Making Sense of Big Data
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Data availability is only as strong as the conclusions marketers can draw from it. Marketers nowadays have access to larger pools of data and metrics than ever before. But data availability is only as strong as the conclusions marketers can draw from it- which in turn, are only as useful as the change they can affect based on those conclusions. Like this presentations? Upcoming webinars and videos on brighttalk.com/channel/14093/hippo-cms
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Making Sense of Big Data
- 1. We’ll be with you shortly. Get in touch via @oneHippo
- 3. BIG DATA IS A QUESTION – NOT AN ANSWER. The opportunity for marketers is we can now listen for any kind of topic or subject, across any social network. Marketers can analyze that and use it to deliver better engagement. The key is in how you actually do that analysis. How do you make the data small again?” Gordon Evans VP of Prod. Marketing, Salesforce.com
- 5. “Patternicity: the tendency to find meaningful patterns in both meaningful and meaningless noise” - Michael Shermer
- 9. “Patternicity: when the cost of making a Type 1 Error Is Less than making a Type 2 error”
- 11. There is no correlation between the number of interactions and the depth of consumer relationships. CEB - 2014 “there’s this whole notion of being able to identify and convert people in a different kind of funnel – this is done through engagement focused experiences.” Gordon Evans VP Prod Marketing, Salesforce.com
- 12. “It’s always the same mistake: to believe that to see the logical pattern of social facts, you must extract yourself from the details, go upward until you embrace vast landscapes panoramically”
- 14. Data is always embedded in a context. Our Data has a bias to it precisely BECAUSE it is our data.
- 15. Being Right isn’t always right
- 16. Data knows what IS – not what WILL be
- 17. “We have all this Data that we can derive meaning from, but it’s only half the story. The other half is the emotive needs of that customer. Their aspirations, fears, dreams, goals etc..” Wilson Raj Global Director Customer Intelligence, SAS
- 18. Data isn’t something that is always meant to make the consumer experience better. Sometimes it’s something that ALLOWS US to make the consumer experience better.
- 19. Beautiful Data… A home for digital experiences and data Julie Fleischer – Director Data, Content & Media 2 Trillion pieces of data Making the company smarter - develop meaningful advertising strategies
- 20. “In the coming decade, marketing will be re-engineered from A to Z. Marketers will need to rethink fundamentally the processes by which they identify, communicate and deliver customer value.” Philip Kotler, 1999 Kotler on Marketing
- 21. “high performance brands both leverage what they know about customers - and develop BREADTH of optimized touch points to create the “total experience” “Share of Wallet” to “Share of Experience” “Motorola Solutions, a pioneer of a new framework, used SAVE to guide the restructuring of its marketing organization and its go-to-market strategies…” Eduardo Conrado VP of Marketing & IT
- 22. 1. Data always EMBEDDED in a CONTEXT we need to understand our bias, and understand the gaps. 2. Signal & Scale – There are some things that Big Data will never be able to tell us. Smaller is sometimes better 3. Using content technology to help us listen first, see what our existing patterns are for the data that IS – instead of always pre-supposing that we know the answer..
Editor's Notes
- So… as we start to think about Data and marketing and content – we need to realize that Big data is a question – not an answer… We already know that the roles of the CMO and the CIO are evolving. We also know that the use of content and data to enhance consumer experiences is one of the primary drivers of this evolution. Big Data just might be the big idea that hastens the alignment of this purpose; but just like content, it won't deliver it on its own. Advancing our success with data-driven content creation will only come with the evolution of a new role in the organization What is new is that the quantity of content being created, the capabilities of technology, and the rate of change in business have all increased exponentially. As Gordon Evans, Vice President of Product Marketing at Salesforce.com, said when we spoke with him for this article, "The opportunity for marketers is we can now listen for any kind of topic or subject, across any social network. Marketers can analyze that and use it to deliver better engagement. The key is in how you actually do that analysis. How do you make the data small again?"
- In a recent study, the CMO Council found that two-thirds of both marketers and IT executives now feel Big Data can surface customer-centric business opportunities. But, simultaneously, half of both groups believe that functional silos still prevent the accumulation of data, and therefore hinder any kind of customer-centric strategy. At the Content Marketing Institute, we've certainly observed this happening at large enterprises. Basically, marketers are reading the scads of articles and research reports about how Big Data might be the best thing since sliced bread; yet, they still have no idea how to "bake" it.
- In 2008, science historian Michael Shermer coined the word "patternicity." In his book, The Believing Brain, he defines the term as, "the tendency to find meaningful patterns in both meaningful and meaningless noise." He went on to say that humans have the tendency to "infuse these patterns with meaning, intention, and agency," calling this phenomenon, "agenticity."
- So, as humans, we're wired to make two types of errors that have relevance here: Type-1 errors, where we see the false positive — a pattern that doesn't really exist. Type-2 errors, where we see the false negative — we fail to see the real pattern that exists.
- Example… Walking down the street at night… And there’s a click and a dark figure in the dark alley that you pass…… Your choice is to cross the street and avoid the alley or not… If you cross the street and it was a cat standing on top of a garbage can… No harm no foul… But if it was a guy with a knife about to take you out… You now win the Darwin award… And you’re weeded out… Patternicity is when the cost of making of making a type 1 error – or seeing a pattern that isn’t there - is less than making a type two error…. In other words – the cost of me crossing the street and NOT getting a knife in the chest is LESS than me believing that the dark figure is a little old lady and doesn’t mean me harm…
- Today's marketers are particularly prone to patternicity and making Type-1 errors. Because so many marketers use analytics to serve as a "proof of life" in support of the particular strategy they've put forward, their measurement methodologies have become predicated on making sure they capture anything that looks like success. In other words, a data-driven marketing mindset has pushed many marketers into scrambling to seeing patterns of success that may or may not be there. We see increased time-on-site and call it engagement — without considering that it may actually be due to frustration because users can't find what they're looking for. We see more "likes" as an indicator of success on Facebook, disregarding that people actually have to "like" your page before they can comment on how much they hate you. We see the articles noted as “most popular” on a website has having more weight because their more popular – disregarding that the reason they may be popular is that everyone is linking to them as an example of how ridiculous they are… This is truly the reason of the “all publicity is good publicity” mentality./. This tunnel vision has marketers focused on using data solely to optimize transactions instead of viewing it as insight on how to deepen engagement — as evidenced by a recent IBM study, "From Stretched to Strengthened," which found most CMOs use data in hand to optimize transactions and not to deepen the relationship with consumers.
- We do this all the time right…. We focus on creating more and more transactions with content and our consumers thinking that it increases our relationship – when in fact it’s the opposite…. In fact a corporate executive board found exactly that… That there was NO correlation between the number of interactions and the depth of relationship with consumers…. Gordon Evans from Salesforce.com further framed this disconnect by saying, "There's this whole notion of being able to identify and convert people in a different kind of funnel — where you take them from strangers to friends to fans to advocates. That's all done through engagement-focused experiences." Put simply, marketers have got to start looking for meaning, using content and data to deepen the relationship with consumers, rather than always focusing on more transactions. In other words – how do we use TECHNOLOGY to first Listen to what is REALLY happening with individuals… – make it smaller and more manageable – rather than always looking at the Aggregate as a means to develop ever more AVERAGE strategies… REALITYCHECK…. QUESTION I could pose it back to Sonija and I would say something like “So - this idea of focusing on more likes… I know you guys have been strong proponents of using technology to first LISTEN to what’s happening to help develop personas and what’s working on the site…. does this ring true? “ Sonja can then respond and we can discuss a little bit about the idea of developing personas and their interest around their REAL consumption and use of content, rather than what we ASSUME it to be…
- Marketers – really humans… already pre-disposed to find patterns Been so for a long time… Gabriel Tarde 1898 - "Always the same mistake: to believe that to see the logical pattern of social facts, you must extract yourself from the details, go upward until you embrace vast landscapes panoramically"
- Big Data is hard… And challenging – and even Google - with as much info as it has gets it wrong… 2013 flu trends overestimated the flu by as much as 50%... Why because the algorithm was slightly off – and the input is searches for flu – vs actual cases of it – which could be reflected in preparation rather than actual cases…
- Data is ALWAYS embedded in a CONTEXT" WE need to understand that our data has bias to it and understand the gaps… . XI. Think about our own data for a minute… The one that Marketing is supposed to be so great at… Our Web traffic data… This data only tells us What our visitors DID…. It doesn’t tell us what they DIDN’T DO..
- Target used its data to send marketing information – trying for a better experience for its custome – who was purchasing all the things that would indicate a pregnancy… They ended up sending information to the girl’s dad…
- This is the key… Our data right now… It knows what is… Not what will be…. This is where we need to use Data that we gather – whether it’s analytical data, or explicit data that a customers gives us – and use it to derive insight on how we might better delight that customer – not make yet another average transaction… .
- I call this the Marriage of the rational and the emotional Wilson Raj, the Global Customer Intelligence Director at SAS, frames the issue quite elegantly, by explaining, "The data, while powerful, is only half the story. The other half is an understanding of the emotive needs of our customer. What are their aspirations, fears, dreams, desires, etc.?" So how do we start to balance both of those things and extract value in our content creation efforts? Wilson advises, "CMOs must ask, 'Do I have the data?' If the answer is 'yes, but I can't get at it," [they] don't have a Big Data problem, [they] have an analytics problem. But if the answer is 'no,' then the CMO must start to examine where they can get it, and add in the missing linkages." And this is important for us as marketers, because in order to properly ask, "Do I have the data?" we must first answer this question: "What small data is needed?" QUICK BREAK NUMBER TWO - SLIDE 16 “This is something that I know you’ve dealt with before Sonja…. This idea of getting at the RIGHT data… Whether it’s CRM or Third Party data, or web analytics….. Don't you find that your clients are succeeding more with the RIGHT DATA.. and asking the right questions…. Then we can talk quickly about how this data accumulation should be a process…
- We also have to realize that the data we’re capturing isn’t something that makes the consumer experience better… but something that allows US to make the consumer experience better…
- But hopefully we can do both…. And Kraft is a wonderful example of that…
- Creating experiences….. Changing our organizations and our approach to content and technology….
- Marketers must understand the data we have should always be embedded as part of a context. Our data has inherent biases precisely because it is our data. For Big Data to have any value beyond the information we already have, we will need to move beyond using analytics as a method to prove success or ROI, and instead use data and measurement as a method to improve the continuing process by which we derive more meaningful insight and develop deeper relationships with customers. Yeah, we marketers have been talking about this for years — but this time we really need to do it. We will need to add new roles to our teams (ones that, I would argue, don't exist yet) so that we are equipped to peel back the layers of Big Data and make it small. These players aren't necessarily scientists or mathematicians, but they will have the necessary talent and ability to ask advancing questions of our data, our customers, and influencers, and apply the art of listening, conversation, and synthesis to transform facts and results into meaningful insight. We need to change our approach to content management – and Use content technology to help us listen first… Understand what the existging patterns are for what IS – instead of pre-supposing that we know that answer…. We need people who can help us ask advancing questions of the data and then help us to develop smarter strategies about how to create those better experiences… Who are these people? The above qualities sound like a lot like those of journalists, or perhaps talented researchers? Or maybe our data scientists must add new skills? Perhaps this may even be the future role of the influence marketer. Quite candidly, the road has yet to be paved. What I do know is that if Big Data is to mean anything more to content marketers and creators than just a big box of nonsense and distraction, the "Manager of Meaning" role must come to pass.