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What is Discovery-Based Shopping?

In the world of eCommerce, discovery-based shopping is becoming an increasingly popular way for consumers to find and purchase products. Unlike traditional shopping, which relies on search-based queries, discovery-based shopping uses algorithms to suggest products based on the user's behavior and preferences.

Here's how discovery-based shopping works:

  • User behavior is tracked through cookies, browsing history, and other data sources.
  • Algorithms analyze this data to identify patterns and make recommendations based on the user's preferences and interests.
  • Users are presented with products that match their interests and preferences, even if they didn't specifically search for them.

The benefits of discovery-based shopping are clear. It allows consumers to find products they might not have otherwise discovered, and it enables retailers to make personalized recommendations that are tailored to each individual user's behavior and preferences.

Real-time analytics to accelerate discovery-based shopping

Here are some of the benefits of using Macrometa's real-time analytics and AI algorithms for discovery-based shopping:

  1. Personalization: AI algorithms can help eCommerce companies deliver personalized recommendations to each individual user, based on their behavior and preferences.
  2. Real-Time Analytics: With real-time analytics, retailers can analyze user behavior and make recommendations in real-time, increasing the chances of a successful sale.
  3. Scalability: Macrometa’s hyper distributed cloud is highly scalable, allowing retailers to easily expand their capabilities as needed.
  4. Data Protection: Macrometa includes data privacy features, ensuring that user data is protected.


In conclusion, discovery-based shopping is a powerful tool for eCommerce retailers looking to deliver personalized recommendations to their customers. By leveraging the power of data analytics and machine learning, eCommerce companies can improve the customer experience and increase sales, while also ensuring that user data is protected and secure.

Related reading:

​​What are Recommendation Engines?


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