Big Data

Training tomorrow’s Marketers on Big Data

Big Data Boot Camp for Marketers

Big Data is rock’n the Marketer’s world. It is signalling a wake-up call that marketers need to be more metrics driven, more technically savvy and more process oriented. At the top of the food chain, CMOs are taking on responsibilities that traditionally belonged to CIOs. And at the middle management level, marketers are being required to be more technical and metrics oriented.

The days of just fishing for eyeballs or operating based on one’s gut instinct are long gone. It is no longer acceptable to just look at demographics or psychographics or just count eyeballs. Instead, marketers need to focus on the numbers — people’s tribes, their behaviors, their interests, their online behavior — both in terms of surfing the website or a mobile app or transacting with a page or shopping cart..

Most marketers would agree, however, that they are not prepared for the incoming Big Data wave: they lack resources, lack data know-how, and they don’t know how to get started.

According to a study from The Economist Intelligence Unit, only 24% of marketers use data for actionable marketing insight. Furthermore, in that same study almost 50% of marketers cited a lack of capacity to analyze big data. Some companies are increasing their budgets for Big Data analytics. The problem is that there’s no road map for getting these marketers up to speed.

Rather than focus on the bells and whistles (the technology) of big data, here’s are 7 steps a marketer a marketer can take to get out of their comfort zone and jump into the Big Data World:

  1. Understand the definition of Big Data, which is usually defined by the 3Vs:

    1. Volume or the amount of data involved

    2. Variety or to how the data is structured

    3. Velocity or the rate at which it is generated and analysed

  2. Subscribe to and learn from few key bloggers, who can teach you the ropes:

    1. SemAngel Blog by Gary Angel: Gary brings over twenty years of experience in decision support, CRM, and software development. Gary co-founded Semphonic and is the President and Chief Technology Officer.  But don’t let the CTO title fool you. Gary is the the brightest consultant I have worked with and can take complex techn issues and break them down into easily digestible and understandable. chunks for markets

    2. Analytics Blog by Justin Cutron: Justin is currently the Analytics Advocate at Google, so he has a boatload of knowledge. In his blog, he breaks down digital analytics for businesses.

    3. Customer Analytics blog by the SAS’ companies – This blog is for anyone who is looking for ways to improve the business of marketing and communicating with customers, which includes everything from multi-level marketing to social media campaigns.

    4. Big Data Hub by IBM: This blog is filled with case studies, videos, etc. from key players at IBM and beyond.

    5. Business Analytics Blog by Tim Elliot: Tom is an Innovation Evangelist for SAP. This blog contains his personal views, thoughts, and opinions on business analytics.

  3. Get your organization big data ready:

    1. Tear down your organization’s silos and engage multiple departments

    2. Give team members homework — tell them to read the blogs mentioned above.

    3. Think about how you will link your current data infrastructure to your project (that means a business analyst, and IT guy, etc. should be involved in the meeting)

    4. Know and recognize that Big Data is a team sport

  4. Work with  framework your organization agrees on, such as:

    1. Define Your Goal

    2. Understand your resources

    3. Review key segment’s Journey

    4. Confirm you are capturing data during each phase

    5. Establish benchmark

    6. Create a small measurable deliverable (test)

    7. Track over time

    8. Establish toll gate reviews

    9. Expand program

    10. Tweak your programs as needed

  5. Define the desired outcome and the one question you want to answer

    1. Yes, narrow it down to one (primary) question

    2. Answer the question and move on

  6. Understand your inputs by breaking down your customer(s) journey

    1. Identify the different sources of data, such as social network behavior, information from third party lists, mobile usage, downloads, etc.

  7. List out different types of potential metrics you could track:

    1. Information related specifically to the customers transactions (or actions)

    2. Information related to a segment’s usage patterns

    3. Information related to the overall marketing program

In some respects Big Data is just an extension of database marketing, a popular term in the 1980s and 1990s because it focuses on leveraging customer information to segment an audience and develop personalized campaigns. The biggest difference now is that we can leverage unstructured data (video for example) and implement just-in-time programs.

I am a big believer in learning by doing. If a Marketer really wants to be figure out how to integrate big data into their business processes, they need to have on-the-job training. (And to that point, I actually believe this is important for the CMO as well as the Business Analyst, although the latter might get more in the proverbial data weeds!). If marketers don’t do this, they will lose their admission ticket to be in the marketing world.


Personalization with Big Data


Back in the 1900s (1991 to be precise), I trained in a database marketing type of boot camp. I worked on American Express (AMEX), managing it’s Gold Card direct marketing efforts. Amex, a leader in personalizing printed communications, had created its most successful program when it highlighted in the direct mail pieces that someone was a “Member since XXXX.” Yes, membership had it’s privileges. But also, for American Express, this personalization triggered a lift.

Show me what you got

Now it’s 20+ years later. And while 2013 was the year of Big Data in the back office where companies tried to set up the proper infrastructure and human resources to be part of this phenomenon, 2014 will be the year to personalize Big Data on the screen.

Of course, the term personalization has many meanings to many people. For the purposes of this blog, I am focusing on ‘the content on the screen.’ Customizing what the user reads and sees will be the challenge, especially because a responsive design approach still requires careful consideration about what is personalized on a tablet versus an iphone.

Big Data will be operationalized

With personalization being a key theme in 2014, marketers will need to get their hands dirty and truly understand the different categories in their customer database. They need to design their digital platforms with their database in mind, knowing that different areas of the screen can pull in content from both the customer and product database. For example, Amazon pulls in two different types of data based on my purchase behavior: books on digital marketing, which I am interested in, and children’s videos, which I access every night via their Instant Video. Their customer database might carry just the title name, the author and the price. The assets for that information would be in a product database. The two need to work closely together on the screen.

Every day, Netflix and Amazon demonstrate their ability to leverage this kind of data to talk to their customers on an individual and personal level. Sometimes, I think they could go a step further in personalizing info on the page, especially because one of the big battle grounds in 2014 will be same day delivery. Amazon and Wal-Mart can incorporate GPS data to determine potential offline purchases or product drop off points.

Intuit’s 2013 Turbo Tax product offers a nice personalized solutions for its loyal members. It automatically transfers returning customer’s personal information and prior year tax return data, including wage and salary information from their employer, and then adapts itself based on that information to splash screens and questions that are not relevant to their specific tax situation. The company leverages all the valuable preexisting info that sits in its databases.

Size doesn’t matter

Smaller and medium size companies need to take their old school ‘face-to-face’ approach to the next level and personalize more than just ads or emails. They need to personalize at all touch points, including customer service, Skype, Hangouts, etc.

It’s important to remember that having the largest dataset or most sophisticated database will not guarantee an effective personalization program. It requires testing out and knowing what data elements will motivate a customer or partner to take an action.

Getting under the hood

Here are simple steps to get you started:

  1. Assume any data element in your customer or product database can be used to personalize information on the screen.

  2. Identify the type of tribes/segments who will visit your site or your app (or even call customer service).

  3. Prioritize a list of 3 CTAs (call to action) you want each of these segments to take when they use your product/site.

  4. List out the information you want to display on screen.

  5. Map out these info elements for multiple screens (Tablets, Smartphones, etc.) because you can’t share the same information on a smartphone as you can on a PC.

  6. Confirm these data elements are stored in your database(s) and if not, plan on capturing and storing them.

  7. Work with your designers and programmers to determine how many characters, picture size, etc. you can fit on the page.

  8. Work with your analytics team to set up the proper tracking

  9.  Remember: Start simple. You don’t need to personalize each area on the screen.

  10. Also remember, give your marketing team a basic course in database marketing.

Training Marketers on how to leverage their customer and product databases will take time. The more they can understand about how data can be pulled from a system and displayed on a screen, the more effective they will be in selling their products and services. This will take time. This will require marketers to get their hands dirty, get under the hood, and understand more than the fundamentals of big database marketing. This is true even if they work outside Silicon Valley or Silicon Alley.

The question is: Do they have the desire to acquire this skill set?

Zooming in on (your location)

The Map: Transformed from a Statiic to Evolving Platform

This occured to me while watching Dora, the Explorer, and her magical map.

Deloitte recently came out with a report discussing the power of combining location data with government information. While the report focuses on the influence this is having on governement services, it also brings to mind the impact on the private sector.

Our ability to compare places is becoming (more) multi-dimensional. We are moving from the traditional approach of looking at location based on

  • Demographics: Age, gender, income
  • Infrastructure: Transit, land use
  • Geography: Natural resources, threats
  • Public assets: Government facilities, resources
  • Administration: Regulations, tax cod

Location Takes on New Meaning

The report highlights many opportunities for companies to leverage more detailed location data. They can:

  • Look at the uniqueness of a certain place: Information on neighborhoods goes beyond census data and other numbers and focus on tribal behavior, such as what kind of services people are accessing, where they tend to congregate (sorry if this sounds big brother) and how they share different experiences.
  • Bring to life the interaction between Tribes: Following up on the above, we can see how different neighborhoods or tribes interact with each other. As Human 1.0’s research shows, people belong to multiple tribes and can change tribes over time.
  • Tailor products and services for different tribes which could be based on location or context (note: that tribes don’t have to be based on location).
  • Share data: Data is easy to share with different stakeholders, such as government agencies, divisions within a company, etc.
Note: This enables (and maybe requires) organizations to interact and respond to local Tribes on a daily basis. This is accomplished with the help of Geospatial tools that:
  • Harness place as a comparative tool
  • Drive accountability
  • Move from prescription to prediction
  • Rethink boundaries

Sharing of Experiences

Location services reinforce the power of community and sharing experiences at a local level. When location is coupled with other information, it opens enormous opportunities to servce customers better. As Deloitte points out, it

Allows us to quickly visualize and find meaning in billions of transactions,  tweets, check-ins and geotagged photos. When combined  with existing government data and expertise, this  intelligence can, in turn, help us redefine the way we see  and understand the world, creating digital pictures of the ebb and flow of our societies.

A ‘place’ becomes a living and evolving platform of information. It enables organizations to:

  • The host (the government’s or company’s app) becomes a device to gather people together based on their location
  • The crowd has power in numbers to influence outcomes or to partner with other lcoations (shared experiences)
  • It becomes more apparent where to allocate resources.

All of this adds a new dimension to ‘Service Delivery and Design,’ a topic that I have discussed earlier. Companies now have a new challenge (and opportunity) in managing customer touch points. As Deloitte points out, there is definitely an ‘arms race’ among Google, Apple, Facebook, Amazon and others to offer services based on location. These tend to be silo’d offerings though, not taking into account the different nuances (and the sometimes overlapping behavior) of each Tribe. In the case of Facebook, it is unclear of how comfortable people in sharing certain information.

Big Data and Privacy


This weekend I had some down time and decided to read The Daily You by Josephy Turow, dean of Graduate Studies at the Annenberg Communications School at University of Pennsylyania.

And all I can say is that this book is a must read for anyone working in the digital space, especially advertisers. The book starts out with a nice history of web advertising and then goes on to discuss today’s customized advertising, discounts, news and entertainment , all of which are being tailored by newly powerful media agencies on the basis of data we don’t necessarily know they are collecting and individualized profiles we don’t know we have. Advertisers are placing individuals into what the author calls “reputation silos.” (These are really different psychographic type of segments)

For example, you might be categorized as a Caucasian living in New York City who only eats organic foods and watches Mad Men every week. Is that such a bad thing? It depends on what types of ads and offers are being served up to you based on this information.

The main message of the book is that although we love cool new web based technologies and platforms (Facebook, etc.), the consumer runs the risk of limiting our privacy and anonymity to advertisers.

Reading this book reminded me of my days at AOL, when I worked on their first commercial Internet properties, GNN and WebCrawler, creating advertising inventory. One day back in 1995 stands out for me. It was when Proctor and Gamble, the largest media buyer, wanted to advertise on several of our properties. My co-workers and I spent the rest of the month running around like chickens without our heads making sure everything went perfectly for P&G. It was a simple reminder that the advertiser rules when revenue is involved.

According to the author, we are just at the very beginning of an advertising or consumer behavior tracking revolution as advertisers aim to integrate consumer information across multiple platforms (the web, mobile, and TV). This is Holy Grail for marketers. Companies like Google will also use this information to serve up personalized search results, not just ads. Ironically, when people were asked how they’d feel if a search engine tracked what they searched for, 65% said it was a bad thing. 73% overall said they were “Not OK” with personalized search, since they felt it was an invasion of their privacy.

Although Turow doesn’t touch upon Facebook’s and Google’s recent and ever-changing advertising privacy policies in the book, he does provide some good commentary on this topic in a recent interview he did on NPR’s Fresh Air with Terry Gross.

So far, The Daily You has not gotten the press it deserves. So, take a chance, buy it and read about where media and advertising are going. And for those folks who are media buyers or work with major advertisers, it is important read because of it will provide some valuable insights into customers’ and viewers’ privacy concerns.

Companies can get more informed and responsible by becoming members of the Network Advertising Initiative (“NAI”) and adhering to the Digital Advertising Alliance’s Self-Regulatory Principles for Online Behavioral Advertising. If you’re an online user, you can find out more about online behavioral advertising and learn what choices you have and how to use browser controls and other measures to enhance your privacy.

Since online advertising is becoming more and more complex, what do you think both publishers and advertisers should do in the face of the increasing discussion about consumers’ privacy?

Analytics: Key part of Social Business Center of Excellence

 So you want to build out a robust social media analytics program for your company, eh?

This process should be very similar to the approach you took in building out your digital analytics program. Follow the same trail to the summit.

Like any good journey, you need to make sure to focus on the basics first, such as:

    1. Getting internal alignment from you key stakeholders on your business objective (Hopefully, one objective!)
    2. Obtaining sign-off on the key metrics you want to look at
    3. Understanding your organizational constraints and resources
    4. Identifying and setting up the right tools/technology

But before launching a program, there are some important steps along the way that you should seriously consider:

    1. Work closely with your IT group because they usually set the standards for bringing technology into an enterprise environment
    2. Work closely and meet often with your financial partner (usually there is a finance guy assigned to your team) to show them that you are working on driving the business forward, that you understand what you are doing.
    3. Establish a baseline to measure from and know that every so often you might have to ‘move the goal line’ of desired results as well as the original baseline because your growth my skewed in the early stages of the program
    4. Incorporate Share of Voice vis a vis your direct competitors, your indirect competitors (if you are selling financial software to small businesses, excel can still be viewed as a competitor)
    5. Understand that there can be multiple ROIs for the whole organization since different groups have different objectives in using social media.
    6. Know that if you have an international focus, the same tools might not always work as the ones you use domestically
    7. Build in a mobile component to your social media analytics because as we all know, it is here to stay.

Most of the above applies to an enterprise type or Fortune 100 company. Ideally, the individuals working on measuring your success would be part of a Center of Excellence. Note, however, that this is more than the hub-spoke model, where your social media team resides in the middle with representatives from multiple groups.

One of the challenges with this model is that the groups representing the spokes are not funding a full time or part time person to look at social media, but rather having someone ‘just attend the meetings.’ Secondly, the Hub, the social media team tends to still be influenced by where they sit in the organization. If they sit with the public relations team or corporate communications team, those groups business objectives might not support others divisions. Ideally, I think Social Media today should be a true Center of Excellence, completely funded independently, and set up like finance or human resources, where the group assigns individuals to support others in the organizations.

This Center of Excellence idea is not completely new. The big difference here is that I am recommending it be treated like finance, legal or HR. Not in terms of being more of an operational role, but rather focused on a stand alone entity that embeds its own people into each group and pays for those people vs. having it be someone from a business group’s part time job. After talking to many companies about how they address social media in their organization, many wrestle with either a) individual groups doing their own thing or b) they only have a few hours a week of a business person’s time.

More on the center of excellence next time I blog here…

Oh yea.. Yes, your data jockey (s) should be part of this team too. : )