The United States is far and away the largest advertising market in the world. In 2016, more than 190 billion dollars went into advertising in the U.S., twice what went into reaching consumers in China, the next largest market.
TV ads have always been far and away the biggest earmark for those advertising dollars, but when all the numbers are finally tallied for 2017, it looks like TV will finally be giving up the number one slot to digital ad buys.
There’s a reason for that change, beyond just the general migration of consumer attention to internet destinations and away from television. TV still takes more attention from the American public than websites, an average of 164 minutes per day per person. Internet content is gaining fast though, clocking in at 157 minutes per day, but it offers marketing professionals something that television doesn’t: solid, quantifiable metrics.
Websites track every page view, every click, every consumer comment, and even which websites users go to next after all those views, clicks and comments are made. Major social media providers like Facebook and Google know exactly what products people search for, when they search for them, and how much time they spend shopping for and vetting a product before actually adding it – or another product – to the cart. That wealth of information is solid gold for marketers.
Marketing is more than just advertising, of course. It can impact product development, branding exercises, pricing, and a million other factors that go into the sales process. Exposure to brand elements, trending hashtags on social media, personal income, and location can all factor into buying decisions.
While marketing was once a guessing game aimed at trying to predict what consumers want, and when they want it bad enough to actually buy it, today the data needed to answer those questions is all there for the taking, sitting in vast, chilled data centers just waiting for an intelligent algorithm to extract it. Master’s-educated marketing analytics professionals will be the ones businesses call on to interpret that data and provide the answers.
Big Data Uncovers The Black Arts of Marketing
John Wanamaker was the 35th Postmaster General of the United States. But before that, he was a department store magnate in Philadelphia who gained immortality in the advertising industry with a famous and apparently timeless observation about his marketing spending.
“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”
It will probably astound future generations of marketing professionals that so much money was spent on marketing for so long without any proof whatsoever that it had an effect on consumers. Marketing is a complex business and measuring the effects of ad campaigns, branding, and other strategies has been notoriously difficult for decades.
That complexity is exactly what makes data science the right tool for the job, capable of aligning consumers with the right product at the right price point, and then measuring the effect.
The business of weighing and measuring hundreds of subtle and interwoven variables is exactly what marketing analytics pros are trained to do. They have the tools and expertise required to derive quantitative results from advertising dollars spent, and the ability to present business execs with a crystal clear picture of exactly how big a bang they got for their buck.
In 2016, the Advertising Research Foundation published a research study based on 12 years worth of data that finally offered definitive proof that advertising worked. Up to that point, many individual campaigns could be proven effective in terms of spending to revenues, but it was often impossible to quantify why or how they were working… or, critically, to duplicate their success.
This was illustrated by a 2011 study suggested that approximately half of all advertising is ineffective. Market saturation has made mass market advertising decreasingly effective as younger generations have effectively learned to tune out ad campaigns the more they’re exposed to them. When ad content exceeds approximately 30 percent of the media stream, consumers tune out.
This is a big problem for both marketers and advertising companies. The Economist points out that massive profits are baked into current market assumptions for advertising companies, but the diminishing returns that modern audiences have shown don’t line up with the expected profits. This has led to a knife-fight among marketing agencies competing for slices of an oversold pie of ad dollars. Marketing analytics is proving to be key to coming away from this fight a winner.
Marketing Analytics Offers a Solution in the Form of Evidence-based Advertising
Evidence-based advertising may represent the future, and it will be marketing analytics that businesses rely on to deliver that evidence.
Many studies of marketing efforts show positive effects, yet duplicating those campaigns rarely, if ever, duplicates the results. The conditions for success often depend on variables that conventional marketing professionals can’t anticipate or quantify, including:
- Timeliness
- Cultural affect
- Novelty
- Nature of the product
- Target audience
But big data offers some of the tools for gauging those hard-to-measure variables.
Marketing Analytics Brings Together Disparate Data Sets For Sales Results
Marketing analytics professionals tap into corporate databases using SQL and other languages to pull out data about sales. They also create marketing databases, accumulating as much information about customers and potential customers as possible. These are often integrated with public data stores, such as address and telephone directories, as well as specialized marketing databases kept by companies like Acxiom, which take in as much data as possible about individuals in order to build detailed profiles for advertising purposes.
Because findings have to be translated into reports that business executives and marketers can easily grasp and use, visualization and storytelling are valuable parts of marketing analytics. Tableau is a popular tool for both analysis and visualization.
Marketing analytics also involves tracking larger trends, which can involve sifting economic data at the local, regional, or even global levels. Analyzing competing firms and products is also frequently part of the work. There’s a lot of creativity required in finding the right data sets and weaving them together in ways that are useful. The more education you can get in the field, the more relevant your results will be.
How to Select the Right Marketing Analytics Master’s Program
If you plan to invest in a master’s degree in marketing analytics, you’ll want to make sure you are putting your time and energy into a program that will give you the skills you will need as well as the contacts that will help your career thrive.
You might want to look for programs that have industry partnerships with big names in data science. The Robert H. Smith School of Business Master of Science in Marketing Analytics, for example, notes high-caliber internships available with companies like:
- Amazon
- IBM
- Deloitte
- Merkle
But big tech companies are not necessarily the only places you can get solid experience in big data marketing techniques. Marketing, after all, is a nearly universal function in business today, and some of the companies that are generating big marketing data aren’t necessarily big names in technology or even in data science. Capital One, Chase, Target, Walmart… traditional companies that have massive marketing operations are great places to learn about the applications of data science to marketing processes.
Make no mistake, though, you do need to pick a program that offers strong technical education in analytic procedures. The Smith school promises to teach you technologies like R, Tableau, and Python, for example. You’ll want a program that covers:
- Statistical programming
- Customer and market research and analysis
- Customer relations management systems
- Qualitative and survey research methods
Programs that lean more toward economics or promotional skills, or do not include the technical side of statistical analysis, are probably not a good bet.
Like any master’s degree program in an applied science, it’s a good idea to check the background of instructors teaching the curriculum. The more recently they’ve actually been out working in the industry, the more likely their experiences will be beneficial to your own education. Real-world examples help shape courses to provide pertinent techniques and models of the type of work you’ll really be performing when you graduate. This makes you a lot more attractive to potential employers as well as more confident and capable.
Also improving your value to employers are programs that offer a dual, co-terminal degree, usually an MBA, like the one found at Illinois Institute of Technology. It’s a more difficult progression, but the dual threat of having a strong business education together with advanced analytical skills opens up many career paths that would be unavailable to only one or the other, including corporate executive positions.