4 Ways to Transform Your Marketing In An Analytical World

Transform Your Marketing

Whether you’re in a large business or you’re an entrepreneur, you’ve seen that how products and services are marketed has changed dramatically in the past several years. Our social, mobile, always-on, data-driven, analytical, highly-personalized world is changing at a pace never seen before.

How your message reaches the world is changing as fast as the technology changes. And the role of marketing has shifted, requiring marketers and business leaders not only to understand traditional marketing but also to mine data to make decisions.

Adele Sweetwood has just released a new book, The Analytical Marketer: How to Transform Your Marketing Organization. As Senior Vice President of Global Marketing and Shared Services for SAS, she guides marketing strategy and go-to-market programs. Her research and 30 years of marketing leadership make her the perfect executive to explain the shift in messaging and what to do about it. I recently asked her about the changing nature of marketing and analytics.

 

“If you don’t like change, you’ll like irrelevance even less.” –Eric Shinseki

 

Deliver A Great Customer Experience or Risk Extinction

Data analytics is all the rage in helping executives make decisions. How is it transforming traditional marketing?The Analytical Marketer_Book Jacket

Being a customer-centric business was once the exception, not the rule. Now businesses across all industries need to deliver a great customer experience or risk extinction. Marketing can lead this transition by defining what a meaningful interaction looks like for that business’s consumer. The best marketers today have a keen sense of, and clear focus on, the demands of the customer, through sophisticated analytics and data-driven methodologies. In our digital “always on” world, where we’re continually collecting copious amounts of real-time data about our customers, marketing is in the best position to own and leverage that data to understand and service the customer in ways that weren’t possible before.

 

“It is a capital mistake to theorize before one has data.” –Arthur Conan Doyle

 

Develop Multiple Skills for Success

Since we learn that a numbers-orientation is left brain whereas creativity is right brain, is it really feasible to be equally skilled at both?

I don’t believe anyone is exclusively left-brained or right-brained. Being more analytically-oriented or more creative can certainly be innate in someone, but with training, new skills can be learned and developed. Marketers have traditionally worn many hats, so flexibility has been a long-standing component of the job. While a member of my team may not need to tap into her entire skillset every day, she absolutely needs a wide variety of skills that include analytics, social media, storytelling, and creativity to be successful.

 

You say that marketing is traditionally reactive: Launch, wait, try again. What’s changing?

The reactive approach to marketing simply doesn’t fit into a customer-centered business culture. Marketing now is more about science or math that is driven by an influx of data, channels, mobility, and, most importantly, changing customer demands. Analytics is driving campaigns. As a marketing department, that means leaning more on the work of folks who help analyze behavioral data and the digital footprint of our customers and prospects.

In fact, some of the most interesting work within our marketing department at SAS comes from those focused on data forensics. This is the practice of using data discovery to establish the facts of a marketing activity, a campaign, or a broader initiative. But beyond the basics of data digging, data forensics incorporates intangibles. They are the piecing together of anecdotal and qualitative tidbits along with quantitative data to develop a rich picture of what is working and what isn’t. With that data and analysis, we’re creating campaigns that are more focused on where customers are in their decision journey and what they are looking for. We’re not blasting an email campaign and waiting for results – we’re a step ahead.

 

“Data beats emotions.” –Sean Rad

 

Common Challenges

As you talk with marketing leaders across different fields, what are some of the common challenges they are facing?

The Promise of Big Data

The Promise of Big Data

Big data not only has the potential to usher in change, but it is already revolutionizing whole industries. Companies are collecting and utilizing data in ways that most of us are just beginning to understand. Some of us have followed stories of social media companies and how they use data. But it’s beyond that now. Televisions have been created that capture what you are saying. Flashlight apps on our phones have accessed your data. On the other hand, some companies have used data to make our lives easier and personalize our experience.

In Matters of Life and Data, Charles D. Morgan takes you on his personal journey from humble beginnings to CEO of First Orion Corp. He serves on numerous boards and notably was the CEO of Acxiom Corporation from 1972 to 2008. Recently, I had the opportunity to talk with him about his new memoir and his experience in the world of big data.

 

Warning: A flashlight phone app may access the data on your phone.

 

The Benefits of Big Data

Using Data Science to Transform Information into Insight

3 Facts I Bet You Didn’t Know about Data Science and Scientists:

 

  1. Data scientists are not mystical practitioners of magical arts.
  2. Data scientists are “sexy” according to a recent Harvard Business Review article.
  3. Data science can “call presidential races, reveal more about your buying habits than you’d dare tell your mother, and predict just how many years those chili cheese burritos have been shaving off your life.”

I learned these facts minutes after picking up John Foreman’s new book Data Smart: Using Data Science to Transform Information into Insight.  Data Smart is the textbook for anyone wanting to turn raw data into action that makes a difference.

John is the Chief Data Scientist for MailChimp.com, the email service powering subscriptions marketing campaigns.  MailChimp also powers blogs like this one, allowing you to sign up and receive blog posts in your inbox.  John has also worked with a range of organizations from the FBI and Department of Defense to global corporations including Coca-Cola and Intercontinental Hotels.  You can follow him on Twitter @John4man.

Data Smart by John ForemanJohn, who did you write this book for?

I wrote Data Smart for anyone who wants to learn the cutting edge analytic techniques that businesses like Amazon and Facebook are using to turn their data into revenue.

And when I say “learn,” I don’t mean just “learn about.” In Data Smart, readers use actual techniques, such as artificial intelligence and data mining, to solve real business problems. That way the reader can get a sense of how to apply them to their own work. Think of the book as on-the-job training.

That’s why each chapter works through a data science technique in Excel – spreadsheets are a safe environment that readers feel comfortable working and following along in.

He who would search for pearls must dive below. -John Dryden

I wrote Data Smart for anyone from business intelligence analysts to programmers to quantitative marketers to sports analysts to C suite executives. For anyone who truly wants to learn analytics, this is the most accessible book for gaining a foothold in the discipline.

Misconceptions about Data Science

Give us your definition of data science.  What’s the biggest misconception people have about your field?

Data science is the use of transactional business data (think sales data, website traffic, social interactions, ad conversion data, employee performance data, etc.) to make decisions that result in revenue growth for the business.

There are a few big misconceptions about data science. First, the field isn’t just for those who do online advertising (e.g. Facebook, Twitter, or Google). No, a brick and mortar mom-and-pop shop can benefit from artificial intelligence models too. For instance, if you run a hotel, being able to forecast demand in light of your prices and competitors’ prices is invaluable. And that’s true whether you’re a single hotel or Intercontinental.

Second, you don’t need a Ph.D. to do data science. Some of these techniques, like customer segment detection, are analytically tough, but anyone with the motivation and some spreadsheet skills can learn how to do it.

The Surprising Predictive Power of Analytics

You have been predicted.

Companies, government, universities, law enforcement.  All are using computers to predict what you will do.

Will you click on the link in the email?

When will you die?

Will you pay your credit card bill on time?

Are you pregnant?

Dr. Eric Siegel recently released Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die. It’s a fascinating book that has surprisingly broad ramifications for all of us. Eric is a former Columbia University professor, the founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times.

Let’s start with the definition. What is predictive analytics?

It’s technology that gives organizations the power not only to predict the future, but to influence it. The shortest definition of predictive analytics is my book’s subtitle, the power to predict who will click, buy, lie, or die. Predictive analytics is the technology that learns from data to make predictions about what each individual will do–from thriving and donating to stealing and crashing your car. By doing so, organizations boost the success of marketing, auditing, law-enforcing, medically treating, educating, and even running a political campaign for president.book_med_2

Why should the average person care about predictive analytics?

Prediction is the key to driving improved decisions, guiding millions of per-person actions. For healthcare, this saves lives. For law enforcement, it fights crime. For business, it decreases risk, lowers cost, improves customer service, and decreases unwanted postal mail and spam. It was a contributing factor to the reelection of the U.S. president.

Let’s jump to politics then. How did President Obama’s campaign gain an edge by using persuasion modeling?

The Obama campaign’s analytics team applied persuasion modeling (aka uplift modeling) in the same way it can be applied to marketing: drive per-person (voter/customer) campaign decisions by way of per-person predictions. If an individual is predicted to be persuadable, then make campaign contact (e.g., a knock on the door). By utilizing resources (campaign volunteers) more effectively in this way, the campaign enacted the new science of mass persuasion. They proved this won them more votes, within swing states and elsewhere.

Everyone is talking about “big data” but data on its own isn’t interesting or useful. You explain how data can show incredibly interesting insights including the fact that if you retire early, your life expectancy drops. Tell me more about that and what else we’ve learned from it.

Beyond the great hype around so much data, the real question is what to do with it. Answer: use data to predict human behavior.

The whole point of data is to learn from it to predict. Talking about how much data there is misses this point. What is the value, the function, the purpose? The one thing that makes the biggest difference to improve how organizations operate is to predict.