What are User Reactions?
User Reactions allow readers to provide an emotional reaction to content, by selecting the appropriate emoticon from within the Emoticon toolbar, located near the bottom of an asset. User reactions can either be enabled for an entire site, or on a section-by-section basis. Additionally, User Reactions may be disabled on individual assets within the Other tab for content that could potentially be sensitive to some readers.
In the event that a user mistakenly chooses the wrong Emoticon, this can be resolved by simply selecting another emoticon. Please note that another event will be fired to reflect the correction as well.
Reaction Types
User Reactions support the following 5 Reaction Types:
- Angry
- Sad
- Funny
- Wow
- Love
How to Enable User Reactions
User Reactions are disabled by default but can be enabled within the Community User Accounts Application Settings by navigating to General settings within the Public Profiles panel.
User Reaction options include:
Disabled: No reaction emoticons will appear and no data is collected.
Logged-in Users Only: Only users who have registered and signed into their free User Account will see User Reactions. Data is collected on registered users only.
All Visitors: Allows all Site Visitors to see the Reaction Emoticons on your site. This is also known as Anonymous Users. Data is collected on all site visitors.
User Reaction Page Customizations
Once User Reactions have been enabled on the site, further User Reaction options are available within the Page Customizations, within the Social Tools panel.
User Reactions: This property enables the User Reaction toolbar at the bottom of article assets. It can be used to gather a reaction data from users, which can then be seen in data analysis or can be used as sorting criteria in blocks. Option include:
Inherit from user settings: The Public Profile settings noted above will be inherited.
Disabled: This setting will disable User Reactions for the URL, while overriding the Public Profile Settings.
Enabled: This setting will enable User Reactions for the URL.
User Reaction Text This property creates a title above the User Reactions toolbar. By default, it is blank.
User Reaction Explanation Text: This property creates a bit of smaller explanatory text below the User Reaction heading. It can be useful for details about User Reactions to end users. By default, it is blank.
Data Collection
User Reactions can be used to track user interaction, while creating different audiences for your site using the data collection from these reactions. This data can be used to tailor site content towards users, thus improving the user-experience. For example, a block could be created that includes the Sorting Rule "Reaction Type" and be configured to pull content in from the Highest number of reactions to Lowest, or vice-versa. From the reader's perspective, reactions may be left immediately to what is being viewed, thus seeing more relevant content that is organized based on their engagement.
Reaction Analytics
User Reactions are tracked in Google Tag Manager (GTM), granting admins the ability to learn which assets are the most engaging and the breakdown by reaction. When users engage or react to site content, variables are in place to capture those reactions, which in turn trigger Social Events within Google Tag Manager. These Social Events are then used to trigger a "Page Dimension" in GTM. The comparison of the Action versus Dimension will indicate the percentage of users who are using reactions.
The following Social Events are taken into consideration:
Action: reaction-angry (or other reaction such as sad, wow, love, funny).
Network: The site itself.
Target: The URL the event was triggered on.
Reaction Behaviors
All reactions are tracked by our TownNews iQ DMP (Data Management Platform) program. 'Signals' for Audience Targeting, Ad Targeting and other behavioral content recommendations.
Reader Engagement
TownNews tracks when a User Reactions to an article along with that articles specific meta data. This generates a 'Crowd-Sourced Sentiment' analysis of the content which is able to be used in future data algorithms.