Memo is the only platform that partners directly with publications to report readership data (article traffic). Today, we’re announcing an extension of our direct-from-publisher data with Predictive Readership – adding thousands of publications to Memo’s robust analytics platform.
How Predictive Readership is Calculated
Predictive Readership calculates how many people likely read an article based on tens of thousands of attributes, including headline, topic, day of the week it was published, industry, region, average article traffic for the publication, and so much more.
We built, trained, and refined the Predictive Readership model based on article readership data from our database of millions of articles across thousands of publications and tens of thousands of tags, categories, and attributes within them.
What it Looks Like
Memo’s Enterprise analytics platform reports readership at an article level for brands, their competition, and key topics they care about. Users with Predictive Readership can now see predicted readership alongside all other coverage with an indicator to differentiate it from Memo’s standard, verified readership numbers. You can also filter it in (or out) of your view within the dashboard, export data, and integrate directly with our API. This is what it looks like in the dashboard:
Memo’s Reporter Intelligence database reports reporter readership averages, topic readership for reporters, and readership for individual articles. Users with Predictive Readership will see predicted readers next to articles and for reporters that contribute to publications with predicted readers.
To learn more about Memo readership, visit https://memo.co/readership/.