Companies rely on marketing attribution to determine which marketing channels have contributed directly or indirectly to a conversion goal (attribution). It is both about the justification of the expenditure and the improvement of the customer journey in the multichannel marketing mix. Interestingly, even though aware of the importance of attribution, less than a third of businesses rely on marketing attribution as an analysis method when running campaigns.
According to a January 2017 survey from email marketing software provider GetResponse, at least around two-thirds of email marketers worldwide use email automation, but more advanced automation techniques are not as popular. Email automation is a robust, seasoned marketing tactic, the company highlights, which is why marketers are using it not only to inform customers about company news, offers and promotions, but also for customer onboarding and to ask for feedback. When it comes to enhancing email with more advanced automation techniques, however, marketers are not as far along. Only a third of email marketers used automation for basic profile-based targeting or targeting email content based on individual personas and behaviors. Even fewer, namely just over a quarter, used it for personalization through dynamic content, or content that changes depending on who opens an email and when it is opened.
“It’s not that marketers don’t want to use these techniques”, eMarketer analyst Nicole Perrin explains. “They do. The challenge is that for most marketers, the tech stack is not fully integrated, and the customer data that would make it possible to create dynamic content or engage in profile-based targeting is still heavily siloed’, she said, adding that they could be doing more if their stack were integrated, or if their data were in a single platform.
The report of AdRoll mentioned last week actually came to a similar conclusion, revealing that only one out of three marketers knows how to deal with their data and pointing out that the collection of data isn’t really the challenge, but the selection of the relevant data sets.
AdRoll cuts right to the chase by explaining: “At one end of the attribution spectrum there are the simplest models familiar to many marketers, such as first- and last- click attribution, but to add the appropriate sophistication to a model, marketers need to think about the actual customer life cycle, pull in the appropriate data and understand the kinds of marketing touchpoints that are predictive of conversion. At the other end of the spectrum, there are machine driven models which utilize artificial intelligence built on complex algorithms. These models look at the impact of the marketing touchpoints and enable business analysts to run the statistical analysis based on actual conversion events. However. all these models are ultimately subjective, but all are better than no model at all.” Not to mention that there is no one algorithm that solves the problem, instead, you need to keep applying different algorithms until you get the best answer for the problem you are trying to solve.
Considering these facts, you should constantly work on improving your analytical skills and allocate an appropriate budget to deploy marketing attribution efficiently, don’t you think?
By Daniela La Marca