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Modern eCommerce applications incorporate various techniques and provide useful features to enhance user experience. Some of these features are proven to be highly useful for strengthening the relationship between the app and customers.
One such feature that we mostly see in the eCommerce app today is a product recommendation, it helps boost user engagement with the app and also offers a higher influx to the cross-selling opportunities for the platform.
So, if you are a project manager or a developer who wants to deliver the product recommendation feature to the customer then this article is for you.
In the article, we will cover the following topics-
The eCommerce product recommendation feature guides users in the same way a common store owner helps shoppers to choose the related products they didn’t even know they needed. This functionality customizes recommendations depending on individual choices, intentions, and needs.
The feature also leads shoppers to choose one product over another based on different criteria such as cost, availability, brand, and supplier. For example, if you are looking for cold press cooking oil for a particular brand it will recommend you with the other similar complementary product of the same brand.
This is the technology that analyzes data about shoppers with Machine Learning and Artificial Intelligence algorithms by learning which types of products and offerings will interest users.
The product recommendation engine then generates data to create accurate individual profiles, which in turn helps the engine get the exact kind of content or product in which a specific customer might be interested.
Finally, the trained algorithm generates product suggestions and predictive offers like discounts and deals of the day tailored to each customer. The app also sends you frequent follow-up emails on recent purchases and even on app searches.
The recommendations are based on user search behavior, product preferences, contextual relevance, and nearest supplier availability.
Companies have realized that the personalization of the user experience is the key to the app's success. It makes customers feel special and valued. Additionally, it helps them to save time as they quickly get what they are really searching for.
So, if you are planning to add this feature to the app, here are a few popular Product Recommendation APIs that can be used in the eCommerce project.
Qubit is partnered with Google to bridge the gap between eCommerce websites and their users. It is the personalized engine for eCommerce product recommendations. It amplifies your eCommerce product selling rate with strategies built for the individual and not just segments.
To deliver integrated personalization Qubit provides several APIs and data sources. The Qubit API is a single interface to fetch, mutate and deliver data efficiently. Qubit uses artificial intelligence to provide valuable insights making eCommerce more effective, personal, and profitable.
Recolize is not only used for product recommendation but it is great for content creation. In fact, it allows its eCommerce users to access shopping patterns and create content according to their interests and which is more relevant. This in turn helps to optimize the traffic of eCommerce websites.
But how does Recolize do that?
It accesses user shopping patterns and creates blog content only relevant to these patterns, also the platform can be integrated with WordPress and Magento keeping everything in one place. Overall, Recolize Engine provides the following things for the eCommerce app:
It uses Machine Learning Algorithm to analyze and offer the customers the product they are most likely to purchase. It is a platform built for eCommerce Merchant apps with features to provide individual product recommendations to consumers.
Its search API lets its users interact with the Unbxd platform and enables them to implement all search-related functionalities with ease. It has the following key features:
These are just a few popular APIs but there are more such APIs for eCommerce product Recommendation. However, what API to choose completely depends on you and your app's requirements.
From the topics discussed above, now you have a good understanding of what is product recommendation, how it works, and what is the best product recommendation APIs that you can use in your eCommerce application.
So, it's time to bring your idea of integrating product recommendation features into your app. And if you want to make it as fast and easy as possible just use DhiWise- The intelligent app development platform for building web and mobile appsefficiently with the intuitive GUI.
Read this article, on how to build an Android eCommerce app with DhiWise .
The platform makes it super easy to build apps faster with its LowCode and ProCode capabilities. It provides the following key features for building apps efficiently:
And so on.
But in this article we are more concerned about its API integration capabilities, so let's see how DhiWise makes API integration a simple task.
The platform enables developers to integrate APIs into the UI components or screens using Create Actions or Manage Controller Lifecycle. Developers just require uploading the API postman file or need to manually add API.
They can add required API, select headers, parameters and body, manage response data and bind it to the respective view.
To know more about API integration in DhiWise watch our Youtube video or you can visit our help docs for API integration and Adding APIs and Environmental Variables.
Every day new eCommerce apps are emerging in the market, adding more competitors to your app. Product recommendation is one among the several features that can make your app stand out from the crowd.
With DhiWise and product Recommendation APIs you can add this new feature to your app in just a few steps and take your app to the next stage concerning user experience and usability.
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