How to Nudge Users to Continue Watching Content


"Continue Watching" is one of the most common section that we can find in any OTT website or app. This section helps intrigue users to complete the series or movies that they have started in the order of recency. Similarly, sending out communications conveying the same, can help us improve metrics such as watch time and engage the user in a smooth manner.

In the long run, communications like these help us retain our users and keep them hooked provided the suggestions are in the right order. Also, the engagement to these communications can help us predict the user behaviour on what they like to watch, when, and other related insights. Moreover, this helps us not just to remind the users, but also subtly conveys that the app understands the user. This provides better customer experience, which in return will increase their loyalty to the app.

The following are some use cases we can achieve with this strategy:

  • Recommending content a user has rated good and suggest them to re-watch it
  • Recommending content a user has marked watch later in the last 30 days and has not started watching it

In this article, we will create a Push campaign to recommend your users on what to watch next. Leveraging the Product Catalogue feature, we will take advantage of cross-channel messaging to nudge users about the content they have viewed but not completed.

Expected Result

Users receive a Push Notification on their phones, with recommendations to continue watching content:




  • Events to track the action of a user searching for content, watching the content, adding a content to watch later, rating a content, completing the content and each action’s related information such as the genre, title, type, progress, rating, platform. To understand how to track events, refer to the Developer Guide. Note that the steps might differ based on the SDK being used.
  • Mapping of the tracked events above to concerned MoEngage events. Mapping these events helps us in understanding the action and thus running our recommendation models and querying models on top of it to create an expected output. For information on mapping custom events to MoEngage events, refer here. In this example, the custom event of starting a content will be mapped to "Product Viewed" and the custom event of completing a content will be mapped to "Product Purchased".
  • A catalog and a respective feed that has a list of available contents and all related information about the same from the name or title to the director, cast, and description to any awards that the title won in any category. Set the feed to refresh at a suitable interval so that the latest information can be maintained. For more information, refer to Catalogs.
  • Settings for one or more channels such as Push, Email, SMS, or WhatsApp.

Create a Recommendation

In this section, let us create a recommendation based on the users action:

  1. Navigate to the MoEngage Dashboard and select Content > Recommendations from the left navigation. The Recommendations page is displayed. For more information, refer to Creating User Action Recommendations.
  2. At the top right corner, click + Create recommendation. It takes you to the first step "Select recommendation model".
  3. In the Filter by user action and item attributes section, select the User Actions model.
  4. Click Next. It takes you to the second step "Create recommendation". Enter the following details:
    • Recommendation name: Enter a name for the recommendation. For example, "OTT_ContinueWatching". This will be the name through which you will refer the output of this recommendation model.
    • Recommendation description: Enter a description for the recommendation. This description will help you understand what the model is aimed at.
    • Catalog: Select the catalog that has all the list of content provided in your platform with all the related information starting from the title to director’s name, casts, genre to any awards that this has won.
  5. In the Filter recommendations by user actions section, filter the contents that the user has started watching but not completed.
    1. From the Item where user performed drop-down list, select “Product Viewed”.
    2. Select the Exclude checkbox.
    3. From the Item where user performed drop-down list under Exclude, select “Product Purchased”.
      This query provides the list of content that a user has started watching in the last 10 days but has not completed in the last 10 days.
    4. In the Sort the filtered items section, from the Order results by drop-down list, select "Most Recent".
  6. Click Create to save the changes and create the recommendation. The status of the same will be "Active" on the Recommendations page.
  7. The Recommendation engine shares the set of content a has started but not completed in the last 10 days, sorted by the recency.

Now that the recommendation is created, let us create our Campaign to nudge people about the content that they have viewed but not completed.

Create a Push Campaign

In this section, let us create a campaign to recommend your users to continue watching OTT content:

Step 1: Target Users

  1. Navigate to the sidebar on the left and click Engage > Campaigns and click + Create campaign or click + Create new > Campaign.
  2. Under Outbound, select Push > Periodic.
    You are taken to the first step "Target users" of defining your campaign.
  3. Enter the following details:
    • Team: Select a team if your organization has teams enabled for your account. For more information, refer to Teams in MoEngage. For example, "UseCases".
    • Campaign name: Enter a name for the campaign. For example, "Continue Watching".
    • Campaign tags: Select the required campaign tags.
  4. In the Target Audience section, select All users.
  5. In the Target Platforms section, select Android.
  6. Click Next to move to the second step "Content" where you can define the content that will go into your Push campaign. 

Step 2: Content

  1. Select the template that you like to go with. For our example, select Single Image Carousel.
  2. In the Message title field, enter a title.
  3. While defining the message, select the product set that is generated through the recommendation that you defined. Enter “@” and search for “OTT_ContinueWatching”, the name of the recommendation that you built, in the Push Personalization pop-up.
  4. Click Done. The following JINJA code is inserted in the Message field:
  5. Edit the code to run a loop through each content and list down the title of the first 5. The final JINJA code looks as follows:
        {% if ProductSet.OTT_ContinueWatching%}
    {% for product in ProductSet.OTT_ContinueWatching[0:5]%}
    {{product.title }}
    {% endfor %}
    {% else %}
    {% endif %}
    In line 3, {{product.title }} will have the title that we have passed in our Catalog for each one of the feed. The loop runs through the product lists provided by the recommendation. Because you selected to sort the list based on recency, you are only looping until first 5 here.
  6. Enter the following code to get the image of the recommended watch:
    1. In the Carousel Content section, add 5 images of the titles.
    2. Select the Image URL option and enter the following JINJA code for each slide by changing the line 2 as explained below:
      Here you can find the code for the Slide 1:
          {% if ProductSet.OTT_ContinueWatching%}
      {% for product in ProductSet.OTT_ContinueWatching[0:1]%}
      {% endfor %}
      {% else %}
      {% endif %}
      In line 2, you are defining the loop to go through just the first item and {{product.image_link}} in line 3 will provide the link to the image.
      Similarly, for slide 2, the line 2 will change as {% for product in ProductSet.OTT_ContinueWatching[1:2]%} and so on.
  7. Click Next to move to the third step "Schedule and goals" where you can define the schedule and goal of your campaign.

Step 3: Schedule and Goals

  1. In the Send campaign section, select when the campaign should be delivered to your users and the periodicity of delivery
  2. Change the deliverability settings based on your requirements. For more information about these settings, refer to Create Push Campaigns.
  3. Click Publish.


In this use case, we created a Push campaign to recommend your users on what to watch next. Now that we have published the Campaign for our use case using Recommendations, we can check out other possibilities of MoEngage’s Recommendations.



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