Retail TouchPoints: Does Big Data Have to Be So Big?
Through a special arrangement, presented here for discussion is a summary of a current article from the Retail TouchPoints website.
At the recent Online Media and Marketing Association (OMMA) Data Driven Marketing conference, Julie Bernard, group VP of Consumer Centricity for Direct Marketing and Loyalty at Macy’s, sent a buzz through the crowd by her admission that human judgment still has value at the company, despite data collection and analysis efforts being a priority.
Macy’s executives recently realized that they had enough data to customize print ads, but found it too expensive, she explained. But the retailer also returned to traditional marketing methods for another reason: Executives believed advertising that was "too relevant" might start to be too predictable. Additionally, customers sometimes look at marketing pieces for fashion inspiration. "If it’s too relevant they don’t get it."
Still, the overall message delivered by several retail data executives at the conference was that maybe "Big Data" doesn’t have to be so big. Retailers today need to break Big Data down to create actionable data. In doing so, they can improve multichannel customer experiences.
"Data has become an issue for retailers because mobile and social media lack traditional structure," said Greg Corso, VP of Media Solutions at dunnhumby. "The velocity and volume of those inputs is incredible. It’s all worth nothing if you can’t act on it. Omnichannel attribution has become paramount. Retailers need to spend more time measuring and analyzing online behavior to see how it affects in-store behavior."
Judy Loschen, VP at Epsilon, detailed her work with a retail client that sent unscheduled emails every Thursday. Tied to the weakest weekly product category, e-mail messages were converting for the first three months, but customer churn and unsubscribe rate were leading to diminishing and destructive patterns. The e-mails were stopped. When they were restarted, however, customer value and open rate rebounded.
"Data affects customer messaging relevance and frequency," Ms. Loschen said. "Data is not just a short-term revenue driving tactic. It’s a key factor in long-term strategy."
Discussion Questions
What are the limits to customized marketing approaches? Do consumers ultimately want more varied (less predictable) ads? Does customer data analysis ultimately lead to overly predictable ads?
It’s data—it’s not marketing. If customer data analysis is leading to predictable ads, it’s because the people interpreting data lack imagination. We’ve known for years that predictability in advertising diminishes its impact—that’s why we flight rather than stream ads on TV and Radio and why we change copy on a “regular” basis—to keep attention to the ad and avoid habituation.
There is a strong presumption here about just how “predictable” these targeted ads can be. This presumption is inappropriate and not well-supported by actual data. No matter how “big” the Big Data gets, there will always be a HUGE random component in customer behavior and advertising effectiveness. There will always be room for truly creative advertising that provokes the customer and gets her to think and do things that she wouldn’t have thought/done otherwise.
One of my grave concerns is that many of today’s digital advertising practices (e.g., retargeting) are decidedly uncreative. We need to truly understand and embrace the inherent unpredictability of behavioral responses to advertising, and stop fooling ourselves into thinking that today’s datasets (and computing power) can change this in a major way.
There’s a strategy—let’s see if we can avoid using the human mind, the most brilliantly designed computer in all of creation hyper-connected to both the seen and unseen. Reminds me of the time I did a shamanic venture into the jungles of Brazil where I watched an illiterate penniless Shaman call birds in and out of the compound at will and keep animals away with nothing more than his mind. I was there with a drawer full of degrees and a bunch of published books…and I couldn’t do what he did so effortlessly. So which one of us was the most “intelligent?”
The point is sometimes we are just too smart for our own good not realizing that there is a natural ebb and flow in the energy of the universe that we can totally manage IF we’d stop trying to be so damn clever. Suggesting that people use the unlimited power of the human mind—aka human judgement—created a buzz through that audience? Really?
And of course having too much detail and “customization” will kill a customer relationship. It’s called “smothering.” Sure I like certain things and that gets reflected in my purchases etc. But when some company starts to TELL me what I like and don’t like I get a little pissed. And that happens because you then begin to deny me my humanity and free will. BACK OFF…and give customers room to breathe and grow and see new possibilities. Robots are “predictable.” People are not…in spite of the determination of marketing analysts to turn them into zombies.
What all of these experts are pointing to is the need for marketers to use common sense. There is enough data to barrage consumers, while swamping marketers. Common sense dictates that retailers should follow social media to listen to, learn from and dialogue with consumers. Email is a useful tool, provided that it is used sparingly. There is a place for traditional, broad-brush media.
Today’s marketers are alchemists, constantly blending mixing and experimenting. There no longer are tried and true marketing axioms other than listen to consumers and treat them with respect.
I agree with Peter on the key point of creativity. I expected a series of innovative breakthroughs from ad and marketing agencies, hoping they would to run wild with all the new and different information available to them. It just hasn’t happened yet—they seem to create most if not all of the copy and even design using the same rules as when they just had transaction log, census and perhaps old demographic data to base campaigns on. Maybe we need to bring back three-martini lunches.
Slowly but surely the industry is coming around to the rational point of view on Big Data. Bigness is not a virtue in and of itself. Actionable data is one step closer to the right end goal, because it starts to build in the idea on getting an ROI on data analysis. And here, there is also rightly a Bayesian aspect. Executives must have a deep understanding of how their business works, so that they can rightly assign the right level of belief in what the data is allegedly saying.
Retailers also need to learn that certain methods of analysis create more actionable insights. To take a silly, non-ad example: if I scrape social websites and see lots of customers think I should paint my stores green, so what? Maybe that gives me an hypothesis. But it doesn’t mean there will be ANY return on that investment. If I actually do it in 10 stores and see a statistically significant sales lift big enough to justify the investment, that is much more actionable. And then, if I can use lots of data (dare I say Big Data?) to sort out which stores or customers show the greatest incremental lift, then I can further target the investment for greater return.
That’s the key. Big Data => cash ROI, not “interesting sounding ideas that seem like they will probably make me money”. Too much of the Big Data space is still in the latter world.
Data is data. Decisions about which data to examine to understand which issues for which reasons will yield information. Understanding that information and its relevance for decision making involves interpretation leading to inspiration. All the data is necessary at the beginning of the process. Intuition is relevant when interpreting the data. There are no shortcuts.
Let’s not get carried away into thinking that the Big Data is going to do all the work. Have you read the book “Blink” by Malcolm Gladwell? Worth the read. See what happens when you rely solely on data.
As for me, I think the biggest play for Big Data is not about marketing. That area is too tricky. I did some research for my sister last week and now I get targeted ads about that stuff every day. Using that data to tell me collectively who my customer is, what they do online and in store, where they linger, what peaks their interest, etc is what can allow me to deliver a better customer experience and improved customer satisfaction.
I agree with everything that’s been said here (and Ian, I love your broad points about the universe). Humans are rational AND emotional, shopping is driven by both sides of that coin. When we focus on one at the expense of the other we lose the complexity of human thought and behavior. As humans we crave engagement, stimulus and novelty. A big data marketing program that becomes staid and predictable undermines all three.
This reminds me of the trend to “test” Hollywood movie endings. Result? Predictable, boring movies where the good guys always win.
Without a doubt, the ability to ‘go with your gut’ and stay instinctively ahead of your customer, regardless of channel, is a missing attribute in retail marketers today. It’s either missing or suppressed—not sure—but in any case, we need more of it.
Mickey Drexler is the last bastion of instincts in the business. Maybe he can impart his wisdom to the rest of us more often and swing the pendulum back to the days where retail marketing was interesting.
Going back to the days when “Knowledge Management” was the buzzy term that “Big Data” is today, reminds us that data is the lowest tier in the hierarchy. The data still needs to be converted into information and then it needs to interact with human intelligence to become knowledge. As the amount of data becomes overwhelming, accessibility and the quality of the presentation layer becomes ever more important.
First, download all the big data. Second, use advanced analytics to find some actionable insights. Third, send relevant offers to people who already kinda behave the way you want them to, using social media. Next …
Hold on there—are you still waiting for that download to finish?
Oh yeah, did I mention that big data expands faster than you can chase it? In both volume and velocity. That means the more you pursue it, the more behind you get.
Evidently some new thinking is needed in a big data world. Sure we can watch the flows, and automate some of our communications. But relentless robot messaging doesn’t win hearts and minds, it just anesthetizes them.
My gripe is not that ads are predictable, but that they are transparently obvious. When I look up a health issue on a search engine, and an unrelated ad appears in the sidebar for a software company I track as part of my work, I know exactly what’s in play.
The click engine is stalking me, and it’s too dumb to anticipate that I might find that creepy or unwelcome—the exact opposite of what the marketers hope.
Now if you’ll excuse me, I have to put my foil helmet back on…
The issue that’s not discussed here is that the data you can gather rarely matches well with the data you need in order to get the important decisions.
We must be careful not to force artificial targeting choices onto our customers merely because “it’s the only data we can find.” I’ve seen too many people choose to target based on the data that’s available rather than a thorough understanding of their target.
Another error in big data is the loss of the slipstream. A VP I worked with observed that the right way to consider targeting is to choose your focus. But also remember that a great many customers come along with you … in the slipstream. Like the leaves that trail behind a truck as it drives by.
Marketing theory about “targeting” is not ironclad—rather helpful focus. It will be a shame if big data creates a hubris that forgets that we don’t, and never will, know everything.
So, of course, instinct is still critical. it always has been and always will be.
The problem with data is that it’s backward looking. Customers are interested in the new and in changes, not the past. Too often, frequent communication just turns the customer off and they stop reading all communications.
Large retailers will never be able to execute one-on-one marketing as it is too expensive. Creating logical groups for new, interesting, informative, and coordinated messages works, but just listing promotions on leftover merchandise will create little excitement.
Lots of data and large sample sizes have little value if the data does not represent all segments of typical customers. Analyzing big non-random data may not produce useful insights.
Marketing is more art than science, and this especially applies to fashion marketing. Anytime you are trying to predict human behavior in the future, you are taking into account assumptions and risks. This becomes difficult, to say the least, when marketing products which appeal to subjective (i.e. non-measurable) components, rather than the 4 basics of marketing (product, price, promotion and place).
We continue to forget that key ingredients such as customer service,which has no measurable, product appeal, retail appeal, consumer state of mind, etc. all play into a purchasing decision, and none of these are quantitative. In advertising, “fresh,” new ads are often the key to better appeal….
Managers and stockholders are best served by spending time on the showroom floor. Look at your customers! Do you have customers? Check out the competition, what are they doing? We spend so much time on data that we forget why we are here.
The article is spot on in many aspects; however, the conclusion that customer analysis will drive predictable ads is off base. Analysis is a tool and a very important tool for marketing and advertisers to use to drive communications. Marketers and advertisers need to work with the insights team to drive the insights in a relevant direction to inform marketing strategies and interesting creatives that will capture their target and connect with customers.
Julie Bernard was 100% correct: analytics need to be used in conjunction with judgment. Analytics should be viewed as a way to objectify decision making, not as the decision itself.