Data is overwhelming.
Let’s face it. Most Marketers didn’t learn about using today’s overflow of data in business school. They’re playing a game of catch up. Marketing leaders are looking to a new marketing role to help them produce actionable data that they can turn into profitable campaigns and customer relationships. The Data Scientist has emerged as this new critical role in the marketing department.
These hard-to-find people can be your tour guides through the complexities of data. They combine computer science, statistics, math, and business skills with creative problem solving and understandable communication to help you make marketing sense of all that data.
Data Scientist (in its current sense) is a relatively new term, first coined in 2008 by D.L. Patil and Jeff Hammerbacher, then data analytic leads at LinkedIn and Facebook, respectively. The Harvard Business Review describes Data Scientists as those who “make discoveries while swimming in data” and who move decision makers “from ad hoc analysis to ongoing conversations with the data.”
While these professionals are exceedingly valuable, they also are equally rare. The McKinsey Global Institute predicted “by 2018 the United States could face a shortage of between 140,000 to 190,000 people with deep analytical skills, as well as a shortage of 1.5 million managers and analysts who know how to use the analysis of Big Data to make effective decisions.”
A survey by Robert Half Technology concurs, suggesting that “most companies aren’t maximizing their data collection and don’t have the people in place to do so.”
Marketing and analytics are merging in the C Suite too, with CMO’s increasingly aligned with their CIO’s. In 2012 only 36% of CMOs said their CIO was a critical partner; by 2014, that percentage grew to 51%. New titles also are showing up in the C Suite, such as Chief Analytics Officer or Chief Data Scientist.
There is urgency too. Forrester Analytics’ State of Customer Analytics 2014 report concluded that analytics is no longer an option, but a necessity for any organization to compete. Every organization in every industry needs a senior-level data specialist on their marketing team. Period.
The Skills & Benefits
Data Scientists are today’s renaissance Marketers – with expertise in a diverse collection of areas, each with a positive impact on marketing initiatives. If you are searching for a Data Scientist to work with your marketing team, below are four areas of expertise for which you should be looking and also a description of why they are important skills for a Marketing Data Scientist.
1. COMPUTER SCIENCE
Programming – Data Scientists know programming languages. Not just Excel or a Graphical User Interface like SAS or SPSS, but higher level programming languages like Python, R, Java or C++, along with lower level languages that talk directly to the computer, such C and Fortran.
Marketing benefits: These programming languages can build software or processes for automated recurring initiatives or quick-hit internal analyses. Some of the code also can be “self-learning”. Over time, the programs collect new data and get more accurate on their own, without human intervention. Initial results will be the lowest you will get — the results keep improving. No need for another big project.
Systems – Data Scientists know data warehouse architecture. They know how to design the systems that house data for most efficient data access and answering business questions. As data becomes too large to handle on a laptop or desktop computer, warehouse-building skills become important.
Marketing benefit: When architected correctly, these systems permit analysts to quickly find solutions to marketer’s business questions. No waiting for a week to learn an answer – the right data architecture cuts your wait down to a few hours or less. That quick analysis turnaround permits marketers to reduce the time they need to take action and increase speed to ROI.
2. APPLIED MATHEMATICS
Computational Linear Algebra/Matrix Algebra – Many statistical or machine learning algorithms utilize matrix algebra to produce a solution. A well-trained Data Scientist will understand this mathematics and not only be able to program existing methods for data analysis, but also manipulate the theoretical foundations to fit the problem being solved. Most variables or fields have missing values when working with Big Data. Because this is so common, sparsity or sparse matrices might be used to save computational time. Algebraic geometry makes it possible to express geometric representation of data in multiple dimensions.
Marketing benefit: Life is not linear. Complex problems require that marketers assess the impact of multiple variables at the same time to help determine the correct answer. The ability of the Data Scientist to capture and assess the impact of all these different factors on your business helps marketers create solutions that will perform well in a complex marketplace.
Applied Statistics – Statistics has evolved with the exponential growth in the volume of data. Assumptions that worked even 20 years ago, do not apply with massive datasets. Today’s Data Scientists use statistics in a more predictive way, to determine the accuracy of an analytic solution against new or holdout data. Modern techniques would include regularization, online computational statistics and other methods for analyzing and modeling Big Data effectively and efficiently.
Marketing benefit: The growth of Big Data provides marketers with great opportunity and great challenge. The larger and more varied the data sets, the more complex the potential combinations. Some will drive success, while others will influence failure. Out of all those variations, which will work for a particular customer? This is where applied statistics helps – evaluating individual customer patterns and recommending combinations that will optimize customer behavior – whether retention, increased cross-sell or other behavior.
Domain Expertise – Data Scientists speak business talk. They can translate all the analytic mumbo jumbo into concepts and theories that non-analytic marketers can understand. They recognize that a given business question exists inside the context of a given company and industry, and the nuances of those outside influences play on the technical work of solving the business problem.
Marketing benefit: A Data Scientist with domain knowledge can be a true partner with Marketing. When analyzing or modeling data, there are many small decisions that must be made to develop an optimal recommendation. The deeper the business knowledge of Data Scientists, the more likely they will adjust the solution to the unique characteristics of a particular marketplace. The net results are recommendations that perform better for longer periods of time, as well as a deep and fruitful relationship between Analyst and Marketer.
A Data Scientist addition to your Marketing team creates possibilities for new insights, measureable initiatives, and a less stressful relationship with data. If you don’t have budget to hire, or can’t find a person with the necessary skill set, small and large consulting firms can give you the benefit of having a Data Scientist on your team, without having to add headcount.
The days of Marketing as a “Creatives Only” fraternity are over. Today’s Marketers need a data translator to help question, discover, interpret and ultimately succeed, in today’s data world. The era of Data Scientists is here.