As marketers, we live and breathe metrics, particularly those related to ROI. After all, a campaign is only as successful as the net profits it brings in for a company.
So I know that when the recent study from Tata Consulting Services found that 1 in 5 large consumer companies are actually losing money on social media many wondered: is social media marketing really producing results for clients or just sucking valuable resources?
This question is a complicated one. In fact, the study itself reveals that. Almost half – 44% of the respondents – aren’t even taking steps to measure social media’s value. And I’d argue that it’s likely that the 1 in 5 figure isn’t entirely accurate. (It should also be noted that twice as many respondents reported a positive ROI.)
The trouble is that social media is hard to measure, and we may not be measuring it in the right way. Current attribution models poorly represent the influence of social media on the buying or decision-making process.
The real influence of social media is hard to quantify, because there is an intangible effect that is more psychological than analytical. In a way, this is similar to more traditional forms of marketing, such as TV, radio, and magazine ads. After all, you can’t count the number of people who clipped out a magazine ad or purchased a soda after watching a TV ad. Instead, marketers look for “softer” correlations, in particular consumers’ attitude toward the brand.
Sure, it’s easy to tell who clicked through, reposted, or followed your social media, but this is incredibly reductive, short-shrifting the true value of social media which often boils down to influence. As a result, it’s likely that often attribution models give full credit to a later step in the decision-making process for a sale when social media surely played a role, often an important one.
Therein lies the issue, until we can accurately measure influence in our analytics tools, we are not going to know where to focus the dollars.
Attribution: A New Concept to Many Analytics Professionals
The entire concept of attribution may still be new to many analytics professionals. Online advertising methods like PPC have a more direct and easy-to-identify correlation between behavior and the conversion. A customer clicks through to a landing page and either converts or not.
It may also be, in part, because attribution models available to analytics professionals have been fairly limited historically, but that is changing with Google Analytics’ new custom Attribution Modeling Tool.
Now you can better track an individual’s path to conversion, even if it is made on multiple visits to your site. For instance, someone first gets to your site through a social media update, then later visits through an email campaign, and finally returns again directly to the site and makes a purchase.
Previously, you could choose to give full credit for the conversion to the First or Last Interaction, Last Non-Direct Click, or the Last AdWords Click. Or you could spread the credit (which, in most cases, is more accurate) in a Linear model, which gives each touchpoint equal weight; a Time Decay model, which gives more credit to actions taken closer to the conversion; or a Position Based model, which gives more credit to the first and last interaction.
Each of these models is limited in some way, which is why it can be valuable to compare different models when analyzing marketing efforts effectiveness, and also why the new Custom Models are so valuable. You can choose your set of rules, everything from how far back to look to the amount of credit you apply to the type or order of interactions. The new capability is incredibly complex, which allows analytics professionals to get an even more sophisticated look at what’s really happening and, from there, better allocate marketing dollars.
Of course, even this doesn’t tell the complete picture, particularly about social media, since a truly successful campaign can impact a buyers’ decision-making process without a clickthrough ever taking place directly from the social media account and drive word-of-mouth marketing offline.
So before you throw out your social media marketing strategy because the numbers don’t add up, make sure that you know what you’re really giving up. The value may be more than numerical.