Sherman Mohr, CEO Understanding Data Mining in the Social Media Age - - PDF document

Sherman Mohr, CEO Understanding Data Mining in the Social Media Age I’m sharing this research and comments in association with a presentation made Nov 21st at the Association for Career and Technical Educators in Nashville, TN 2014. It’s slide orientation coincides with the presentation that exist on Slideshare.net at http://www.slideshare.net/shermanmohr/understanding-data-mining-in-the-social-media-marketing- age Intro Slide: Hi and welcome to Nashville! How many of you have visited Music city in the past? Have you noticed some changes? After 25 years here, I can attest, there are some rapid changes taking place. Changes that are likely fresh in your experience are our hotel rates. Wow! I did a study for an article I wrote on the Sharing Economy, specifically Uber, Lyft and Airbnb here in Nashville and found some interesting stats. A significant event coordinator in Nashville shared with me some time ago that our new Music City convention center increased our city’s capability to host events to the extent Nashville qualified for 77%

• f the conventions in the world. However, Nashville only truly qualifies for 32% of those conventions

due to a shortage of hotel rooms. This means, an online search for hotel rooms will generally turn up rates that are matching San Francisco and Manhattan. It’s far too true, I’ve researched the side by side comparison. How many of you go online to read a review prior to purchasing an item or having work done on your house or car? What are some of the ways you research services or products? Expedia, Hotels.com, Branded sites? 58% of Americans perform online research about the products and services that they are considering

• purchasing. Source: Jim Jansen, Pew Research Center’s Internet and American Life Project, 2010

Over 1 million people view tweets about customer service every week. Roughly 80% of those tweets are negative or critical in nature. Source: Touch Agency Bright Local states that trust in online reviews are believed by only 13% of the readership in 2014 while in 2011 it was 33%. We’re growing more skeptical. I couldn’t find the statistical source but it is said that people only believe 25% of what is shared with them by strangers. Mark Twain said “There are lies, damn lies, and statistics” with that in mind, I may have a 25% chance of your believing what I share with you today. Slide 2: This is when the internet and the online world of data became real to me. My university economics professor Walter Johnson, at Mizzou, cited terrifying specifics about the accuracy of missiles during lectures and I didn’t pay much attention. 27 years later I’m pulling up Google maps and I see the satellite images detailing what side of the house and office I happen to be located in or at least where my phone

Sherman Mohr, CEO is located. You’ll see how this relates to our data mining discussion in just a bit. Have you paid attention to what your phone provides to marketers? We’re going to discuss some of those details today. Our preferences, comments, sharing, and online community involvement is being analyzed. The analysis is so subtle that most participants don't even notice. I cover in this discussion how marketers are gathering, extracting, analyzing and then building advertising campaigns around social media

• participation. In some cases the data gathering is nefarious, those efforts get the headlines. Most of us

marketing types seek to exchange something of value in return for your giving up the details of your life. We want to play within ethical boundaries and perform better for our companies and clients. Slide 3: My motivation around data. My company, Shared Spirits, Inc. is a data gathering business model. Without boring you too much, allow me to explain my interest in the data gathering and data mining business. A couple of years ago, a friend and I were sitting at a bar having a drink and he asked if I’d ever seen a particular game on Facebook? I said I had and asked; Why? He said he wanted to do the same thing except in real life. In other words, he had a practical application

• f something that had been virtualized in the form of a game. In this particular case, the application

surrounded the ability to buy a person a drink from any venue in the world that happened to be in our network and send that drink to a contact so it may be received, redeemed, and tracked all on the smart phone. Why would we want to do this? It’s all about the data. Casual drinkers are some of the most affluent people in the market place spending over 1% of their annual incomes on adult beverages. 144,000,000 million Americans attest to having had a drink in the last seven days. The current way spirits, wine, and beer brands measures success is through case counts. Our app will provide brands a way to build relationships specifically with their buyers, all through our technology of course. As a result of this activity over the last three years, I’ve become far more interested in the way marketing messages are built into technology. I’m a believer in the premise that marketing now has to be delivered inside a utilitarian skin so to speak. Some image advertising will never go away of course but advertising that doesn’t serve to build real relationship along with the ROI will be missing the boat. Slide 4: What is data mining?

• Dr. Bruce Ratner reminds us that there is a problem with the definition of data mining. Data mining is

not at all well - defined. He states; “Today’s data mining is a high-concept: having elements of fast action in its development, glamour as it stirs the imagination for the unconventional and unexpected, and a mystic that appeals to a wide audience that knows curiosity feeds human thought. I googled “definition of data mining” and received a gross (vis-à-vis net) number of 40,300,000 definitions! (Curiously, the first entry was “Data mining is

Sherman Mohr, CEO derogatory … ”) To have a sound working assumption for the task at hand, I netted the “gross” google- number to 4,030. (This netting in and of itself, coincidentally reflects that the definition of google’s search engine optimization is also ill-defined.) Suffice it to say that data mining is an ill-defined concept, as 4,030 definitions are clearly not needed to unambiguously explain the concept. Unprecedentedly, the data mining concept early on (circa 1970s/early 1980s) did not have, and currently does not have the scholarly cause to take form. I conclude that data mining is an ill-defined concept. And, I declare that the net number of definitions suggests there are discipline-specific data mining definitions; but how many are there: 18, 36, 54, … ? [2] Regardless of an agreed number of disciplines, 4,030 divided by the “agreed-number” presents data mining proper or data mining discipline-specific as an ill-defined concept.“

• Dr. Ratner goes on to explain, “Today, statisticians accept data mining only if it embodies Tukey’s EDA
• Paradigm. (exploratory data analysis )[3, 4] They define data mining as any process that finds

unexpected structures in data and uses the EDA framework to insure that the process explores the data, not exploits it. Note the word “unexpected,” which suggests that the process is exploratory, rather than a confirmation that an expected structure has been. By finding what one expects to find, there is no longer uncertainty as to the existence of the structure. Statisticians are mindful of the inherent nature of data mining and try to make adjustments to minimize the number of spurious structures identified. In data mining the statistician has no explicit analytical adjustments available, only the implicit adjustments affected by using the EDA paradigm itself.” Tukey himself summed up his definition of EDA as follows: "If we need a short suggestion of what exploratory data analysis is, I would suggest that: 1. it is an attitude, AND 2. a flexibility, AND 3. some graph paper (or transparencies, or both)." https://www.stat.berkeley.edu/~brill/Papers/EDA11.doc Traditional marketing and sales researchers view sales data in macro-economic ways. In other words, sales and marketing pros from traditional schools of thought don’t always believe in the digital view of

• ur world. They tend to remain focused on the print, TV, billboard, and radio versions of the narrative

that companies want shared. I classify traditional marketing as pretty much anything that is “pushed”

• nto the listener or reader. If the audience wasn’t asked to participate in the results or the campaign in

some proactive way, that’s a sure sign that the advertising was traditional. Slide 5: Data gathering in traditional marketing and traditional market research. Traditional marketing research often involves assessing the overall market for a good or service, surveying consumers about their likes and dislikes, and conducting focus groups to gauge consumer responses to a new product. The growth of information technology has transformed market research, with a growing number of analysts learning about consumer preferences and buying habits by mining massive sets of quantitative data and employing complex algorithms to uncover patterns and correlations that enable more effective marketing. While data mining emphasizes extracting predictive information about customers and sales from large databases, traditional marketing research focuses on identifying factors that influence the buying decisions of households and organizations. Relevant data is then collected, often through sales data,

Sherman Mohr, CEO surveys and focus groups, according to Professor Roger A. Kerin, author of the textbook "Marketing." Traditional market researchers identify an opportunity, collect the needed information, then formulate an appropriate sales strategy. Data mining relies on information that is already available. http://smallbusiness.chron.com/examples-data-mining-vs-traditional-marketing-research-24716.html Slide 6: Data Mining features and examples for our purposes today.. Data mining uses statistical techniques to discover correlations between different factors and variables in large data sets, according to Yale University Professor Ian Ayres, author of "Super Crunchers." These data sets are often measured in terabytes, a terabyte being equivalent to 1,000 gigabytes. Data mining

• ften gives businesses enormous amounts of information about their customers' behaviors and buying

habits, enabling them to more effectively market their goods. Ayres cited online retailer Amazon.com's feature that tells a potential customer that people who like

• ne particular product also like certain other items as an example of marketing through data mining.

You can now purchase software that allows this to take place in your shopping cart instantly. It comes as standard equipment is most shopping carts today. In another example, credit card issuer Capital One generates for its customer service representatives a list of products and services that a consumer is likely to buy based on characteristics of the customers' credit card accounts. You may recall the bad press Target received when it went a little too far in its interpretation of data gleaned from purchases and how they started advertising to teen agers who they assumed were having babies. In the Colorado election most recently, the RNC began utilizing demographic data gleaned from social sites and online data and mashed it up with traditional data and old school door knocking. There were 500 paid staffers with iPads moving through the streets. By election time, there were 1.25 million doors already knocked on with a specific target being low propensity to vote Republicans. http://www.chron.com/default/article/GOP-wins-with-mix-of-data-mining-door-knocking-5879919.php We see this now most routinely in marketing through online search. You enter a search term looking to buy something. You may or may not buy it but the next time you login to Google or Facebook, you’ll likely see an ad for that particular item. Slide 7: Hearts and minds are won in relationships through community, conversation, and education. Simply put, digital technologies have caught fire because they address three core human needs: the need for connection with other humans, the need for self-expression, and the need for exploration. Wrapped up in the seductive ribbon of convenience, there has never been a better formula for consumer engagement. Understanding the human side of the digital revolution will be a key success factor for businesses trying to compete in a digital world. - See more at:

Sherman Mohr, CEO http://www.economistgroup.com/leanback/consumers/at-kearney-consumer-engagement-3-roles- marketers/ Steven Covey stated in 7 habits of highly effective people…”Seek first to understand and then be understood.” This is a marketing mantra for the most successful companies. They have become great listeners of their audience, listening, facilitating the conversation, and providing their customers and prospects opportunities to take the floor so to speak. Every time the conversation flows, data is generated that helps the marketing department do more effective work. “The new marking equation? Engagement = Data” Sherman Mohr http://www.atkearney.com/consumer-products-retail/featured-article/- /asset_publisher/S5UkO0zy0vnu/content/want-to-engage-consumers-in-a-digital-world-don-t-think- digital-think-human/10192#sthash.FpRG51Hl.dpuf The author of this great article on engagement, Hana Ben-Shabat, states that most users of social networks fall into these categories adding that; “Going forward, leading companies will play multiple roles that transcend the transaction.” They will have to provide for the following three types of people. Hana Ben-Shabat in quotes. Slide 8: “The community builder. Whether online or offline, the notion of community has always done miracles for businesses. From the cozy environment of a Starbucks café and the communal table at your local restaurants to the online communities of Burberry and Nike+, rallying consumers around a common interest, idea, or value gives them reasons to come back, engage, and advocate for a brand. Good community builders are good entertainers; like every gracious host they know when to be at the center and when to step back and let their guests take center stage.” In my case it was initiated by my involvement with Meetup.com. Meetup features 177,000 “meetups” averaging nearly 500,000 monthly meetings. I started running or organizing a meetup or group around entrepreneurship seven years ago. This online platform called Meetup.com allows one to organize groups around almost any topic and establish meetings, workshops, activities, and more around the

• topic. The company aggregates anyone with an expressed interest in the topic and shares the meetup

and the opportunities with those that are interested. What this allowed me to do was build community around a topic. I provided speakers, programs, and more and the group has grown to over 1200

• participants. It truly was the gateway tool for me as it pertains to community and my entry into the

serious work of social media and conversion. The early work around data mining I was exposed to came from Meetup.com. Their ability to target specific influencers and their groups was my first exposure to targeted social media marketing. For nearly two years, they wove advertiser dollars into some of our Amazon payment accounts as in incentive to run great groups.

Sherman Mohr, CEO Slide 9: The second quality that Hana Ben-Shabat suggests is needed by social media participants and the companies that serve them is to provide for conversation friendly platforms. You have to have room for the conversationalist. “The conversationalist. To drive self-expression, one must first be willing to have a conversation, be

• pen to feedback, and take risks. Having a Facebook page means allowing consumer sentiment, positive
• r negative, to be there in the open. The idea of “brand control” is slowly becoming obsolete, but as

brands “lose control” they “gain engagement.” Good conversationalists are provocative, encourage

• penness, and ignite creativity that ultimately enriches the community and the brand.”

If the brand is willing to allow the conversationalist the floor, there are dozens of ways to measure the data and gauge what is being said. Companies and organizations of all types are beginning to utilize tools that allow for the real time listening of the audience. Check out Mention.net for ways to monitor conversations around your brand or organization across social networks in real time. Hootsuite is a powerful monitoring tool as well and the venerable Google Alerts still renders results from across the web. I recently took part in a Twitter Chat with a tequila brand. This real time conversation on Twitter was prompted by an email from the brand owner. I popped onto my phone, ask a couple of questions and took part in a conversation surrounding local places to obtain their brand, recipes and more. I got retweeted twice and picked up three new followers through the twenty minute period. One of my favorite web applications was built by BNL consulting of DC. This link is here: http://apache.bnl-consulting.com/stage/TwitterStreamDashboard/ The Twitter Dashboard used for real time marketing purposes by an insurance firm to gauge flu symptoms across the country. A tool similar to this is being used by Clorox as well to modify delivery schedules to retailers where Twitter and social media traffic call for the highest likelihood of sales increases. Step One: Enter a series of search terms Step Two: View the stream from Twitter that is in real time and reflective of all who posted Tweets on that topic or using that word. Step Three: Enjoy your visual map on the Twitter cloud that shows you where the action is. You can then begin to target offers, ads, and more, all based on what your real time results suggests is happening.

Sherman Mohr, CEO Screen Grab: Slide 10:

Sherman Mohr, CEO Slide 11: Third, individuals within platforms want to explore. They want to be educated or educate others. “The educator. To satisfy consumers’ curiosity and need for exploration, companies are increasingly assuming the roles of educator and storyteller. From teaching consumers about their brand and its history to offering “how-to” videos for cosmetics or recipes for food and drinks, companies are seeking to develop new and interesting content to bring consumers back to their stores or websites. “ On the “How to” front: 25.32% of the 1.2 million apps in the Apple App store fit in this category. A full 29.62% serve to allow exploration in areas around medicine, food, drink, travel, health, and more. Do any of you use MyFitnessPal or SuccessWiz? Slide 12: Tremendously popular platforms are being provided as vehicles for education. Udemy.com is one such

• example. You can choose classes from a list of thousands. Every time you search, select, and finish a

course, you’ve offered up digital information allowing for marketing professionals to utilize the social nature of taking a digitally delivered course to more easily model a marketing experience to you. Would you be willing to part with some personal information to take a course? If you received a better price for trading some personal details or shopping preferences would it make a difference? Slide 13: The Three Takeaways We’ll continue down the path toward our takeaways with these three points. What Privacy? - The Trade Off - Trust Me. All three points play an important role in why people offer up their data thereby allowing those of us in the data mining world more access than ever before. Slide 14: A new study conducted by Accenture found that the majority of consumers in both the U.S. and UK are willing to have trusted retailers use some of their personal data in order to present personalized and targeted products, services, recommendations and offers. The study, which surveyed 2,000 U.S. and UK consumers, found that while 86 percent of those surveyed said they were concerned that their data was being tracked, 85 percent said they realized that data tracking make it possible for retailers to present them with relevant and targeted content. Read more: http://www.digitaltrends.com/social-media/why-consumers-are-increasingly-willing-to- trade-data-for-personalization/#ixzz3I7ZQWhi6 When consumers were asked to choose between personalized shopping experiences based on their past consumer behavior, or non-personalized experiences in exchange for having retailers not track their data, 64 percent of respondents said they’d prefer the personalized experience. Read more: http://www.digitaltrends.com/social-media/why-consumers-are-increasingly-willing-to-ade-data- for-personalization/#ixzz3I7Z45OOx

Sherman Mohr, CEO But while 73 percent of consumers surveyed said they prefer do business with retailers who use personal information to make their shopping experience more relevant, the vast majority of consumers (88 percent) think that companies should give them the flexibility to control how their personal information is being used to personalize their shopping experience. Read more: http://www.digitaltrends.com/social-media/why-consumers-are-increasingly-willing-to-trade- data-for-personalization/#ixzz3I7ZBmh7L Slide 15: Consumers will trade a lot for what they want. "It is crazy what people were willing to give me," said artist Risa Puno, who conducted the experiment, which she called "Please Enable Cookies," at a Brooklyn arts festival. The cookies — actual cookies — came in flavors such as "Chocolate Chili Fleur de Sel" and "Pink Pistachio Peppercorn." To get a cookie, people had to turn over personal data that could include their address, driver's license number, phone number and mother's maiden name. More than half of the people allowed Puno to take their photographs. Just under half — or 162 people — gave what they said were the last four digits of their Social Security numbers. And about one-third — 117 people — allowed her to take their fingerprints. She examined people's driver's licenses to verify some of the information they provided. http://www.propublica.org/article/how-much-of-your-data-would-you-trade-for-a-free-cookie http://www.longislandpress.com/2014/10/05/how-much-of-your-data-would-you-trade-for-a-free- cookie/ Slide 16: Technology now permits an individual to trade something they possess, i.e. an online identity, for a better value proposition. Social technology and social marketing is working best when users are receiving value in trade for the

• message. “The best apps inform more than sell.” Bryan Pearson

http://www.fastcompany.com/3026985/leadership-now/essential-tips-for-creating-apps-people-will- actually-use Forty-two percent said they prefer apps that help them gain access to discounts and lower prices, and an equal percentage want apps that help them simplify or organize their lives. This tells us that data mining in social media is facilitated by smart marketers building utility into their apps. The utility of something makes data sharing by consumers seem okay. Examples would include Expedia, Fandango, Phonto, Pandora and more. http://www.corporate-eye.com/main/good-news-for-mobile-advertising-in-apps/

Sherman Mohr, CEO A recent study found that more than 65% of mobile users would not mind seeing relevant mobile ads within the apps they use as long as advertisers provide some type of proof that users’ privacy is well protected - See more at: http://www.corporate-eye.com/main/good-news-for-mobile-advertising-in- apps/#sthash.0Cdleu2K.dpuf This is relevant because people are trading highly personal information with every app download and log in. Data from your Open ID’s, social media profile info, location Info, and increased data on your preferences becomes more useful to marketers with every login and use. What are some of the apps you use as a utility or as entertainment or information sources? Anyone in the audience use an app like Fandango? Pandora or Expedia, Flipboard? Pinterest? Slides: 17, 18 and 19 and 20 Data enhancement is what one company calls it. They also coined the term Social Profile Genome. Here are some examples of what we see as marketers when we go to place adds on Facebook. The FB Advertising tool allows us to see data people have provided relative to details associated with relationship, education, work, finances, home, ethnic affiliation, generation, parents, politics, and life

• events. The headings allow us to click and get extremely granular.

In addition to these examples, I have tools that allow me to download the user ID’s of all participants in Events, Groups, and Pages. Those folks that have their privacy settings set to prevent it can’t be

• retrieved. The premise is that if someone joins a group or RSVPs for an event, they are more likely to be

positive to advertising. Slide 21: Trust is the key component. Trust in complete strangers is now common place and a bit of a risk. Tools and sites like Uber, Lyft, AirBnB as well as Fivr and others have us more used to sharing personal info with strangers than ever before. http://www.sfgate.com/bayarea/article/Sharing-economy-means-putting-your-trust-in-5784060.php Community "pressure" plays into trust. Friendship Trumps Research! Google research says nearly half of us consult friends and family before purchasing. 92% of people use social media to connect to friends and family. http://blog.blucarat.com/gallup-social-media-poll-buyers-trust-people-not-brands/ http://arxiv.org/pdf/1305.7440.pdf How friends influence us on Social Media https://blog.bufferapp.com/social-media-friendships Studies show that 70% of consumers say they look at product reviews before making a purchase, and product reviews are 12x more trusted than product descriptions from manufacturers. https://blog.bufferapp.com/the-ultimate-guide-to-social-proof

Sherman Mohr, CEO Slide 22 and 23: A closer look at the power of influence among friends is found through Ninja Metrics. Their work suggests a social network perspective that requires abandoning some of the core assumptions in traditional analytics. “Data about relationships between individuals are often more important than data about the individuals themselves.” Ninja Metrics Wisdom Individual nodes can be directly connected, indirectly linked, or completely unconnected from other

• nodes. Nodes are defined as individuals.

Some nodes have considerably more connections than other nodes. Some parts of the network clump together into tightly-knit clusters. Traditional analytical approaches take each individual user as an atom, separate and independent: my height doesn’t depend on the height of my close friends. In many contexts this individualistic assumption is an appropriate. But in the vast majority of applications, it’s incomplete or just wrong. A social network perspective says my connections to others influence my own behavior: research has shown that my weight is actually influenced by the weight of my close friends. Ignoring these relationships obscures important processes of how information and influence travels between individuals over these relationships. The data to be collected for social network analysis must reflect observations about relationships. Who happens to be friends with whom? Who teams up with whom? Who buys what? Who plays where? These types of relationships are pervasive in many types of data but the relational implications are often overlooked. Trust is the key component. Community "pressure" plays into trust. Friendship Trumps Research! Slide 24: This means what to you as an educator? Everything that is required to build a new data scientist, thinker, marketing, or strategists begins with

• you. The technical skills, the critical thinking skills that lead young people to ask the right questions and

likely the most important skill of all, the sensitivity toward an ethical view of how data will be gathered and leveraged. Data analysts’ positions are slated to rise 3 to 7% over next 8 years. http://degreedirectory.org/articles/Data_Analyst_Career_Definition_Job_Outlook_and_Training_Requir ements.html The McKinsey Global Institute, the business and economics research arm of McKinsey & Co., has predicted that by 2018 the United States could face a shortage of between 140,000 to 190,000 people with deep analytical skills, as well as a shortage of 1.5 million managers and analysts who know how to use the analysis of big data to make effective decisions. http://www.forbes.com/sites/emc/2014/06/26/the-hottest-jobs-in-it-training-tomorrows-data- scientists/

Sherman Mohr, CEO Slide 25: Who benefits? Those interested in data have a world of opportunity ahead of them. Tam Harbert of ComputerWorld.com describes the future leaders in this field - "These are people who fit at the intersection of multiple domains," he says. "They have to take ideas from one field and apply them to another field, and they have to be comfortable with ambiguity. He goes on to say, That said, most of the jobs emerging in big data require knowledge of programming and the ability to develop applications, as well as an understanding of how to meet business needs. The most important qualifications for these positions aren't academic degrees, certifications, job experience or titles. Rather, they seem to be soft skills: a curious mind, the ability to communicate with nontechnical people, a persistent -- even stubborn character and a strong creative bent.” http://www.computerworld.com/article/2493991/it-management/big-data-means-big-it-job-

• pportunities----for-the-right-people.html?page=2

“By 2015, 4.4 million IT jobs globally will be created to support Big Data, generating 1.9 million IT jobs in the United States,” said Peter Sondergaard, senior vice president at Gartner and global head of

• Research. “In addition, every big data-related role in the U.S. will create employment for three people
• utside of IT, so over the next four years a total of 6 million jobs in the U.S. will be generated by the

information economy.“ http://www.itbusinessedge.com/slideshows/big-data-is-creating-big-jobs-4.4-million-by-2015.html Slide 26: In Summary

• 1. Data aggregation is ubiquitous and pervasive.
• 2. We utilize social media for community, conversation, and education.
• 3. There is little privacy – we don’t care..much.
• 4. We’ll trade a lot for a little.
• 5. We trust friends more than anything or anybody.
• 6. There is great opportunity for leadership.
• 7. There are great opportunities for future positions

Data mining occurs in ways you would never expect. Data is used in ways that one would have found inconceivable a short five years ago. The world of data mining, analytics, and data science does call for some programming skills, however, the ability to marry data to visual dashboards and make a business case for strategies or against strategies is where the greatest value will be delivered.