Screenshot Flagging for User Behavior Analytics

ActivTrak’s Screenshot feature enables administrators to capture clear images of users’ screen activity. With the ability to capture thousands of screenshots per user per month, you need a simple and efficient way to find instances of inappropriate screen content. Screenshot Flagging takes the manual work out of reviewing every image for explicit content.

Identify NSFW Internet Usage

Identify NSFW Computer Activity

When the flagging feature is active, ActivTrak analyzes the content of every screenshot to categorize unsafe images into three categories — medical, violence, and adult. Toggle the Screenshot Report to show only flagged screenshots. Add granular filtering to find unsafe screenshots by date, user, application, website, computer, executable, or description.

Evaluate the possibility of offensive content in each image by checking Unsafe Ratings -- Very Unlikely, Unlikely, Possible, Likely, Very Likely. Understand the flagged screenshot in context with key details about the activity. Each screenshot is accompanied by the following information:

  1. Computer Name
  2. User Name
  3. Titlebar
  1. Productivity Rating
  2. Timestamp
  3. Application
  1. Executable
  2. URL
  3. Unsafe Rating

Shield ActivTrak Account Managers and Administrators

Shield ActivTrak Account Managers and Administrators

Configure an alarm to capture images or videos of a user’s screen to see exactly what the device user sees. For still images, take a single screenshot or multiple screenshots at a minimum interval of 10 seconds. Take advantage of our Video Playback Add-on to record up to 30 seconds of video. Capture 15 seconds before and after the triggering event. View all screen captures with accompanying activity data in the ActivTrak app.

High-level Organization Insights

High-level Organization Workflow Insights

Draw conclusions based on your account’s screenshot flagging usage statistics. Identify the months with a higher than average amount of flagged screenshots. Use the data to discover correlations between flagged screenshots and other factors like seasons, staff makeup, and office culture.

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