According to eMarketer principal analyst Nicole Perrin, “The advances in marketing technology, including techniques like machine learning, don’t mean marketers can just collect data and have a computer tell them what media to buy and how. Data scientists play a big role in setting data-driven strategies, and we’ve heard for a while that big, rich tech companies have snapped up a lot of the top talent.
"But as advanced attribution techniques become more common, roles throughout the marketing department will require competence in understanding and manipulating data. Digital strategists should be educating themselves and their teams and becoming conversant in the types of data they collect and the models that data informs.”
Aside from talent issues, a few other challenges prevent marketers from investing more in data science. Nearly half of the US brand advertisers and agencies surveyed by Advertiser Perceptions and MiQ said that investing in data science is cost-prohibitive. And a Burtch Works study found that mid-level data scientists have a median salary of about $130,000.
A similar number of respondents reported that a lack of accurate measures of business impacts restricts their data science investments.