For being such a tiny word, “big” can breed various reactions depending on the other utterances with which we couple it. It is very rewarding, for example, to achieve a big break, hit the big time and be the big woman or man on campus, but it can also be pretty upsetting to hear we have a big mouth or head, or have become too big for our britches. While we can evenly divide those expressions into positives and negatives, we might find ourselves struggling to know how to tab big data.
Compelling to some, yet confounding to others, the term has become an intriguing topic for businesses that are looking to execute direct marketing programs. Needing to align themselves with companies and specialists who see big data as a vast playground of possibilities, said enterprises have a number of options when considering what the outcome of their information will be. Print+Promo connected with Stephen Yu, president and chief consultant for Willow Data Strategy LLC, Old Tappan, N.J.; Sarah Mannone, executive vice president of Trekk, Rockford, Ill.; and Denis Aumiller, creative/managing partner for Lehigh Mining & Navigation, Bethlehem, Pa.; to gauge the best course of action for those who wish to make a big splash.
Many terms can raise one’s anxiety level, such as “doctor’s visit,” “tax season” and “loan payment.” Has “big data” become such a term for marketers?
Stephen Yu: For some, yes. For early adopters, even the term “big data” sounds uncool. Advanced users moved way past the old definition of big data. The hype factor is dying down for sure, as the word “big” is misleading in a way that data in large quantity will solve problems on their own. But people began to see that this data business is far more complex than just emphasizing the size and speed.
Sarah Mannone: I don’t know that it has. Most marketers I talk to are excited about the possibility of being more data-driven because it means better results. The concerns that arise when we talk about using data to inform our marketing usually have to do with data security and data privacy—and those are rightly major concerns. Data collection should be done transparently, and analysis should be done by people who are trained to understand fallacies and biases. I think the reason many marketers are hesitant to allow more data into their practice is that they feel ill-equipped, just as the average person may feel ill-equipped to handle tax season. The answer is not to ignore it; the answer is to show up with curiosity and learn as much as we can.
What about big data compels you to be such a thorough student of its possibilities?
SY: I believe in the power of data because I have helped my business and my clients using data for over 30 years. I know it is not some hype; when done properly, data do reveal new patterns and free us from wrong assumptions leading to a wrong path. Analytics—the key activity of making sense of data—provides answers to our questions in unambiguous ways. What is not to like? If businesspeople still have doubts about data and analytics, well, lots of luck to them. Their gut feelings will not be enough when others are employing advanced analytics using big and small data all the time. That would be like insisting [on] running on a NASCAR track to beat race cars.
SM: Better data means a higher likelihood of connecting the company that has the solution with the company or consumer searching for that solution. It’s a win/win for everyone involved—no consumer likes to receive a badly targeted ad, but receiving a message that feels tailored to me with just the information I was looking for? That actually feels a little magical, and it can be the start of a great customer relationship. What excites us about data is that we can use it to spot trends, to predict likelihoods and to create more of those magical experiences.
Denis Aumiller: Economics. Using big (marketing) data enables us to be quicker-to-market. This efficiency turns into a competitive advantage for us, as well as those with whom we work.
Where are marketers succeeding with their analysis of information, and where might they be falling short?
SY: Most companies with any online presence are also into digital analytics. They know where the clicks and conversions come from, and they know how leading indicators fluctuate. Where they fall short often is not getting over with channel, product and division-centric point of view. Yes, they do know what is happening on their web and mobile sites, but can they see how one customer is jumping in and out of each channel? Do they understand the true value of a customer, not just in forms of clicks and product views?
This whole big data movement is moving toward customer experience based on personalization via all available channels, and the first step toward such advanced personalization is having the view of each customer regardless of channel, product and division.
SM: When looking at large data sets, it can be easy to make assumptions, and then to rely on those assumptions and base decisions on them. My advice is to test, test, test. Approach every marketing program using the scientific method: the conclusion you drew from the data is simply your hypothesis, and it’s up to you to either prove it or pivot. Don’t think that just because you have access to more data, your programs are automatically going to be perfect.
Which elements of big data gathering and implementing are the most important to marketers in 2018?
SY: Customer experience is not just about having all the buttons on the website working properly and a search engine yielding good results. It is about anticipating what the customers need before they even expressed interests in certain products.
That kind of personalization requires lots of data and analytics work, but in this day and age, all is possible. It is not being done properly, as marketers do not commit to it (though everyone is saying personalization is important), or even if they want to do it, they just don’t know how to convert data sitting on a big platform into usable intelligence (in forms of segments and personas). They really need to talk to a professional when they are just sitting on piles of data, not using them properly. It is like calling an architect and a construction company when building an office complex out of piles of raw materials. Data work requires [the] same type of commitment and expertise.
SM: Data security. If you’re asking your customers for data, you’d better be prepared to take care of that data. We’ve seen some major breaches in the last few years, and the average consumer is rightly starting to wise up about sharing information indiscriminately. Consider what it would take to be worth the trust your customers place in you—and then do that.
DA: Big data brings big success; however, there are noteworthy downsides. Increased problems related to security and vulnerability issues, for example, are major concerns (and are likely, we believe, to continue to be, well beyond 2018). As organizations like LinkedIn, Target, JPMorgan and even Chipotle learned, even a minor breach can have major implications. In our role of providing leading-edge PR counsel, we advise clients on this reputational risk all the time.
Is big data still an elephant in the room, or have companies realized that addressing it bit by bit instead of striving to hit a home run each time will yield better returns on investment?
SY: No serious players use words like “big data” anymore anyway—as many found out that it was just a buzzword, and too many players made empty promises about that. That said, what analytics consultants and service providers must do didn’t really change much. Analysts always have to deal with ambiguities and incomplete information. Our job is to make the most of available data, regardless of our client’s level of understanding in data and analytics. That is why I always start the work by asking their ultimate goals, current challenges and conditions of available data. This whole data stuff is about solving business problems, either for increasing revenue or decreasing costs. Yes, some may come to an analytics company demanding some specific model implementation. But I always start with a defining goal and problem statement. No analyst should build some fancy algorithm just because someone is willing to pay for it. The solution must lead to tangible business results.
DA: Our larger clients exhibit a comfort level with big data that is indicative of its growing importance over the past 15 years or so. We deliver on their expectation that available marketing data will inform our plans for all the services we offer: branding, marketing, advertising, positioning, content creation and PR.
Likewise, we commit to demonstrating results using metrics, as well. Delivering detailed ROI results on an ongoing basis is a key role of each of our account representatives.
What is the future of big data? Are companies such as yours likely to find themselves inundated with larger projects, or do you envision clients desiring truncated projects?
SY: Big data should never be the goal in itself anyway. It should never have been. If there are lots of data, and they move really fast, will they just solve problems for us? Not in a million years. Then how do we make differences in the real world? We must start with data strategy sessions, provided with clear business objectives.
I would suggest taking a phased approach, where small goals of each phase serve as building blocks toward larger, long-term goals. So, yes, if we get to have access to the whole thing, it becomes a big project. But I don’t believe in such things. Analysts must act like doctors, and doctors should not operate on some patient to increase billing. Analysts must have the same attitude; they should do as much as the goal calls for.
It’s a fine balance these days, as budgets are often executed by small divisions in a company, so top-level data strategy sessions do not happen without the involvement of C-level executives. Regardless, consultants should be aware of the whole landscape.
I’d say the answer depends on the commitment level of a company regarding data and analytics, not technology or capability. And there is no one correct answer in terms of how we’d go about it. But the consultant must be thinking about all surrounding elements.
DA: “Big data” is [not] going [any]where, although it may, we believe, undergo a rebranding. “Big” is a notion of size alone, a descriptor that implies only that there’s a lot of it. We see the concept morphing into something more akin to actionable data. Or usable data. Or relevant data. It’s likely to continue to increase in size, but the accent will shift to its usefulness, not its mere vastness.
We at LM&N see not so much an effect on the size of marketing-branding-PR projects that come our way. Instead, we see an increased call for us to leverage our data skills to better collaborate and cross-pollinate within our clients’ internal and external customers. Our comfort level in that ability is leading to greater success for those who enlist our help.