CASE STUDY

How an E-commerce Giant Increased Conversions by Calibrating Machine Learning and AI Recommendation Engine? 

Aug 29, 2022

Highlights of the Case Study: 

Particulars Description 
Client An e-commerce giant approached Quantzig to achieve even higher e-comm conversion rates.  
Business Challenge The client wanted to leverage customer data to improve its recommendation engine and thus boost sales.   
Impact Quantzig used machine learning and AI-based models to build a recommendation engine for the client based on customer purchase and search history. 

Game-Changing Solutions for the E-Commerce Industry 

The success of any eCommerce business depends on its conversion rates, which in turn depends on how effectively its recommendation system displays customized suggestions to its customers visiting the webpage. Consumers’ inboxes and web searches are flooded with product recommendations under the hashtags “Suggestions exclusively for you.” E-commerce giants are reading consumer social media chats, web searches, and even their minds to understand what they are willing to buy and putting it right in front of them. The influence is so strong that consumers buy things they did not plan to buy.   

Quantzig’s recommendation engine collects and analyzes the data for each website user separately. Quantzig’s advanced artificial intelligence (AI) driven solutions enable businesses to gain instant insights into customer paths and behavior. Companies can leverage our machine learning algorithms to create a recommendation system to analyze customers’ digital footprint, personalize their browsing experience, and increase conversions with the help of AI and big data analytics.  

The Challenges of the Retail Client 

Our client is an e-commerce giant with a thriving business and a broad customer base. However, the client was not happy with its business leveling off, hence approached Quantzig to achieve higher e-commerce conversion rates. The client had billions of data points to analyze based on customers’ purchase history, products in the cart, and wish-lists. The client wanted to leverage this vast database to maximize conversions. Thus, the client approached Quantzig to utilize its AI technology and ML algorithms to improve its recommendation engine.   

Our AI recommendation engine was the exact tool the client needed to solve their problems and more.

Quantzig’s Advanced AI and ML Solutions for the Ecommerce Industry  

Quantzig used AI technology to build a recommendation engine for the client based on multiple parameters such as customer purchase history, products in the cart, products liked or rated by the customer, customer wishlists, and time spent on each item and product category.  

Furthermore, we developed a “product to person” collaborative filtering leveraging Quantzig’s machine learning algorithms to uniquely customize the returning customer’s search experience. For instance, the beauty-obsessed youth found our client’s web pages heavy with beauty product suggestions, while a gaming enthusiast could see those pages rich with gaming device suggestions.  

Finally, we developed a push notification model wherein the customers get an email notification and SMS update reminding them of the products they have in their cart from time to time.   

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Impact Analysis of Quantzig’s Recommendation Engine 

Using our AI and ML algorithm-backed recommendation engine, the client could feasibly scale up its conversion rates and achieve the following benefits:  

  • The client reported a thirty-one percent rise in sales to fourteen billion dollars during the third fiscal quarter, up from 10 billion dollars during the same period the previous year.  
  • Forty-five percent of the client’s overall revenue this financial year was from our recommendation engine model and push notification system.  
  • Client’s customers got a full page of customized suggestions for products dedicated only to themselves, resulting in a delightful browsing and shopping experience.  
  • The push notification alerts created by Quantzig’s data analytics team scaled up the conversion rates fourfold by reminding the customers about the products they had put in the cart some time back.  

As a result of this partnership, the client integrated our recommendation engine model into every segment of its purchase process.  

ai recommendation engine

Key Outcomes 

In the modern digitized world, eCommerce retailers have the advantage of having a digital footprint for each customer, which can be leveraged for future purchases. Quantzig’s machine learning and advanced AI-enabled recommendation engine helped the eCommerce client leverage the vast amount of data at its disposal to drive higher conversions. Our interventions helped the client increase its profit margins significantly. The client implemented ourb across its different product segments. 

A Broad Perspective on the role of ML-Based Solutions in the Ecommerce Sector: 

Machine learning is an evolving technology that builds intelligence from algorithms designed to enhance user interaction and browsing experience. Converting browsing into online shopping is crucial for the survival of any e-commerce business. Product recommendations powered by machine learning algorithms can lead to intelligent search results. This not only helps businesses in attaining higher conversion rates but also helps in predicting behavioral patterns and trends by discovering causal effects in data.   

Key Takeaways 

  • 31% rise in sales, increasing from 10 billion to 14 billion dollars 
  • 45% of the client’s overall revenue was from our recommendation engine  
  • Enhanced customer’s shopping experience with targeted recommendations 
  • 4X higher conversion rates due to the implementation of push notification alerts  

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Machine Learning Solutions Optimized Manufacturing Line for a Major US-Listed Copper Manufacturer 

Enhancing Inventory Planning Using Machine Learning | A Quantzig Success Story 

How Did AI Data Solutions Help Leading Fast Food Retailers to Improve Sales by Optimizing their Menu Offerings?  

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