What's new in THRON 6.3

Business Case:

KPI to be measured

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We are pleased to announce that THRON has been upgraded to its version 6.3! 

This update focuses mainly on simplifying the creation of Predictive Content Recommendations and improving the customer experience on online channels through a new content type such as 360° Product View and the possibility of recommending content via Player.

 

360° Product View 

To allow your e-commerce users seeing the products in a more complete way, you can now create 360degrees product representations (to show the product from all its angles) and also animations (to show how the product works or can be used). 

To create a 360 Product View, you need to upload in THRON multiple images of the same product taken from all angles; if you want to create an animation, you need to upload a sequence of images to recreate the animation. If this content is created via Dashboard users will found a new specific action in the “+” menu. If the content is created via API, users will have to use the insert web service and create a new playlist by setting a specific parameter.

The whole procedure is illustrated in this article. 

For 360 product view content type you can create specific Player templates via Content Experience Manager. 

 

New Predictive Content Recommendation

Predictive Content Recommendation has been updated. Not only it has been optimized to speed up loading and updating, from now you will be able to create two different types of recommendation according to the use case:

  1.  The first one is for guiding users across different pages of your channels (URL content only) via widgets (horizontal or wall). 

  2. The second one is for increasing the retention on a same page and is delivered via THRON Player (any content type): at the end of the content playback, users will automatically be offered another content based on their interests. 
    When creating an embed code, users will be able to set a flag that enables the recommendation of other content at the end of the visualization. If the flag is active, users can choose  the specific Predictive Content Recommendation that has to be used among those already active in the platform. 
     

These types of Predictive Content Recommendation must be created and configured via THRON Dashboard, their integration in front-end can be done in two ways: 

  • Via widget or Player (according to the type) 
  • Via API 

The procedure to recommend content via THRON Player is described here.

The procedure to recommend content via API is described here.

 

Measure PCR performance 

Every Predictive Content Recommendation (Both Player and Widget) have its own dashboard through which you can measure its performance (number of impressions, number of clicks and relative click-through-rate). 

Data provided in the dashboard can be filtered by a time interval (30 – 7 – last day). The dashboard provides the following information: 

  • Total recommendations: the total number of recommended content (e.g.: a widget that recommends n content, counts n). 
  • Single contacts to which the recommendation has been submitted: it is useful to know how many people visited a content inside that PCR; it is defined as the ratio between the number of contacts that clicked and the number of contacts to whom a recommendation has been made.
    Note: No matter how many times a recommendation is made to the same person, it will always be counted once. 
  • Most clicked topics:
    • Tag 
      • Number of clicks on content with that tag 
      • Number of recommendations (the times content with that tag has been proposed) 
      • Relative CTRs (click-through rates) 
      • List of the of the most recommended content for that tag; and for each of them: 
        • Number of clicks 
        • Number of recommendations 
        • Relative CTRs 
  • Most clicked content 
    • Content 
      • Number of clicks on that content 
      • Number of recommendations of that content 
      • Relative CTRs 
      • Profiles of the contacts whom that content has been recommended to 

For each element (both tag and content) an indication of the performance compared to the average of the recommendation is also given. This way you can also know which topics and content to invest most in. 

 

To have a quick dive into the news of this release, have a look at this page.  

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