that 88% of online users trust reviews and ratings as much as they trust personal recommendations!
If you believe that social proof can be a dominating factor in impacting the purchasing decision of customers, then you should consider adding a widget for “Top Rated” products on the main page or a “People Who Viewed This Also Viewed” widget on the product page to engage more customers. The focus should be to highlight the ratings of your products so that customers know exactly how reputed a specific product is.
eBay makes use of meaningful statistics with every product to deliver social proof to their customers – this not only improves the user experience but also ensures that visitors convert more easily when they encounter a top-rated product.
- BEST SELLERS:
This is a recommendation logic that combines social proof with sales data to promote top sellers to customers that are looking for the latest products.
Integrate the actual sales data of your website into these product recommendations to add an element of ‘social proof’. With this data, you will be suggesting that ‘other people are buying it and you should too’. However, it is important that you sort your best sellers into specific product categories, as well. This is essential because you want the right audience to be viewing the right recommendations.
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With this recommendation logic, you urge the audience to purchase from new categories that they have not purchased from before, which will open up a visitor to a vast range of up-sell and cross-sell opportunities.
An example of this recommendation logic in action can be taken from Amazon’s top seller’s recommendations that make use of categorized, customized best sellers being previewed to each customer according to their browsing and purchasing history.
- SIMILAR PRODUCTS:
There are several different logics that can be used for determining similar products – for instance, you could simply make use of filtering based on categories (something that can be applied without the need for a product recommendation engine).
However, such an approach falls behind in efficiency and performance because it is a feature that customers can make use of anyways. What you need to do is to combine such simple filtering methods with meta-data (product titles, descriptions, prices, tags) based similarity as well so that your recommendation engine promotes products of the same type (i.e. same brand, same color, or same price group).
Needless to say, this will require you to have a sophisticated recommendation engine setup on your website. Item-to-item collaborative filtering is considered to be one of the best-performing similarity based logics (a method that has been pioneered by the world’s leading eCommerce company, Amazon).
In this recommendation logic, you determine how similar two products are by looking at how frequently they are presented with each other in the purchase history or browsing history of users.
Widgets that make use of these logics are called “Similar Products” or “Visitors Who Saw This, Also Saw” which just about explains the basic idea of it. With sufficient data, these logics can be used to solve problems like automated accessory recommendation with reasonable accuracy.
Image Source – WooCommerce
- FREQUENTLY BOUGHT TOGETHER:
This is another effective recommendation that is often displayed in the shopping cart or checkout page of a website. It is a data-heavy technique and the primary goal of this recommendation logic is to increase your average order value.
What you need to do is to aim to cross-sell products by providing suggestions to visitors based on the items that are in their shopping cart. Alternatively, you could also display this recommendation below the product that a visitor is viewing, too, just like Amazon does it.
This is a compelling way of urging the visitors to your website to buy products that go hand in hand with each other i.e. two products instead of one, three instead of two, and so forth.
For applying this recommendation logic, the layout of the page is an essential factor. You need to make use of your time and resources for A/B testing different designs for this recommendation widget on the products page or the shopping cart page (or even both).
The A/B tests will help you yield excellent results and gather useful insights for this recommendation logic.
Again, Amazon’s ‘Frequently Bought Together’ is a prime example of how you can implement this recommendation strategy on your website.
- FEATURED ITEMS:
This is a recommendation logic which, unlike other strategies that we have described, is mainly dependent on the customer’s browsing history (rather than their purchase history).
By this recommendation strategy, you feature contextually relevant products based on the attributes (such as the brand, category, size, or shape) of the products that customers have previously viewed. With this recommendation logic, the aim is not to cross-sell or up-sell products but instead to improve the chances of conversion from each visitor.
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You are essentially throwing different colors, brands, shapes, and sizes of products that a customer has viewed in the hope that one of them will lead the visitor to convert (since they have already shown interest in the particular product).
Conclusion
The ideas, tactics, and techniques that have been featured in this article are not all that is there to say about product recommendations in eCommerce and marketing. However, it is meant to provide some food for thought to marketers who are planning to make use of a product recommender system for taking their conversion rates to the next level.
With the number of SaaS recommendation engines available in the market today, you can easily implement product recommendations on your website. In this article, we highlight some of the important logic and tactics for making use of these tools so that you can experience the results first hand.