Muvi has just announced two-step-integration feature for its popular recommendation engine Alie. Being AI-powered and industry-agnostic, Alie has always been in the limelight for the diverse sectors. And this new feature is expected to be a game-changer for the Alie customers! From now on, you can integrate Alie with your websites and apps in just two simple steps! Sounds intriguing? Let’s see how!
Alie ingests data from your website or app in four unique ways-
- APIs- Now your host of API can ingest data to Alie in order to generate recommendations!
- Webhook– It is an event-driven API type. What does that mean? So, when a particular event occurs such as – new purchase, sign up, user click on product etc., the relevant information passes via it. You can configure the webhooks on your website or app.
- RSS Feed- It allows the product related data to be scraped from your website or app on which Alie feeds to recommend the appropriate products to the users.
Once Alie gets the relevant data in any of the above-mentioned ways-
It analyzes them ——> Returns the list of recommended product IDs through accelerated inference APIs. Now, what is that? So, this type of APIs can be invoked to display recommendations to your end-users on any page you want on your website or app. For instance, if you want to recommend the best-selling products on the home page and the similar products on the shopping cart page, it will let you do that!
As you know, Alie can be used across diverse industries starting from e-commerce platforms to online news portals. Here we have listed out some of the use cases with the focus on this new feature-
1. Alie customer X owns an e-commerce platform. X wants to recommend products to the end-users on the basis of their recent clicks on the similar products. X configures webhooks on his website to ingest data to Alie based on the event ‘user clicks on products.’
End result: End-user A has recently viewed court shoes and hiking shoes on the e-commerce store. Other similar shoes will be recommended to A.
End Result: End User P has just purchased a new license. P will get recommendations of other similar licenses.
3. Z has an OTT platform. Z wants to recommend movies on the basis of the preferred genres to the end-users. Alie lets Z extract the product related data such as genre through RSS to feed Alie. Alie analyzes the genres of various movies or series and generates appropriate recommendations to the viewers. Product data includes product ID, category, product upload time, price, etc.
Q has just finished watching Wonder Woman. Q will get recommendations of Justice League, Aquaman, Batman vs. Superman, and other similar movies.
4. C owns an e-learning portal and wants Alie to ingest the data related to the user demographics. The host of API of the e-learning platform lets Alie collect the user demographic data such as age, country, gender etc. to generate precise recommendations.
End user R has signed up recently and updated his profile details. R’s preferred language is English. The study materials in the same language will be recommended to R.
Alie is always ready to deliver you more than what you look for in a recommendation engine! It provides you with real-time analytics to let you assess the returns on your investment. It offers you the insights on which recommendations are driving more clicks, purchases, engagements, or views to help you in leveraging the opportunities more effectively!
To know more, visit our Integrate Alie Feature Page.
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