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Analytics vs Reports - Data Calculation Methodology
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Written by Support
Updated over a week ago

February 09, 2017 21:16

Understanding Data In Analytics and Legacy Reporting

It is important to understand that both Analytics and Legacy Reports source their data from the same underlying data set, but their approach and methodologies are different.

We have spent extensive time and effort confirming the data presented in Analytics and Legacy Reports are the same. If differences appear to exist, it is important to understand that we have made meaningful business improvements to the data methodology used within Analytics – methodology that will bring significant benefit to our client’s business but can cause Legacy vs Analytics comparisons to be difficult.

When trying to tie Legacy Reports to Analytics reports, please be aware of the following:


In the below example, data from February 20th would NOT be included:

It is important to confirm that when comparing information between Legacy Reports and Analytics that the Date Range is set the same. In Legacy Reports, the Date Range is set as “from date X through date Y” with both the “From” and the “To” including the date set.

In Analytics, the Date Range setting is slightly different and is set as “from date X until (before) date Y” with the “From” including that data and the “until (before)” NOT including data for the date indicated. To include data from the specified end date in Analytics then the Date Range should be set for one day longer than wanted. (desired end date + 1)

Separately, (coming very soon) we are migrating Legacy Reports to be delivered through the Analytics platform – actually, once done, there will be Legacy Reports 2.0 and Legacy Reports 2.1. A key thing to keep in mind regarding Legacy Reports 2.0 is that they will be re-written as an EXACT copy of the current reports, except they will be delivered through Analytics – no structural, data, or calculation changes of any kind are being made to them to maintain support of, integration with, client-built processes outside of

Regarding Legacy Reports 2.1 we will include enhancements and improvements such as added data elements, added columns, changed data labels (to ensure consistency with Analytics and our published data and measure definitions). Over time, we expect clients will migrate to Legacy Reports 2.1 given the improvements.

Acquisition Date vs. Transaction Date

Acquisition Date allows the system to organize the data by the date that the original order was placed. This enables Analytics to present data in an appropriately connected way. Specifically, Acquisition Date associates Re-bill and Recurring transactions (Cycles 1…X) to the Initial transaction that initiated the order.

When calculating many measures, disassociating the recurring transaction types from the date of origination (the Initial transaction) would cause arithmetic inconsistencies and would deliver incorrect and misleading results - and ultimately incorrect business decisions.

As an example: measures that incorporate time-phasing and transaction type correlation into the calculation (think Re-Bill rate or Chargeback Rate) require the association of a transactional event to other components of the overall order within a timeframe.

But, there are instances where you may want to simply see the count, or summarized value, or count by transaction type, or transactions within a period. When this type of analysis is appropriate, Transaction Date would be used. (within Analytics, it will be noted as such)

Data presented based on Transaction Date will organize the data by the date that transaction was performed without any association to any other component of that transaction. As an example, Transaction Date will not associate the relationship between a Re-bill transaction, or a Recurring transaction (Cycles 1…X) and the Initial transaction (Cycle 0) that initiated the order. Reporting using Transaction Date simply performs calculations on all transactions within the designated date range.

You may find the following Help Center articles relevant to Analytics helpful.

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