Big Data For Marketing: I Want My Real-Time Dashboard

“Data is the new oil.” That was one of my favorite quotes from a conference I attended earlier this year.

The businesses that can harvest and take advantage of big data will prosper and win in today’s hyper-competitive, social-driven and mobile-accessed economy.

For marketers, this presents a massive challenge: first, we need to cover the cost of gathering and storing the data. Second, we need the foresight to look at new technologies and tools to access it. And third, we need to hire the knowledge and expertise required to use these insights to move our business forward.

That is why, as part of my 2013 marketing predictions, I identified data scientists in marketing as one of the emerging roles. And this is also why I want a real-time, big data marketing dashboard.

Otherwise, how will we know that our activities are moving the needle, creating business results and resonating with our customers?

Retailers Looking To Leverage Big Data

I’m not alone. Retailers are quickly realizing that big data is the new battleground in the fight for high-volume but razor-thin sales margins.  The convergence of social media, cloud computing, mobile access, location-based information and e-commerce are all combining to create a “perfect storm” of big data.

Big Data Analytics are helping these retailers shrink their supply chain costs and to determine which products to sell, at what price, in which place and on what level of promotion (remember the “4 P’s” of marketing?). They are also using Big Data to understand who is shopping, and how to deliver the best experience through personalization. This is only possible by analyzing lots of Big Data.

What Is Big Data For Marketing?

One of the key metrics for marketers to determine the effectiveness of marketing activities, especially content marketing is what I call “share of conversations.”

“Share of conversations” is the percentage of time your brand shows up in online conversations.

The number by itself, probably has little meaning. But when compared relative to your product’s market share, or when compared to your competitors, or when compared over time, this metric can help you determine if your content marketing is working.

“Big Data Is Bullshit”

In a recent eBook from Big Data provider Lattice Engines called “What’s in Store for Sales, Marketing and Big Data,” Foundry Group co-founder Brad Feld says:

Big Data is bullshit…20 years from now the thing we call ‘Big Data’ will be tiny data . . . The key for 2013 with Big data is to figure out how to make a difference. Don’t let marketing noise obscure what’s real and what isn’t.

It’s easy to see how Brad is not far off. If the information created in the last 2 years is greater than the information created from the dawn of time until then, imagine what Big Data will mean to marketers in 2023 or 2033.

All I Want For 2013 Is A Real-Time Marketing Dashboard

I want to combine the powerful forces of Big Data for marketing, the “noise” of all the social conversations, the power of understanding prospect intentions in search insights with the results generated in web analytics.

Is this possible?

Here are the steps I think we need to take to get your own big data for marketing, real-time analytics dashboard:

  1. Define your keywords. You need to look at topic modeling around your own solution areas to determine which words your customers are using when they search for solutions. It all starts with the keywords.
  2. Gather search analytics using unbranded keywords on your top categories and themes. Think Google Trends on steroids. For example, you need to know how many searches happened yesterday on terms in your solution category. You need to know which terms were most used? And you need to understand what % of those searches included your brand terms?
  3. You need social analytics on how many conversations occur each day across the social web. This is where the data gets really big. You need to know what % of those conversation include mentions of your brand. You need to know what are the main topics and hashtags and titles.
  4. You need to use web analytics to understand how many of your web property visitors come organically, through search and social and what % of those visitors are from unbranded terms (visitors who didn’t already know you).
  5. It is the combination of these 3 massive big data sets that will give you share of conversations! Now you need a tool to bring them together, normalize them across dimensions and display the insights you need to run your business.
So yes, I think it is possible. And I cannot wait to get my hands on one!

Let me know what you think in the comments below. And please follow along on TwitterLinkedInFacebook and Google+ or Subscribe to the B2B Marketing Insider Blog for regular updates.

Photo Source

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.

15 thoughts on “Big Data For Marketing: I Want My Real-Time Dashboard

  1. Michael, while the idea of real-time dashboards are very cool indeed, there are a couple of problems with their execution.

    First, social marketing dashboards aren’t like automobile dashboards. Better said, we aren’t as good at driving the insights bus as we are the family van. Having data in front of you doesn’t – real time or not – provide the insights and analysis that comes from a little ‘soak’ time. We will get better at understanding the dials and indicators over time, but right now it’s shiny buttons and flying lights and most analysts struggle at differentiating the speedometer from the tach.

    Add to that the service layer – or perhaps subtract. We have a lot of trouble getting real or near-real-time data from the currently available constantly changing API’S.

    Our organization is working on surfacing the Meaning, more than just the data. Just like there are narrative character archetypes in literature, there are patterns in social behaviour that are discernible, measurable, and can be recognized best through automated systems.

    While most fumble with keywords and topics, imagine if the dashboard told You what was important by recognizing shifts in topical points of focus, meme transitions and evolutions, inflection point patterns, etc.

    When dashboards can teach us to fish….

    1. It’s a totally fair point Doug and one I was thinking about when I wrote this but the article was getting a little long already 😉

      I really mean a “near real-time” dashboard and mainly even would be happy just to get “share of conversation” on a monthly or quarterly basis as a guidepost for how well we are doing, what is working and where we should shift our focus. Now at SAP, we are doing this but it is not aggregated in the way I describe, although we are working on it. And it is certainly not real-time.

      having said all that, we are doing near real-time social listening. But that is a bit different from what I am talking about. So good points. Let’s use the data we have and make better decisions? I totally agree!

    1. Great point Jeff. I make that same pitch in a lot of my other articles where I talk about disseminating marketing DNA across the “Social Business.” You are correct that it is an important point here as well!

  2. Michael, man would I love that dashboard as well. Connecting the dots is always hard and I often find we make so many assumption about importance along the way. My only addition to the dashboard would be tying all the touches to a real customer purchase with a financial impact. If we have the ultimate business objective tied to the sources, we could then better weight and prioritize the actions and strategies. You have that and I am in. Then we can test the keyword assumptions against the business outcome and have a real powerful tool.

    1. Peter, thanks and in my opinion, you have just described the holy grail. Share of conversations plus appropriate marketing attribution would drive true customer-driven and business-results-oriented planning from end-to-end.

      I wrote about this more than a year ago in “Who Gets Credit For Marketing ROI?

      It was not a very good expression of the frustration of the “last click problem” in marketing you alluded to. But I do agree with you, and unfortunately, I think we aren’t there yet. I hope soon!

  3. Michael, funny you said holy grail, because I almost said that in my comment. I actually back spaced over it because I think we need to tie as much as we can to financial ROI as possible today without feeling it is unattainable. Even with the “last touch” issue, It still gives us visibility to the gateway to conversion. If we start measuring more there first, the next frontiers are the other digital touch points. Some of the digital pathways are there today. These can help us gain more insight into the entire digital customer acquisition equation.

    Even though we do not know all the +’s and -‘s in the entire equation, I firmly believe we should still try and measure by the ultimate equals at the end of the equation.

  4. Great post, Michael. Marketing data, as you well know, is in silos — like CRM, or web analytics, or marketing automation, or social media tools. A unified, real-time dashboard is just what we need. But Santa is not likely to bring one to the Brenner house this year. Thinking 2014 might be the year.

    I’ld also like to see some predictive analytics in the dashboard. Simply aggregating all the marketing data is not enough. There are likely patterns and behaviors across social, web and other platforms that are meaningful, but hidden in the swell of big data. Hoping for a dashboard that tells me not just “what” is happening, but “why” and “what we should do about it.”

    1. Thanks Brian. I figured it might take some time but I am willing to wait for the predictive aspect. We need more than just the insights, we need the ability to model different approaches and see what impact our activities might have.

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