We're constantly striving to make improvements to our platform, and are always expanding the list of metrics that we track. Today, those metrics include:
- Page views
- Average/total engaged time
- Average scroll depth
- Social actions
- Device type
- Referral buckets
SIMPLEREACH PROPRIETARY METRICS
- SimpleReach Predictive Score
Cool, but what does all of this actually mean? Allow us to explain...
Page views are a count of the number of times our tag was loaded on a certain content item. We do not de-duplicate page views on a time frame or user basis. If a user loads a content item and reloads the page 10 seconds later, we count that as 2 separate page views.
Uniques provide the number of individuals that access the content, and are deduplicated based on the dashboard. We count uniques via a cookie that does not include any personally identifiable information. We currently do NOT de-duplicate uniques across browsers or devices.
AVERAGE/TOTAL ENGAGED TIME
Average and total engaged time are calculated as active time with content. Active time means the content must be in the current active tab in the browser, the browser must be the focused window, and the user is performing actions (scrolling, moving mouse). We count active time every five seconds, and will continue to count as long as an action is seen within seven minutes of the last action (to account for content that may be longer to consume, such as video). If a user leaves their computer for 20 minutes and re-engages with content, we will start counting again, but will not count the 20 minutes.
If you're looking at those numbers in a export, average engaged time x page views = total engaged time in seconds.
AVERAGE SCROLL DEPTH
Average scroll depth gives the percentage of page views that reached a certain point in the content. We capture the data by quartiles (25%, 50%, 75%, 100%). Each subsequent quartile is a subset of the previous one, meaning, if someone hits 25%, and then 50%, they will be counted in both.
Social actions are an endorsement or share of content via a social network or aggregator. We work with the social networks’ APIs to capture all social action data based on the URL of the content. Our system knows to start looking for social actions as soon as a piece of content receives one page view with our tag active on the page. Social actions include:
- Facebook reactions, comments, and shares
- Pinterest pins
- Twitter tweets
- LinkedIn shares
Similar to social actions, once a piece of content has been viewed, we use Twitter’s API to capture any tweets that include a link to that content piece. If there are URL shorteners being utilized (e.g. t.co or bit.ly), we unroll the shortener to which content piece (and canonical URL) it points to. Tweets are ranked by the most influential users who have tweeted the content piece by utilizing the tweeter’s Klout score.
Referral buckets are determined by utilizing the referring URL in the header of the HTML. This is a standard method of determining referral source. We break out referral source into 5 major buckets: social, apps/IMs/email, search, internal, and other sites.
Social: reflective of any social networks or aggregators we track. For example, a user on Facebook who clicks on a link to your content and then arrives on your content, is counted as one social referral.
Apps/IMs/email/etc.: traditionally called “Direct” traffic, signifies no referring URL.
Search: major search engines, in aggregate (i.e. Google, Bing, etc.).
Internal: internal traffic from your site.
Other sites: known sites that do not fall into any other buckets.
We can also determine whether referrals are organic or paid using a combination of query string parameters and referring URL.
If a piece of content is shared with the query string parameters still included in the link, we will continue to count any traffic driven from that link as paid traffic. Effectively, paid traffic accounts for both paid and earned visits to content.
Device type is determined by utilizing the user-agent ID of the browser that is being used to read the content piece. Because browsers are unique to devices (i.e. Chrome for desktop vs. Chrome for mobile), we are able to determine which device type is being used. We break out device type into desktop, mobile, and tablet.
SIMPLEREACH PROPRIETARY METRICS
SIMPLEREACH PREDICTIVE SCORE
The Predictive Score (a number 0-99) is assigned to each content item according to our proprietary algorithm, which forecasts the social traffic the content item will receive in the next few hours. It's calculated using data we've gathered across 90+ million content items and takes into consideration 100+ variables like Social Actions, page views, and time-dependent metrics.