Almost daily I field questions from marketers who are trying to compare two different reports.  They are confused because the numbers don’t match.

There are many, many, many reasons why, when comparing two reports, even from the same system, the numbers will not match.

The reasons are (and each week, I will cover one reason in detail):

1. Attribution Reporting

Attribution reports’ calculations update daily and divide credit (orders, revenue and profit) over all of the contributing ads, impressions and clicks that led to a sale or other conversion.  Attribution is a newer concept for many marketers.   The fact that there is now the idea of a fraction of an order is definitely a different way of thinking.

2. Non-Attribution

Most marketers are very comfortable with non-attribution reporting.  Common examples of non-attribution reports are reports that are used for operational decisions, for example a Daily Order Report from a shopping cart.  Problems arise when trying to compare an attribution report to a non-attribution report (comparing apples to oranges).

3. Multiple Data Source – Over Counting/Over Crediting

If web analytics have not been configured to track all of the different sources of traffic to a conversion level, marketers are left to rely on reports provided by the source itself (e.g. Google AdWords Reports, Yahoo Search Marketing Reports, as well as other vendors like Display, Affiliates and Email).  Because none of these sources are ‘aware’ of the other sources, conversions and revenue can be over counted, and therefore, over credited.

4. Under Counting – Under Crediting

This is a by-product of the limitations of last click.  If you are using traditional web analytics, this is likely a problem.  Because the referrer only pays attention to the last place where a visitor came from, you wind up under crediting certain sources.

5. Accuracy – Data Quality of Web Reports

Here is the big elephant in the room that no one wants to talk about.  It is possible that the data that you are relying to make important spending decisions is wrong.  The number one cause, in my experience, is a problem with the implementation.  Examples I have seen of implementation problems are code not being on every page, conversion code not being on the page or not being correct, and profiles or other settings that have not been configured properly.  It is definitely worth auditing your implementation, even if you are using a free solution.

6. Bonus:  One web vendor report to another

Even armed with the knowledge that both implementations are correct and complete, it is most often an exercise in futility comparing one vendor report to another.  The reason for this:  each company has a different idea of how metrics should be defined and calculated.  And each company has settings both internal and external that define how metrics are calculated (e.g if someone is on your site for 60 minutes are they one visit or two).

This week – Attribution

Attribution is a difficult concept.  Take pay-per-click as an example.  In order to fairly and accurately measure an ad, you have to think about latency.  On the day an ad runs, some of the conversions will take place.  But some people will come to your Web site from the ad and not be quite ready to purchase.  They may decide to return to your site a few days later and purchase.

To be ‘fair’ to your ads, you have to be able to count these conversions and credit them to the original ad (or multiple ads if several were seen along the way).

For example, say someone clicks on a Google ad on April 27^th.  They get to your site but are not convinced to purchase.  Instead they continue their research.  The next day, April 28^th, they go to Yahoo, click on an ad and purchase.

If you are attributing credit, here is what your reports look like:

April 28, 2010 – Yesterday’s Report

Here’s the tricky thing – the numbers change.  In order to give credit for latent conversions, the historic performance will then change.

April 29, 2010 – Custom Report Range 4/27/2010

There is no additional ad spend, but the .5 order is now credited to the correct day.

And this impacts all of the calculated metrics.

April 28, 2010 – Yesterday’s Report

Here’s the tricky thing – the numbers change.  In order to give credit for latent conversions, the historic performance will then change.

April 29, 2010 – Custom Report Range 4/27/2010

And even a step further, this impacts the ROI for each day.

The best thing about solutions that provide attribution reporting is that they supply this information already pre-calculated, so you don’t have to think about these types of calculations or even consider the fact that there are now fractions of orders.