Recent years have seen the rise of automated marketing operations, insights, and data analysis. Marketing and Sales organizations are using data from new sources in innovative ways to holistically inform and improve their performance and conversion rates.
These first- and third-party data sources are largely captured and categorized by algorithms augmented by artificial intelligence, natural-language processing, and machine learning.
And contrary to popular fears, the robots haven’t taken over yet, which highlights the reality that there have been business analysts, data scientists, and marketers making sense of these new data streams and intelligence.
In a recent article on martechadvisor.com, author Daniel Raskin predicted that real-time data analysis will become so central to the marketing function that the marketing data scientist profession will emerge and become cemented in the marketing function.
Marketing Data Scientists Abound
Some practitioners consider the marketing data scientist profession to be beyond nascent.
Michael Lock, Aberdeen’s senior vice president of research, argues that the vast majority of an organization’s data processing and analysis is done for the purpose of marketing.
Michael Lock
Whether an organization approaches data science as an art or a discipline, the output is “inextricably linked to marketing,” Lock said.
The business analyst role has existed for decades. Many organizations already structure that position within the marketing function because business analysts (who Lock figures are branding themselves as data scientists these days) are analyzing data to open up new markets, determine which products are worth developing, and predict how products will perform and which features will resonate with users.
The work business analysts and data scientists do now is “inherently marketing-driven the vast majority of the time,” Lock said.
The idea of the emerging marketing data scientist role isn’t so much a question of “is there a future in it?” he said, but instead, an argument of “how much of the present is already taken up by data science applied toward marketing purposes — and my sense is that a lot of it is.”
Data Science vs. Marketing Data Science
As for the future of the data scientist role, there will be times when the job isn’t tied into marketing.
At organizations such as manufacturers who deliver unfinished or partially finished goods to other manufacturers, their marketing efforts are not high on the list of organizational priorities. At such an outfit, data scientists will continue to focus on optimizing the product supply chain and new product development process.
At high-tech giants like Oracle, IBM, SAP, or Microsoft, the ability to identify new customers and sell to them is core to the business model, and that responsibility falls under the purview of marketing. So, the majority of their data science efforts are going to be tied to marketing.
“Those companies are gigantic marketing machines,” Lock said. “For any organization that has a significant portion of their budget tied to marketing, you can bet that a large element of data science is going to be applied to those marketing efforts.”
Smaller organizations that lack a current budget allocation for data science need not fret, because user-friendly business intelligence and analytics solutions have proliferated the market.
Rather than trying to hire an expensive data science resource, small- and mid-sized businesses can instead invest in tech that can give “citizen data scientists” the ability to search and identify correlations and buyer intent in their data, Lock said.
The Future of the Marketing Data Scientist
According to Lock, the way that data science is evolving is aligning it to be geared towards marketing, to a large extent.
“With the exception of companies that are purely operational, or almost entirely operational (where data science is going to be applied towards the optimization of supply chain management or whatever it might be), it’s going to have a high degree of relevance in marketing. The connection between the two isn’t going anywhere,” Lock said.
The future of the marketing data scientist may be nothing more than a more accurate title.
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