In the week leading up to the Facebook IPO, news broke that General Motors was pulling $10 million in display advertising from the world's largest social network due to poor performance. But after digging into the story a little deeper, one thing became clear: There seemed to be an issue with how GM was measuring its display advertising campaign performance.

Making Measurement Make Sense (3MS) has provided principles and solutions to pressing issues of digital measurement standardization. The one that seems to get the most attention is the proposed move from served to viewable ad impressions. The other one that people talk about is GRPs. But the more traction 3MS gets, the more we hear and read a variety of imprecise, even inaccurate stories about what 3MS or the current stage of testing is about.

A key finding of the recently published joint Forrester Consulting/IAB report, "Digital Attribution Comes of Age," was that "algorithmic attribution models are gaining acceptance, but some marketers remain skeptical." Specifically, the report states that algorithmic attribution's supporters say that it is "statistically principled, objective and unbiased," and that "data is setting the weights, not opinions." Meanwhile, detractors of the model say it is "difficult to explain," "opaque," and "subject to 'dangerous math' that can create misleading outcomes. Fortunately the algorithmic approach can be tested both in terms of the outcome and the causality assumptions.

The most recent ARF Audience Measurement conference was titled "The Measurement Crisis." Crisis or not, there were real signs of discord in the industry -- primarily about digital ratings.

Microsoft has announced its intentions to make "Do Not Track" a product default in the upcoming Internet Explorer. In case you haven't been following the story, this means that companies abiding by "Do Not Track" will no longer gather user-specific data from Internet Explorer -- which holds roughly 37% of the US browser market -- unless users explicitly opt in to have their data reported. The marketing community is obviously less than thrilled at the prospect of so much online data going dark, and have strongly urged Microsoft to reconsider.There's been plenty of time for some great thinking to emerge …

Last click, as a measure for the performance of digital media, was king for most of the Internet era. Now that its reign is over, the industry must work together to ensure a streamlined attribution ecosystem. The accurate valuation of media is essential to the health of the digital advertising marketplace, as is a more efficient media planning and buying process. Our industry has the chance to seize the great opportunity of this new era by facing its immense challenges now, in the early stages of its development.

Without indulging your scientific side, and going strictly on your powers of perception, it is clear that we live screen-infused lives. We also live lives filled with multitasking. Some of you may say that observations about people who work in media, marketing, and data are skewed toward multiscreen users and multitaskers -- and you would probably be right. That's why we talk to consumers regularly. We seek their input on what they do, buy, think, feel, and so on. We measure their behaviors, attitudes, beliefs, opinions, shopping habits, and more.

In light of the Facebook IPO and Facebook's plans to sell premium inventory via API, it's worth pausing to take stock of Facebook metrics. It turns out, the metrics on Facebook are an example of a wider growing phenomenon in digital media: the metrics of silos.

I authored a MediaPost article last June that asked the question "Can the Accuracy of Attribution Be Validated?" It examined a number of the most common marketing attribution methodologies of the day, and challenged readers to think about if and how the accuracy of each could be mathematically corroborated. The topic sparked a lot of guesses and a lot of dialogue, both online and in conversations with readers. Given the diversity of opinions, I thought I'd revisit the topic and provide the answer that I withheld in that original piece.

Attribution models have emerged as a powerful tool for helping advertisers understand which parts of their marketing efforts are driving sales. An attribution model works by assigning partial credit to each advertising event that influenced a user to convert, and can generally be separated into simple models and advanced models. Simple attribution models use predetermined weights to assign credit to each ad, while advanced attribution models use a more scientific approach.