8 Reasons to Introduce Purchase Recommendations in Your Online Store
The beginning of the year 2021 is the best time for the eCommerce industry to implement new solutions that aim to modernize and improve online stores and, as a result, boost sales and
a conversion rate. One of the most important trends in 2021 is undoubtedly personalization based on artificial intelligence (AI) and machine learning.
More and more external tools offer solutions supported by this technology. One of the most accessible options on the market is the product recommendation engine. It is easy to install and use, as well as to measure efficiency. There are many reasons to choose this innovative tool.
Today on the blog we have listed 8 of the most important ones.
Why introduce a recommendation system in an online store?
The recommendation engine is not another additional tool that - because of its persistence -interferes with the appearance of the store and irritates users navigating through the store's website. On the contrary, thanks to personalized recommendations, the customer has a chance to feel special. These very accurately and effectively selected product recommendation models are able to get to know the user's preferences right away, thanks to an advanced algorithm based on machine learning and artificial intelligence (AI). Because of recommendations the store user does not have the sense of wasting time. You can avoid a situation where the customer browses through all subpages of the catalogue one by one to find the desired product. Thanks to recommendations, they can be inspired by the purchased item tailored to their preferences or users who are similar to them.
Are you wondering how the recommendation engine works? We have answered this question in detail on our blog. To find out how recommendations are generated, see here.
Here are the top 8 reasons why you should decide to implement a product recommendation system in your online store.
1. Increase sale by 5-10%
If we are talking about eCommerce activities that are actually effective, it's worth looking at specific numbers. According to the 2018 Brilliance report concerning personalized product recommendations, recommendations accounted for up to 31% of the share in sale growth. In turn, 12% of all purchases made by customers result from recommendations displayed to them.
2. High and effective personalization of purchases
Customers are more willing to buy recommended products that immediately meet their preferences. To gain the customers’ trust and provide them with the most tailored shopping experience, it is worth improving the personalization of the entire offer. Personalization is ensured by solutions based on machine learning technology, such as, for example intelligent searches or product recommendation engine. Not only do they facilitate navigation through the store catalogue, but also give customers the feeling that the store's offer is tailored to their preferences.
A properly designed algorithm will be able to learn the preferences of the store users based on session history, previously viewed products, products that have been added to the basket, etc. Thanks to this data, it is able to select and generate personalized offers. The product recommendation system is an intelligent solution, which is one of the simplest and, at the same time, the most effective options for improving the personalization of purchases. To find out how (non-personal!) data is collected, see this article.
3. A simple and fast way to improve your online store
Many online store administrators are looking for ways to quickly upgrade their store to gain customer trust and increase sales. What comes in handy are external tools, which are usually easily available solutions offered in the Market Place of a given eCommerce platform.
It is worth remembering, however, that tools to improve the condition of an online store are available elsewhere, and their installation does not have to be difficult or require technical knowledge. Recostream is an example of such a solution, as it stands out on the market by the speed and ease of integration without the help of an IT specialist. The only thing you need to do to integrate our recommendations with the store is paste a short line of code in the page section and it's ready. You can read more about the 3-minute integration here.
4. How to reduce the number of abandoned shopping baskets
The recommendation system is a very flexible tool. The window with purchase suggestions can appear practically anywhere on the website of an online store. Recommendation location is crucial when it comes to click-through and profitability. We wrote more about where to place recommendation windows earlier on the blog. Proper placement of recommendations in the store reduces the rate of abandoned baskets.
The key places are a window with recommendations on the product page below the product, a pop-up with sets of Cross-Selling recommendations that appear immediately after adding the product to the cart, and a set of manually defined recommendations that appear on the basket page. Thanks to this arrangement, sales growth can increase by a half. This also brings the desired effect of reducing the bounce rate.
5. An unobtrusive tool that can be easily adapted to the appearance of the website
Consistency of the appearance of your online store website is essential. When considering a new tool that aims to extend the functionality of the store, it is worth considering whether the external solution can be easily adapted to the design of the store. Transparency, consistency and a well-designed UX (user experience) in an online store contributes to building customer trust and increases the chances that they will return to your store and - above all - will not leave it due to intrusive and pushy special offers, advertisements and pop-up windows showing up everywhere.
At Recostream, we focus on consistency, simplicity and thoughtful selection of the location of recommendations in such a way that they are not intrusive. Additionally, we make certain that each element is fully adapted to the appearance of the store. If you plan to change the look of your website within a few months, don't worry! Modifying the appearance of the recommendation window is so simple that it can be done at any time.
6. No cold start
What does it mean? The recommendation engine may generate several recommendation models. Not all of them are able to show recommendations immediately after the installation. Recommendations are generated only after the time needed for a sufficient number of users to browse the site. Then the algorithm collects and analyzes data and only with a given amount of data on the browsing history is it able to create recommendations. This is the case, for example, with the "Recently Viewed" model. The proposal of items that were viewed by the user in the previous session takes X minutes (depending on the platform) to end the session in order to be generated.
It is different in the case of the content-based model. For example, in the "Similar" model the user is displayed products that have common features with those currently viewed. The algorithm compares product descriptions of all items from the catalogue and shows on the product page those that have the most common elements. Content-based models avoid the cold-start problem and are able to be displayed to customers as soon as the tool is installed on the store page.
A detailed product description is useful not only when we want to optimize the store's website in terms of SEO, but also when we want to personalize the purchases of our customers.
7. Great performance
We are aware that not every external tool meets the expectations of administrators and owners of online stores. For this reason, many solutions on the market offer a trial period of 7 to 30 days. At Recostream, we took it a step further. We have full confidence in the results of installing our recommendations. If, after one year, the share of our recommendations in sales will not be 10 times greater than the cost of our service, we will refund all fees for this period.
8. Real-time efficiency and traffic analysis
Recommendation engines, thanks to an algorithm based on machine learning and artificial intelligence technology, are able to collect information on each event in real-time - clicks on recommendations, entering the product page, entering the shopping basket page, etc. Basic statistics are available in the Recostream dashboard, thanks to which you can analyze the conversion and effectiveness of the tool on an ongoing basis.
An interesting option is also the ability to connect the product recommendation system to Google Analytics in order to measure statistics. Thanks to this, the store administrator has access to all the most important metrics in one place. How to do it? In this post, we provide tips on how to track recommendation conversions in Google Analytics and how to integrate both systems.
Is my store ready to implement a recommendation system?
Today we have learned 8 reasons why you should decide to try out a product recommendation system in an online store. There are still some questions to be answered. What conditions must be met for the product recommendation engine to work in the online store? Are Recostream's recommendations compatible with any eCommerce platform?
What conditions does the store need to meet to introduce recommendations?
In order for the recommendation engine to generate the best optimized and best-selected personalized recommendations, the traffic on the website should amount to 1000 page views per day. Otherwise, the algorithm will have insufficient data to provide the user with a set of recommendations that will suit their preferences. The second important factor is the number of products in the store catalogue. Based on our implementations so far, we suggest that the minimum number of products in the store should be 100. You can read more about when is the best time to implement recommendations here.
How to integrate the store with the purchase recommendation engine?
Each recommendation engine has a different way of integration. This process often requires additional involvement of an IT specialist. This is no longer necessary with Recostream. Our recommendation engine can be integrated with any eCommerce platform, both SaaS and Open Source. Here you will learn exactly what the process of integrating Recostream with your store looks like step by step.
The product recommendation system is a tool that improves many elements of the online store. With one solution, the store owner or administrator will be able to modernize not only the UX and purchase personalization, but also increase conversion, traffic on the store's website and build the trust of the customers.