Three NewsWhip metrics that will keep you one step ahead when managing live issues

In a world of retrospective analyses and next-day charts, it can be difficult to manage live events as they unfold. We know that our users are charged with managing the reputation and coverage of some of the world’s biggest brands, and that’s why NewsWhip’s metrics are built with speed in mind, to make sure they’re ahead of the game and not facing any nasty surprises. 

Users will likely be familiar with our Total Interactions metric, giving you an at-a-glance view of the total amount of engagement a given article or social post has received, but here’s a reminder of three NewsWhip-native metrics that are built on top of that total interactions data to help you through the next time you need answers at speed. 

Predicted Interactions

Predicted Interactions does exactly what it says on the jar — it takes the total interactions that an article or post has received in the time since publication, and extrapolates on it using our patented algorithm, predicting performance as much as 24 hours in the future. 

This is particularly useful when you’re tasked with seeing if an issue will continue to grow or if the bulk of the momentum is already behind it. Whether you want to flag a potential problem or opportunity or calm a C-suite executive who is worried about a rogue tweet they saw, Predicted Interactions can help you do that. 

Highest Velocity

Highest Velocity is a measure of virality, and acts like a speed gun showing you how fast an article or post has spread. It checks the rate at which an article or post gets new interactions at regular intervals. It then displays the highest point at which these new interactions were obtained at any point in its lifetime.

This allows you to see which articles made a big splash, and identify the fastest growing content at any time, helping you to prioritize the signal amidst the noise. 

Overperforming

Overperforming is a publisher-level metric that tells you how much interest an article or post has compared to the average for that publisher or Page, represented as a multiple. This works best when you are focused on coverage from one publication or a handful of publishers, and you can measure performance of mentions of your brand compared to other articles from them at a glance. 

This removes the guesswork and gives you something tangible to contextualize performance without having to dig through thousands of articles, allowing you to instantly gauge the public’s interest in what’s been written. 

We’re committed to helping you get to that next layer of analysis, to find the signal in the noise even quicker than before, and we’re confident that these metrics will help you do that.

If you have any questions about how best to use them, don’t hesitate to get in touch.