How exactly does the analysis for continuous stories work? This article will explain the different analytic types that power each sentence in your continuous narrative.
Continuous stories measure trends over a certain period of time. The analytics types for these narratives include performance, progression, averages, totals, streaks, volatility, segments, and predictions.
Take the sample narrative below, which measures Sales per month:
Let's break down the analytics type driving each bullet.
The first two bullets use average and range functions to call out the average, maximum, and minimum values across the entire time period you are analyzing.
The third bullet covers overall performance of your measure over the entire time period. Did sales increase? Decrease? Did the trend at the end of the period match the overall trend?
The fourth bullet uses progression analysis. This sentence will call out the largest increase/decrease based on your measure during the time period, using both a percentage basis and absolute basis.
The next few analytics types are correlation, segments, and trendline.
Here is an example of a correlation bullet:
As you can see, these bullets will mention any notable correlation between different series in your data.
Here are examples of segment bullets:
Segment analytics calls out noteworthy increases/decreases in the time period. You can adjust the settings for segment analytics in the settings module under the Analytics tab. Specifically, you can change the threshold for percent changes that you find noteworthy and want to be mentioned in the narrative. For example, if only changes of 60% or greater are interesting to you, the narrative will not include content about a trough in a time series that featured a 30% decline.
Below is an example of a trendline bullet:
Trendlines are determined by how well they fit your data with a certain percentage of confidence. You can adjust the settings for trendline analytics in the settings module under the Analytics tab. Specifically, you can set the minimum confidence level that the narrative should include content related to an overall trend line and prediction. For example, if an overall trend line can be drawn at 90% confidence, but you have set the threshold at 95%, content about the overall trend or predictions will not generate. You can also turn on/off predictive analysis.
For more information on Segment and Trendline analytics, reference this article.