Attribution management begins with a tracking technology in place that allows you to track both clicks and view-throughs, and tracks beyond the last click. Here’s an example of the type of data available on a particular order if an attribution management technology is in place….

Continue reading article on Search Engine Watch Blog…

A Visual Blog

In previous posts, I’ve tried to explain the reasons behind the frustrating fact that some report data just won’t ever match. This week’s topic is a no-brainer. To best describe why reports created by pulling data from different data sources won’t match other reports, let’s see it visually.

So, why is this a problem? Say you haven’t configured your web analytics to track your PPC, or maybe an agency is managing your PPC, but you have not given them access to your web analytics, so you must rely on the data the search engines provide. Inevitably, someone in your organization is going to want a roll-up or an executive summary of all the engines. The result is then the creation of a report from disparate data sets.

The problem – each vendor report is not aware of the other vendors. So, in the example below, each vendor report will claim credit for the entire purchase and claim all of the revenue.

As you can see, this greatly overvalues the conversion and creates an unrealistic view of the performance.
If you do try to compare the compiled report to your web analytics, there will be a problem as to how web analytics will credit that sale, as you can see below.

The real need is to conceptually ‘divide up’ the order and revenue and give everything credit.

By thinking about dividing up credit, you more accurately value the contribution of each advertising source. With this accurate and comprehensive picture, you can really optimize your spending, ensuring that you focus your spend, time and attention on what truly is working. What you may then find clicks (and impressions) that occur at the very beginning of the ‘funnel’ are getting the credit they deserve, so you may be able to increase bids on your more general keywords or show true ROI on banner impressions.

Attribution management is a practice that is starting to get more attention from online marketers, fueled partly by the pressures they are under to make smart decisions on online ad spending.

Attribution is a method of determining which of your online ads lead a customer toward a purchase decision, and pinpointing the level of influence of each of these ads. Traditional web analytics has been helpful in determining which sites are “sticky,” and which sites draw qualified traffic, but attribution goes a step further…  continue reading on DM news site

The first meeting included people from companies such as Range Online Media, Rosetta, Under Armour, JC Penny, Google, Rimm Kaufman Group, QVC and American Eagle. The goal of this first meeting was to establish a charter for this SIG. These are the three goals that emerged:

1)  Review current multi-channel allocation methodologies for determining incremental sales, highlighting the pros and cons of various approaches;

2)  Review available and emerging technologies for tracking and allocation;;

3)  Recommend best practices for retailers to implement in their organizations to effectively measure the incremental impact of their marketing dollars.

In order to achieve our charter, we setup two groups during our second meeting: Group 1 is Case Studies, and Group 2 is Technology. Group 1 (Case Studies) is working with a few of the eTailers in the group that are currently performing attribution management to document the process they are using today, and the before and after affects that attribution management has had on their marketing decisions and their organization as a whole.

Group 2 (Technology) is evaluating current technology that exists in the attribution space, as well as identifying features that attribution management should contain in order to track effectively, measure accurately and produce actionable data to improve the bottom line.

Once the case studies are completed, we are going to bring in analytics experts to audit our findings and validate our processes and recommendations. These “analytics experts” will be some of the most recognizable names in the field.

The third meeting took place on September 22^nd at the Shop.org Summit in Las Vegas. In this meeting we vetted some of the challenges with creating case studies about attribution, as well as some of the data points that need to be captured to make the case studies worthwhile. One challenge that arose when trying to produce before and after results is using two different time frames. For example, a company might have been using last click attribution in Q4 2008, then switched to multi-touch attribution in Q1 2009. If we compare profit, revenue, sales figures, etc., the increases or decreases we may find may have nothing to do with attribution, but more with the time of year that we are in.

We also identified some data points that we need to have in the case study. We recognized that the companies that take part most likely will not want to share any personally identifiable information, as they don’t want to give away any findings or secrets to their competition. Some of the data points that we agreed need to be captured are the marketing mix that attribution is being compared across, the ad spend, the type of attribution, and the industry the company is in, beyond just knowing they’re an eTailer.

A the end of the third meeting, we all agreed to have firmly established outlines for the retailer case study and technology review prepared for the next meeting, which will take place in later in October 2009. The ultimate goal is to publish the retail case study and technology review sometime in Q1 2010 after the 2009 holiday shopping season has commenced.

If you would like to keep up to date with the findings of this SIG, go to www.shop.org and search for ‘Attribution SIG’.

If you would like to read more about ClearSaleing’s findings in the world of attribution, please visit www.AttributionManagement.com or contact us directly.

This is the first blog in a 10-part blog series for the Attribution Management Buyers Guide. This first section focuses on Attribution Variables, which are the key metric(s) by which your advertising analytics solution values conversions and attributes credit across the participating team of ads.

Most advertising analytics packages that offer attribution will attribute credit according to one of the following three metrics: 1) profit; 2) revenue; and 3) conversions. Some packages can attribute all three metrics as well.

There are pros for each one of these variables, and cons for some:

• Profit:
  • -Pro - Businesses are in business to do one thing – generate profit. Therefore, anytime you can measure a business activity according to the profit it drives, the better you understand the value of that activity. The same is true for advertising – if you understand the profit a particular ad generates, then you definitively know if that ad is worth continuing to buy or not.
  • -Con - There are none, however, we realize that calculating profit can be difficult for some business entities.
• Revenue:
  • -Pro – If you cannot get to profit, this is the next best metric. Though revenue does not definitively tell you if you’re making profit on those ads, you could infer that considerable revenue is being made on that ad, so you could continue to invest in that ad.
  • -Con – Just because revenue appears to be trending in a positive direction does not mean you are also producing a profit. By not considering your margin and cost of goods sold, you could be misled into investing in ad that is not producing profit.
• Conversions:
  • -Pro – Allows you to see which ads were involved in the highest number of conversions. This may shed light on top of the funnel types of ads that generally do not receive conversion credit, and this can help expose the type of value they have to the success of other ads.
  • -Con – Since all conversions are not created equal, it’s difficult to understand what impact any ad is having according to conversions on the bottom line. It is nearly impossible to perform accurate attribution with only this metric at your disposal.

As a follow-up, ask the vendor how they calculate profit. In order to be truly accurate, they should be incorporating your cost of goods sold and cost of advertising into their calculation.