Big Data For Marketing? It’s All About The Questions

Looking into a heavy topic today: Big Data for Marketing. “Heavy” because it’s sorta philosophical. I think Big Data for Marketing is more about the questions than the answers. More about the insights than the technology. The opportunity lies in defining how Big Data can help you better reach your customers with your messages in a way that gets them to act. And this starts with simple questions like: how did your last campaign perform? Which keywords drive conversions? What websites did my prospects visit before they came to my sites? Which social conversations are spurring the actions that lead to deeper engagement with your brand? Big Data for Marketing is easy to say but hard to do. So here I will look to a few of the “experts” on how to take advantage of all this data and turn it into real business insights that drive real business value.

Big Data Marketing Is Like Gold Mining

Dean Bedard likens Big Data marketing to gold mining when he says “it’s not enough to know where the precious stuff is. In order to reap the riches, first they have to get it out of the ground and turn it into something they can use.” He outlines four steps to prioritizing the road to mining Big data insights including:

  • Setting up a cross-functional marketing and IT team
  • Prioritization of the marketing goals Big Data can help you accomplish
  • Mapping the data sources to obtain reporting on key metrics supporting the main objectives (KPIs)
  • Creating an “agile marketing” implementation roadmap which develops against the highest priority areas to generate the quickest value.

Big Data For Marketing Requires ‘Destination Thinking’

Matt Ariker from McKinsey had similar thoughts when he suggests marketers start their Big Data projects by thinking of the end goal and then working through all the details. This so-called “destination thinking” will help the strategic marketer avoid the traps of many Big Data Marketing projects where the deliverable becomes the end goal itself instead of the business value imagined at the outset.

The Era of Big Testing

Scott Brinker (@ChiefMarTecsuggested in my own future of marketing interview series that we need to encourage more marketing experimentation and “Big testing.” He believes marketing needs to take advantage of both new technology and new talent to start creating hypotheses. Then to use Big Testing to prove them out – right or wrong. For Scott, “the key to scientific marketing is actually the embrace of marketing experimentation as a driver of continuous innovation.”

Marketing Offices As Trading Room Floors

Brian Kardon (@BKardon), CMO of Lattice Engines imagines a day when marketing offices resemble trading desks with screens of real-time data streaming in and marketers yelling “buy, buy.” But he laments, the effort by most marketing departments to develop real-time dashboards are “dwarfed by countless marketing Powerpoints and never-read marketing plans.” Brian understands the power of questions. In his own office he has dashboards that tell him:

  • What was the unsubscribe rate from that new campaign?
  • Which version of the email performed better – the one with the orange button or the blue button?
  • What deals are stuck in the pipeline for more than 60 days?
  • Which reps had the lowest win rates this year to date?
  • Is Twitter sentiment for our brand trending up or down?
  • What % of our customers at Dell are using Lattice right now? How does this compare to yesterday, last week or last month?
  • How many unique visitors came to our site today?  Where did they come from?

Big Data Marketing Must Be Illustrative

According to Jon Baron (@TagManJon) the difference between Big Data and Big Data Marketing is found not in the analyses, but in the insights that turn into actions. Jon define Big Data as “a simplistic term which refers to the automated accumulation and analysis of audience data on a large scale.” But emphasizes that Big Data for marketing must be illustrative of the target audience the marketer is seeking to understand. It must help us to be more efficient or effective at reaching a target audience and getting them to act on the marketing message.

Big Data Marketing Means You Understand Your Customers’ Questions

Finally in my own Big Data Marketing rant I talk about the need to understand the questions that our customers are asking when they do a Google search, visit a website or participate in a social media conversation. I believe every marketing plan should start with an analysis of your companies “share of conversations.” This shows you not only how well known your company is in your solution space, but also how likely your customers are to act on that awareness (RT, comment and ultimately convert to a lead and a customer). My own 4-step plan to Big Data Marketing Insights:

  • Define your customers’ top keywords and topics through search analysis. Starting with a simple look at Google Trends.
  • Social analytics to show what % of social conversations include mention of your brand. This is where the data gets really big.
  • Insights from your Website analytics will help you understand which keywords and referring domains drive conversions.
  • Finally, combine these 3 massive big data sets to help to make decisions on marketing plans, tactics and budget.

So here is a curation of thoughts from folks I follow. But let me know what you think in the comments below.

Michael Brenner

Michael Brenner  is a Top CMO, Content Marketing and Digital Marketing Influencer, an international keynote speaker, author of "Mean People Suck" and "The Content Formula" and he is the CEO and Founder of Marketing Insider Group, a leading Content Marketing Agency . He has worked in leadership positions in sales and marketing for global brands like SAP and Nielsen, as well as for thriving startups. Today, Michael helps build successful content marketing programs for leading brands and startups alike. Subscribe here for regular updates.

14 thoughts on “Big Data For Marketing? It’s All About The Questions

  1. Good article and references Michael. Definitely heavy indeed. From a philosophical standpoint, I view Big Data giving us a window into “how” behavior. Whereas I also believe Big Data needs to be complemented by qualitative understanding of “why” behavior to get true insight and foresight about customers/buyers. Now that could be another heavy discussion 🙂


  2. “Big data means you understand your customers’ questions” Yes! If you don’t understand your customers’ questions, how on earth are you providing value to them?

  3. Michael, When I read your thread on Big Data I’m mostly hearing Small Data — unsubscribe rates, sentiment and even brand monitoring are small subjects in the Big Data pool. We’ve been developing tools and methodologies for marketers to access and analyze big data. In the process we discovered that big data analysis is very good at unearthing risk (which is the same as opportunity). This led us to seeing Marketing as a risk management function. Done well, Big data analysis tells companies that unsubscribe rates will fall next quarter, sentiment is about to turn positive or your brand will be seen as less relevant over in the next 18 months.

    Jon Baron is right about the insights being more critical than analysis. Insights come from asking the right question — but it’s not the customer’s questions that matter. There is a common experience or “glue” that binds communities together. Asking questions about the binding reveals more insights about risk and opportunity.

    1. Hi Russ, so you’re adding the whole Predictive element here which I completely agree is critical. You are also right on about most (not all) of the data referred to as small data. But I can’t agree that the customer questions don’t matter.

      Every businesses’ pure existence relies on anticipating and solving those core customer questions. The business that has yet to identify which questions their customers are asking are flying blind and speaking only or mainly to themselves.

      I’m not suggesting that this is all a successful Big Data Marketer should do. The themes you mention are important to protecting and growing the business. But it’s the understanding of the combination of customer and business questions and predicting outcomes that will drive success IMHO.

    2. Russ – I think you are making an important distinction. Big Data is definitely not synonymous with basic marketing analytics. I think you are 100% right that there needs to be an algorithmically-based element of prediction to count as big data. Thanks for that insight.

      “You Keep Using That Word, I Do Not Think It Means What You Think It Means”

  4. Hi Michael,

    Great article and I especially liked your four step plan. I have developed something similar regarding big data and CRM and I also developed four different steps in how the future of CRM is impacted by big data:

  5. Thanks Michael, very insightful. I think that big data is a real challenge to marketers and that it needs to become simpler to use before we see mass adoption.

    1. Thanks Ariel, i’m hearing a lot of people talk about the little data (insights) that are what we really need but to me, it still begins with asking the right questions

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