How to increase customer satisfaction with a unique recommender?

The choice assistant will find all available information about the product you need, compare the price-performance ratio and give you a list of advantages and disadvantages. On the final step of comparison, the personal choice assistant will present the "advantageous alternatives" and offer the solution. Betterfy allows clients to see what the product looks like, get acquainted with its functionalities, and ask the store experts about the product to make the best choice.

One of the most crucial tasks for eCommerce customers is to recognise what products are worth buying and why. This is true especially now, during the post-Christmas sales.

We developed a native eCommerce choice assistant inspired by the offline shopping experience. The choice assistant compares the product alternatives, evaluates them (price-performance ratio), and tells you their advantages and disadvantages.

The AI model behind the choice assistant produces

• the price-performance ratio for all products
• advantages and disadvantages of individual products

On the graph below, you can take a look at the data from the model trained on the mobile phones category from one of our customers to better understand our solution.

The performance calculated by the ML model is plotted on the y-axis while the prices are on the x-axis. We are focused on one selected product in the plot (Samsung Galaxy S10 lite). Based on the shown metrics, we are able to assess which products have a better price-performance ratio than the viewed one (Samsung Galaxy S10 lite). To make it more useful for the customers, we also look at the similarity of the products. Those are plotted by colour and popularity of the individual alternatives, mapped by the size of each point. Going over the individual points, you can see the top 3 advantages and top 3 disadvantages for each alternative (compared to the viewed product).

The final outcome used by one of our clients can be seen in the screenshot below — the so-called “Advantageous alternatives” to the currently viewed product with a comparison of advantages.

Motivation

How to bring offline shopping experience into the digital world using AI?

Imagine how your purchase works in a good, specialised physical store. Imagine how you want to buy, for example, a stroller, TV or a car. What is it that you appreciate the most about offline shopping? We would guess that it is:

• You can see what the product looks like
• You can touch the product and maybe even try its functionalities
• You can ask the store experts about the comparison to other similar products, the benefits and disadvantages and their opinion about the best fit for your needs

We believe this shopping experience is crucial for satisfying the customers and building a long-term relationship between stores and customers. When customers purchase without understanding the product or its alternatives, this creates even more problems later, at home, when they start using it. Some customers are disappointed, and some even decide to return the product. This adds costs to your business, and employees waste a considerable amount of time and money. Moreover, unsatisfied customers may leave negative reviews and feedback and harm your credibility and search ranking.

Our solution

We are on the way to bringing this offline experience into the digital world in a native way. And we started with the third point above - you can ask the store experts about the comparison to other similar products. This offline service is essential for situations when you are looking for a product that you don’t buy regularly – when you’re not sure about the right choice (e.g. electronics, specialised sports equipment, car). You don’t want to be pushed or persuaded; you appreciate the help from an expert in the given area. After you describe your general requirements, the expert presents your options, points out pros and cons, recommends the best choice for you, and explains why and how they made these decisions. This is the experience many shoppers miss in eCommerce.

We have managed to transfer this shopping assistant experience to the digital world in a digital-native way. We developed a machine learning solution that provides customers with similar but better products and compares them in a credible and transparent way. The engine automatically evaluates the advantages and disadvantages of individual products and their price-performance ratio. This is done by the ML model calculating the performance of each product. The model is trained on the set of all products (even past ones that are no longer offered), their parameters and prices. Therefore, the engine is suitable for products that can be described well by parameters, and it also works for products without history (new products, one-instance products). That means the algorithm does not suffer from a cold start problem.

If you are interested in more details, check the plot above or here.

We call the engine Betterfy as it can reveal better choices. The practical usage of this engine is shown further.

How is the engine used in eCommerce?

Better choice recommendation. Betterfy advises more relevant products with a credible and easy to understand explanation. Highlighting the advantages of recommended products will help the customer make the buying decision. As a result, customers get a shortlist of products with similar (or better) parameters to the one they are looking at. And they get an explanation of why the recommendations are better. Just like with an expert in a physical store, the customer will understand the exact reasons why the recommended products are better than the previewed ones.

Better choice recommendation visible on a product detail page

Above-standard product features. Betterfy automatically generates the features of the products, which are specific for them among other products in the same category. The customers can understand quickly how individual products differ and what is special about them. For example, this car is special due to its low consumption within its price level. This information can be placed either directly on the product detail page or in the products listing, enabling users to make the best choice efficiently.

Above-standard product features are listed in the category overview

Explanation, why customers should buy selected products. Many products are outstanding (have a good price-performance ratio), and there are no (or not many) better alternatives to be recommended by Betterfy. In this case, Betterfy can work vice versa, i.e. saying why the viewed product is the best in a given category and price level. The explanation for why the products are good can be done by comparing similar products and presenting better features of the selected product. Or simply by saying that the product is a good choice and why it is like that (as shown below).

Explanation of why customers should buy selected good products

Price-performance index. Betterfy produces a price-performance index for each product, along with an explanation of why it is high or low. Customers can clearly see what products should get their attention. The ratio can be demonstrated by a clock icon, as shown below.

Price-performance index — green/yellow/red clocks

We developed this solution together with one of the key eCommerce players in Europe, the Mall Group, reaching great results in revenue. We believe these results are driven by customer satisfaction.

„The solution that DataSentics developed with us enables our customers to choose alternative products transparently based on their advantages and disadvantages. The solution is unique in the world of recommenders thanks to using machine learning to generate transparent and explainable recommendations to our customers. This led to an increase in revenue of up to 20% in certain categories while increasing customer satisfaction at the same time. DataSentics was a partner to us along the whole journey from the initial idea to a scalable solution in production and worked with us as one team.“

Visit product website