"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Shashi Upadhyay, CEO at Lattice Engines.
For the past 15 years I’ve worked with marketers from Fortune 500 companies who are trying to get their hands around the increasing amount of data that is flooding into their databases.
Repeatedly the question I get is: How in the world can I manage all of this data and actually use it to make smarter decisions for my company?
No matter how experienced or intelligent they are, marketers struggle to figure out how to best consolidate data and use it to drive real value for their companies. The problem is that data solutions are not one-size-fits-all, especially for enterprises. Companies must move away from the status quo to leverage data successfully.
This may sound counterintuitive, but hear me out. While it is helpful for the marketing lead to have prior marketing experience, I believe it is critical that they have a data-based background. Whether that’s an undergraduate degree in robotics or previous experience running a data-focused team, marketing leaders today need to feel comfortable analyzing numbers to drive imaginative campaigns.
All successful marketing programs brim with creativity, but we’ve now hit the point where all programs need to be infused with data as well. Marketing is becoming a revenue center, rather than a cost center, and the only way it will work effectively is if teams are sending the right message, to the right prospect, at the right time.
Since using data is the only way to ensure marketers are talking to the right prospects for their company, a data scientist should be leading the charge and helping marketing teams craft targeted, personalized campaigns.
What They Bring To The Table
Data scientists bring many advantages to marketing teams. They know, for example, how to determine which data matters most.
Just because you have the data doesn’t mean it will make a difference in your marketing output. Companies need to first identify their business priorities and then a data scientist should map out what data they need to achieve success. In some cases, a data scientist will need to deploy new technologies to better use the data they are collecting, while in other instances, they’ll just need to integrate the systems already in place so that all the data resides together, rather than in silos. Once the data sets are organized, teams will have the ability to analyze data, gain insights and take action.
Data scientists are naturally programmed to infuse data in everything that they do. Data can’t just be used for the programmatic work. Data needs to be intrinsic to the entire marketing operation, starting from the hiring process through performance reviews and all the way to project performance and revenue impact. Data scientists think in numbers so they will naturally attach quantifiable measurements to tactical actions, making data a critical piece of the company’s business.
What’s more, because the marketing department interacts with so many other departments, infusing data here can start a movement that will help the entire organization become data-driven.
Google is a perfect example of this level of data analysis and action. When the company realized it was losing female employees, quants crunched the numbers and realized its maternity policy was a major culprit. By depending on the data instead of anecdotal evidence, Google adjusted its policy to give employees five months of maternity leave, which dramatically decreased the number of women who voluntarily left.
Addressing The Skills Gap
The STEM (science, technology, engineering and mathematics) skills gap facing us today is frightening, and it could get worse as recent reports show an overall drop in middle school math scores across the country. This means the companies willing to invest additional resources in those candidates that demonstrate both a knowledge and passion for data will come out on top.
Putting a data scientist in charge of a marketing team is an important step toward fighting the STEM skills gap. With a small pool of STEM job candidates, current employees need to be educated in data-driven practices to fill the gap. A data scientist can teach by example, showing their team members the ins and outs of data strategy and encouraging future leaders to cultivate the STEM skills needed to drive highly targeted campaigns.
Furthermore, a data scientist will be the most effective at communicating the marketing department’s needs to CTOs and CIOs, who are generally revered as the resident STEM experts.
Now don’t get me wrong: I believe traditional marketers have important skills and creative visions to bring to the table. However, without a data scientist to direct efforts toward the right customers at the right time, marketing campaigns will have significantly less positive impact on their company’s bottom line.