Use predictive analysis to prioritize
The what-if analysis widget is a data science feature that uses predictive
analytics to tell you the impact of performance changes on conversions, revenue, and other
With version 3.0 of what-if analysis, you have more flexibility in how you interact
with the interface. You can choose which timing metric to analyze, which filters to apply, and
which dimension to break down the analysis. You’ll be able to see how shifts in a sub
population will contribute to the overall revenue increase.
The summary provides real-time performance results based on the metrics and the time period
that you select. The Reality tab is the default view that shows your current performance
results along with projected improvements. The Possibility tab shows your projected
This example of the reality view shows the number of visits (1.6 million)
recorded and the number of beacons gathered (30.7 million) within a four-day time period.
The chart shows the median load time (2.47 seconds) and the median conversion rate (8.72%)
during this time period. All of the recorded metrics are listed on the right. The x-axis
represents the session load times in milliseconds. Projections on improving your total
revenue are calculated for you.
Based on the projections given in the reality view example, this possibility example shows
the results of the projected performance improvements. The chart represents how changing the
median load time by 419 ms during this time period can improve the median conversion rate by
1.02 points, which in turn improves the daily revenue by $1.6 million dollars. The projected
metrics are listed on the right.
How are projections calculated?
Each time a what-if analysis is generated, mPulse calculates the optimal load time to get
the highest conversion rate with the least amount of change in load time.
Load Time & Metrics
This view shows an individual chart for each of the business metrics that you
want to optimize for.
The metrics are projected based on the real user traffic on your application and reflect
predicted behavior based on a given page speed. The circles are your goal metrics. These are
the points at which mPulse predicts the best improvement in a metric relative to the
improvement of the page speed. The horizontal lines are how mPulse predicts those metrics
will change. Your current business metric and load time position are shown under Current.
The session load time (page speed) is on the x-axis.
To adjust a metric, enter the value in the field provided under Projected or drag the
slider up or down. To adjust the page speed, click the speed until it reaches the desired
value. Once you set your goal speed, the other metrics are updated, and you’ll see the new
projection in the summary’s possibility view.
The breakdown view shows performance distributions based on the selected Group By filter.
In the example below the Group By filter was set to “Country”. The top ten attributes of the
dimension are shown in this view, and each can be modified independently. Business metrics
and overall site speed are projected based on the individual modifications. Speed can be
adjusted by moving the page load time slider under each chart; when released the chart and
metrics will update to present the new results.
Use the filter bar to select your app, timers, metrics, dimensions, and date range to
capture performance results, as shown in this example. The Group By filter will enable the
Breakdown section of the report, revenue and conversion metrics should be set here if available.
This widget is available from the widget type directory. Just Create a custom
dashboard, drag and drop the What-If v3.0 icon on the dashboard, then use the filters to
select the time period and metrics for your analysis as shown in this example.