How Recommender Systems Fire Up Ecommerce Conversion Rate

How Recommender Systems Fire Up Ecommerce Conversion Rate

Recommender systems were created to provide a superior experience and service to online shoppers. An e-commerce recommendation engine is an artificial intelligence technology that has transformed the online retail world for both shoppers and sellers. The value they have brought into the ecommerce sector is tremendous. The main idea behind this system is to create a recommendation platform that will create a more customer-friendly experience. At the same time, the recommendation generator will ensure a boost of sales and higher conversion rates. A good conversion rate is an indicator that your users are enjoying the shopping experience on your website. Keeping track of the conversion rate is vital for any businesses’ success.

Why is Conversion Rate Important for Ecommerce

A conversion rate refers to any desired action taken by the website visitor that you want them to take. It measures what happens once people get to your website. A low conversion rate indicates that you’re doing something wrong because people are not taking your desired actions. A high conversion rate, in contrast, shows that your efforts are resultful and you are generating revenue. In a nutshell, a conversion rate is an indicator of how you’re performing as a business. That’s why it’s extremely important to measure the conversion rate.

Unlike popular opinion, a conversion rate doesn’t relate to sales only. You set the conversion metrics for your ecommerce individually. Conversions can be any key performance indicators (KPIs) that are important for your website. Consider the following KPI examples:

  • Making a purchase in an ecommerce shop
  • Registering on the website
  • Providing any personal information, such as credit card details, and letting the website to store this information
  • Subscribing to newsletters
  • Getting a subscription, both free and paid
  • Downloading any trial goodie, which will incline the shopper to move forward in the sales funnel
  • Starting to use an app that was downloaded
  • Spending a specific amount of time on the website
  • Coming back to the website for a certain action, such as finishing a sale or looking for something new

Basically, anything that can be measured is a potential conversion KPI for your ecommerce. Tracking these KPIs will help your ecommerce to stay relevant and successful. In order to have a good conversion rate, the first thing to consider is to set-up a recommender system on your website.

Superior Customer Experience

A recommendation engine collects and analyzes data for every website user individually. Based on this data, a recommendation platform is generated for individual users. People who click on recommended products visit way more pages and stay on the site longer. But those who don’t, they usually end up visiting just one page of a single product. So with the help of product recommendations, people spend more time on your website. If people spend more time on your site, then most probably they enjoy their experience. Such an experience has higher chances of resulting in a sale or whatever desired action. Thereby, conversion rates are also increased.

Product recommendation engine and user experience

sistema-recomendacao-ecommerce

Attracting new customers is important, but keeping the existing ones is a completely different thing. Although companies spend a lot of money on retention marketing, customer retention is five times more effective than customer acquisition. If the visitor keeps returning to your website, it’s an indicator that he/she enjoys the service on your website. Only by ensuring a high-level customer service, your ecommerce will be able to keep the shoppers coming back. So, one of the most important targets of recommender systems in e-commerce is to ensure an excellent customer experience. A good customer service ensures high retention rates, better engagement, and increased satisfaction. All of this translates into the greater business result and higher conversion rates for your defined KPIs.

Personalization: the Key to Increased Conversions

One of the most important targets for having high conversion rates is providing your customers with exactly what they want. The recommender systems optimize the content available on the website, adapting it to the preferences of a specific user. Optimizing the website content will result in bigger sales and increase the conversion rates. When you show the shopper that you know what exactly they want, you will boost the customer engagement levels with you website.

Personalized product recommendations analyze the past purchases and recently view items of the shopper. They also look into what items the user has searched for. By collecting this data, recommender systems analyze all the information and start generating relevant suggestions. Your website needs to collect a lot of insights about the user, in order to be able to create individual recommendations like these.

If there’s not enough information to make highly personal recommendations, recommender systems will still be able to generate recommendations. They will compare the search data of one user to users with similar preferences, and make suggestions based on such similarities. Recommendations can be highly personalized, but it doesn’t mean that it’s the only best option in every situation. There’s a lot more to recommendations engines than personalization. However, real personalization can’t be achieved without properly working recommender systems. Any personalized product recommendation is always powered up by a recommender engine. To increase the conversion rate of your ecommerce shop, using personalized product recommendations is a must. A boost in the conversion rate is only one of many direct benefits of personalization.

Ecommerce recommendation engine

Increased Sales and Average Order Value with Personalization

Product recommendation engine drives sales for both upselling and cross-selling in ecommerce. It keeps making suggestions to engage the user with the content once more, and perhaps, to help find the product he/she looks for. For now, 35% of Amazon’s revenue is generated by recommendation engines. Also, 75% of what people watch on Netflix comes from their recommender system as well. Statistics don’t lie. The recommendation platform in ecommerce is indeed effectively driving sales up.

With the help of a recommender system, the ecommerce shopping experience has been transformed. The brick-and-mortar shops have a serious advantage over online sellers. They have helpful salespeople, who can help the shopper to find what they’re looking for. First, online retailers had to struggle to find a way to compensate this disadvantage. But now, with the help of online chatbots and personalized product recommendation system, the e-commerce has become the customers’ most favorite shopping channel.

Only an intelligent tool can rearrange the whole store, to find a single product that fits the tastes of a specific shopper. A salesman in a brick-and-mortar store is physically unable to do this. A visual recommendation can serve shoppers with personalized offers. This results in higher sales, lower cart abandonment, boosted conversion rates, and better KPIs in general, like bounce rates, times spent on the site and social shares.

Types of Recommendations that Should be Activated

Recommendations that pop-up during shopping are different because they are generated by different algorithms. Product recommendations don’t have to be personalized only to be engaging.

Recommendation on the Product Page

  1. “Customers who viewed/bought this…” – this technology works by identifying the similarities between the users’ shopping preferences. The logic behind this algorithm is to analyze how often two products have been together in purchase or browsing stories. An example of such recommendation is “people who viewed this item also liked this”.
  2. Similar Products – the recommender system takes one simple category and combines it with a meta-data, such as a price or product title. Combining these data, the recommendation engine is able to come up with relevant suggestions based on the brand or color.
  3. Personalized Recommendations – the system works by analyzing all the recent items the shopper looked at. By considering the most recent search results of the user, the recommendations are more accurate than ever.

Main Page Recommendations

  • Popular products – the most basic, yet effective recommendation strategy that works well in almost all ecommerce shops. A smart recommendation engine will also consider other data as the view count, add-to-cart events and clicks. Getting a right item to the product page is extremely important, as according to the Pareto’s rule in marketing, 80% of product sales come from 20% of products.
  • Products with a high rating – positive ratings and feedback are also an indicator of popularity. According to a survey by BrightLocal, 88% of users trust online reviews as much as personal recommendations. Rating greatly affects the purchasing decisions of shoppers.
  • Personalized suggestions – these recommendations vary from user to user. The algorithms show only individual recommendations, based on the specific user’s previous actions.

Personalized product recommendations

Cart Recommendations

 

  • Frequently bought together – the main reason why most websites have a cart page is to provide featured recommendations. This technology is also extremely effective.
  • Upgrades and accessories – the logic behind this technique is to offer the user accessories for the items in the cart. Also, by analyzing the previous purchases of the customer, the recommender system will also provide recommendations that are upgrades to the products the person already owns.

 

Conclusion

Recommender systems are the driving source behind improving sales in ecommerce shops. They generate great results for the business by improving the engagement, satisfaction, and retention of the customers. Activating a recommendation engine will help the shoppers to get tailored suggestions and improve the conversion rates of the shop.