Jepto

@elliot_anderson1 Thanks and a great question. No they are not, we researched a range of Algorithms in our testing and decided that the best option would be to take advantage of the Data Science community and utilise open source algorithms. They have the resources and community around them to improve over time. For the KPI predictions we are leveraging the Facebook Prophet algorithm, which has great accuracy and is considered the current standard for this type of real time prediction (You can select any Google Analytics metric and we will run the algorithm utilising 3 years of your own historical data to give you a live preview of the prediction) For our Anomaly Detection feature we are utilising Twitter's Seasonal Hybrid ESD algorithm. We also did a lot of research in this space and found that there was not one size fits all algorithm because different use cases will want different anomaly thresholds. So to overcome this we have exposed all of the inputs to the algorithm so you as the user can adjust the sensitivity as you seen fit. To make this understandable (as the algorithm hyperparameters can be confusing) the preview is also in real time and shows you how many anomalies would have been detected in your last 3 months of Google Analytics data so you can find the right fit for you. We are also working on adding influencing metrics to KPIs, so you can nominate a metric that affects your KPI metric to achieve a higher level of accuracy.

@errol_mathew Depending on what platform you use for call tracking, many of them utilise the offline measurement protocol in Google Analytics, you could definitely do that.

@dmac sweet! What would that look like on your RAD dashboard ?? - I’m going to look that up and get back to you.