There’s a funny saying circulating with marketers right now on the current state of Big Data:
“Big Data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
Gartner recently released a report that 64% of companies are deploying or planning to deploy a Big Data project, yet 56% struggle to know how to get value from their data. As Matt Asay wrote about the Gartner study, “it seems that they’ve allowed the hype around Big Data to both motivate them to start but also confuse them as to where they should go.”
The promise of Big Data is significant and many predict that 2014 will be a breakthrough year for Big Data marketing. Yet, I’ve seen many companies struggle with Small Data, let alone Big Data.
Big Data doesn’t replace Big Ideas. It’s what you do with the data that matters. As Big Data matures and starts to deliver on its promise, big marketing ideas to leverage the power of those Big Data insights will be needed more than ever.
I’d love to hear some of your favorite case studies on leveraging Big Data in marketing.
(Marketoonist Monday: I’m giving away a signed print of this week’s cartoon. Just share an insightful comment to this week’s post by 5:00 PST on Monday. Thanks!)
18 CommentsJoin the Discussion
and first thank you for your cartoons that always are pure joy to find on my FB wall 🙂
I think it is a complete different job, being a marketer and analyzing data. Especially that kind.
But I’m a researcher… I might be a little biased myself… 😉
[film spoiler] Like end of Finding Nemo when the tank fish finally get into the ocean in their bags, big data is the same…’Now what?’.
This happens so often, a confusion between cause & effect. So many think big data is going to supply them with some sort of insight, idea or instantly reveal some hidden truth when its actually the other way around. Many people buy an expensive camera thinking it will make them a better photographer, when really better photographers have better cameras. The same is true of big data
Jacky Hobson says
It’s much like the Emperor’s New Clothes – no one wants to actually be the one to stick their neck out and publicly admit “I don’t know how” or, even, “I don’t know what it is”. Most marketers don’t trust their data enough to even use a personalised name field let alone base campaigns on buying history or preferences.
Completely agree. We had/have loads of data floating around various internal systems, but lots of it is of varying degrees or reliability/ quality.
Our start point is to try and clean up what we’ve got, to understand what we know and see what it might be able to inspire (marketing-wise).
THEN.. we can implement an automation programme, based upon processes that work for us and generating data that we expect.
By starting with smaller questions and fixing things one step at a time, we’ll end up with a really useful tool. The hard part is not jumping to the end game without understanding how (or why) we got there.
We’ve used big data several times at comparing customer and consumer trends in our CPG business – when do sales start on a new product or a seasonal business, where are they felt geographically, which channels perform better than others – and then use that to match up promotions at the right place and time to engage with consumers. It’s been a challenge for us, not only to get data that is clean and accurate, but then to deal with the internal resistance when the big data insight conflicts with our “tribal knowledge” about consumers and markets, and different agendas with our organization.
asit gupta says
Data’s role is to drive better decisions. The fact that decision making process in most companies is flawed and full of cognitive biases is well captured in the book “Decisive’. http://www.amazon.com/Decisive-Make-Better-Choices-Life/dp/0307956393. Big data itself is not going to solve this issue.
Blane Warrene says
It would seem that perhaps only the absolute largest organizations (NSA, app stores from Apple, perhaps Google) have unlocked some of the value of big data. Part of the problem is overreach – always needing more data to try and get a fuller picture. It would be wise to dig down into the data available already and look for locked up value. While I am an early Gen Xer who embraces technology – I am also not fully sold on the value of leaving “it all” up to the data – as flawed as we are humans do make some excellent decisions on instinct and experience.
Big Data sounds like a professional wrestler’s name? I have used “Big Data” in a past project and it did serve me well. What made it useful was; (before I purchased it) Setting the parameters to narrow the amount of data to a usable/useful quantity…understanding what to ask the data… what was the goal of obtaining the data… and how I planned to use the results. Oh yeah, and having a team run the analysis for me. I found it to be very enlightening and it changed some of our marketing strategy and messages.
Bill Carlson says
I’ve done some work for one of the largest big data suppliers and it still comes down to people somewhere in the chain, whether at the data supplier or the recipient marketer or both, to decide what info matters and does not, then assess the selected info and then decide how to act on it.
And I have seen many examples of multiple people looking at exactly the same data (big *and* small!) coming up with very different interpretations and ideas about how to apply those interpretations. (Love the references above to “tribal knowledge” and “cognitive bias”!)
As a practical matter, it is entirely possible to know too much — sure, the more you know, the better off you are, but at some point the overload of info coupled with a natural desire to work through it and/or a sense of nervousness about not digging deeper can, in my opinion, slow a process down rather than speed it up.
And time is important. A good idea executed on a timely basis beats a better idea that never gets past the spreadsheet. The problem is that sense of dread associated with believing there even *is* a better idea which, in general, can’t really be proven. And even if there is a better idea, how *much* better which most certainly would be tough to model in advance or test A vs. B.
As mentioned, perhaps the largest of the largest brands have the marketing sophistication, budget and tools to actually leverage some of the most granular data available, but practical limitations about ultimate activities should be a factor for most others in deciding how much work to put into digging into big data. All too often comes down to “which TV show should I run my commercials on?” or “which websites should I run my banner ads on?” or “I’m not creating an individualized email for every single consumer so what are the most common denominators for content so I can cover everyone with one, or maybe 3 variations?”
Note that I’m a numbers guy, love the analytical process and think there is absolutely merit in working with the data, but “all things in moderation…”.
The manufacturing industry–companies that make stuff–have a plethora of data. It’s big, it’s small, but it’s there. TMI is a good acronym for them, because they can quickly become inundated with data, but there’s no information–it’s just discrete points of temperature, pressure, speed, etc. So a lot of folks serving that industry are providing tools that take the data, and make it relevant, by structuring & adding reporting on top of it. For manufacturing companies, that’s huge, and as you’ve aptly pointed out, education needs to happen in order for them to “get” what the products offer (they are called Enterprise Manufacturing Intelligence).
Jeff Zwelling says
Great cartoon, Tom. Big data may be one of the biggest buzz phrases in marketing right now, but there is signal among that noise. Marketing campaigns are constantly creating big data across channels, but big data is not the magic answer. Marketers need to first make sense of that data. The solution lies in attribution; more specifically, regression-based, algorithmic attribution that tracks users across their entire paths to purchase from first exposure to conversion, and scientifically attributes value to each marketing touchpoint. I have seen brands, including Dollar Shave Club, Bonobos and Indochino, take advantage of attribution to make sense of their big data, and as a result optimize their marketing spends.
Jeff Zwelling, CEO and co-founder of Convertro
For me the biggest peculiarity surrounding Big Data is this sense that the use of data in Marketing is something new. Direct Marketers have been using data to build regression models, segmentations and customer profiles for decades, arguably the only difference is that these have become more important and actionable than ever before thanks to the prevalence in digital channels.
The term “Big” often implies that the volume of the data is the challenge marketers are grappling with, yet advances in technology mean it’s never been easier to store and process large volumes of data. Data transformations that used to take hours to run 5 years ago now take seconds.
Volume, Velocity and Variety aren’t the challenges most marketers are facing, but rather how can I use it to enhance customer engagement and experiences. The sooner we approach Big Data as a creative challenge rather than a technical one, the sooner we’ll start to see it make a real difference.
Wouter Verburg says
Excellent cartoons that always manages to put a smile on our faces!
As an academic Industrial Design Engineer, I have always been fascinated with the ‘data to wisdom’ journey in many value chains. A couple of my findings to share that also link to earlier posts above:
> Small data can prove to be BIG challenges in internal and external environments – uniting data sets from different departments (silo’s) within one company can be a big achievement (without qualifying for big data) and provide valuable insight. Not everybody will be pleased with the findings. Unite & close the ranks internally!
> New is always scary – a proper understanding of where your business is coming from (past value) and where you would like to go to (future value) can help you fit the pieces together. Companies who ‘dare to share’ this analysis with the employees, have much more agility and are better survivors of crises. Map the road of value add and remain flexible to adapt to changing realities!
> Make or buy – sometimes it’s a lesser investment to buy external data than to repair internal data. There are a million (at that time) valid reasons for datasets that have turned bad throughout the last decades. And there are always more than one way to achieve the desired result. Walk around and talk to your specialists, you will be amazed how much help/data/information is already available. Accept your past and create your future together!
What question would you like to have answered (value add) when and what -big?- data is therefor required?
For ‘Big Data’, should we not read ‘Dig Better’?
J C says
Big data isn’t valuable for what it is, but for what it makes possible. Actionable data is the goal to strive for. It is much like the difference between “knowledge” and “wisdom”.
Steve R says
Perhaps the 3Vs defining “big data” (velocity, volume and variety) matter less than the “so what?”… which I define with the 3As:
ACCESSIBLE (understandable, communicated well with the right language and images)*
ACCEPTABLE (believed by decision makers as lack of credibility of inaccurate or incomplete data can be a major barrier)
ACTIONABLE (you can actually do something with the insight that makes a difference)
This works for big data and little data alike.
[* like your cartoons are a great way to get across sometimes complex concepts in a great way]
tom j. hidvegi says
I believe that ideas are about promoting and big data is about predicting. In today’s marketing environment it shall not be either or but both. Having said that, big data will never help your marketing if you are not prepared to deal with small data first. If your marketing is not agile enough and you are not prepared to adapt to an ambidextrous marketing management, then regardless of your predictions and insights you will lose on small data first. I believe that, Big Data=Pro-acting & Small Data=reacting.
If Big Data was indeed like teenage sex, a more accurate description (from the broader population’s view rather than just the teenager’s point of view) would be that a vast majority of people would like to think it doesn’t exist at all, there’s no need to talk about it, preaching abstinence is a realistic way to deal with it, and that teen pregnancy doesn’t happen.