We report to the customer monthly the extra revenue we have generated with Datatrics.

If I add up the extra revenue per month, I arrive at 222.05.

However, when I select this total period in Datatrics, I see an extra turnover of 246.58. How can that be different? The numbers are based on the same report, only in one, I look at it per month, and in the other, I look at it for the total period.

I understand that it may differ slightly due to rounding, but a difference of almost 10% seems a lot to me.


This is because, with the calculation of the total extra revenue, you are extrapolating in periods in which the proportions of all data may have been different.

If you calculate the extra turnover in a shorter period, the ratio of the data used (number of profiles, turnover) will be different, and you will arrive at a certain extra turnover for that period, but in a different period, the ratios will be slightly different.

It is always better to draw conclusions with more data and in more extended periods when you calculate the extra turnover based on extrapolation, so for example, an entire period that you use Datatrics instead of just looking at the past month.

Circumstances are different throughout the period: there may be more or fewer touchpoints displayed, the A/B group ratio has been adjusted, and there are more people or fewer on your website.

Even if you have the A/B test on 50/50 for an entire period, it can have a ratio of 49.43% / 50.57% for one day and 50.03% / 49.97% on another day.


The example in this URL shows that when you calculate an extra turnover per month or for the entire period by means of extrapolation, you arrive at a different additional turnover.

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