New White Paper by Jim Sterne and Anametrix - From Data Scientist to Data Artist


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Digital luminary Jim Sterne, founder of the Digital Analytics Association, explores the new and compelling role of “data artist” in business. He believes a “data artist must have a firm comprehension of hard science, a sound understanding of business goals and processes, a penchant for creativity, and a talent for communication – a very rare combination.” In this exciting white paper, he explores:

The differences between the data scientist and the data artist;

The need, value and availability of today’s powerful, flexible analytics tools, which are now affordable;

Moving beyond reports to true analytics without requiring a team of technologists, mathematicians and data analysts;

How the U-T San Diego, a top-25 news publisher, grew readership and revenue using a powerful analytics platform, bucking trends to become a profitable news business.

Learn more about data artists and use analytics to gain profound improvements in revenue and profitability in your business.

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New White Paper by Jim Sterne and Anametrix - From Data Scientist to Data Artist

  1. 1. White Paper From Data Scientist to Data Artist Data Sculpting to Shape Business Insights by Jim Sterne
  2. 2. EXECUTIVE SUMMARY Discover the new role of data artist and understand the need, value and availability of powerful, flexible and affordable analytics tools that do not require an advanced degree in mathematics nor a team of information technology experts to use. Learn about the professional requirements of a data artist and how to change corporate culture with the right analytics tools in the right hands. Read about the exploits of a news organization that used those tools to change its culture and become profitable. The Data Artist and His Tools A great data artist needs a clean dataset, powerful yet uncomplicated analytics tools and the skills to discover – and deliver – meaningful, valuable insights to an organization. What is a data artist? To answer that, we need to define scientist, data scientist and artist. A scientist is responsible for understanding and advancing the properties of materials and/or processes. A data scientist is responsible for understanding and advancing the nature of data, its collection methods, and the algorithms for processing it. An artist is responsible for creating something new that delivers original insight and evokes emotion. A data artist is responsible for delivering fresh insights from data to help an organization meet its goals. This is the person who takes the output from decision-support systems and turns it into consumable theories, postulates and hypotheses that can be tested and applied to the business. A data artist uses data streams and advanced analytics systems in the same way a regular artist uses oil and brushes, stone and chisels or wood and carving knifes. A data artist must have a firm comprehension of hard science, a sound understanding of business goals and processes, a penchant for creativity, and a talent for communication - a very rare combination. Page 1 of 11
  3. 3. Case in Point - A Data Artist and Clear Goals When the new owners walked into the San Diego Union-Tribune (now U-T San Diego) in 2009, they made their goals abundantly clear: increase readership (product), increase advertising (revenue) and rigorously use analytics to make it happen. Joseph Gordon, Director of Research at U-T San Diego, wired together all the data he could get his hands on to help grow readership, inform advertisers and support the editorial and sales teams. He also had a two new arrows in his quiver: a very powerful analytics platform from Anametrix and a management mandate. U-T San Diego put up a paywall in 2012 and experienced less than half the loss of pageviews seen at other publishers that followed a paid-subscription strategy. Content consumption increased 10 percent the next month and has continued to increase, despite the paywall. U-T San Diego is a very rare entity: a profitable news organization. Continue The Art of Analysis - Understanding Raw Material With more and more data streams becoming available, understanding their properties is challenging, but necessary. Survey results require an in-depth knowledge of exactly what questions were asked, how they were asked and of whom they were asked. It’s imperative to know how the subjects were selected and whether the interview happened in person, on the phone, via Twitter, etc. Advertising data is voluminous and continuous, and it involves a sophisticated familiarity with ad servers, ad networks, branding, and third-party metrics providers like Nielsen and comScore. Web behavior data requires a comprehensive understanding of whether the data comes from log file analysis, page tagging or both. A solid familiarity of cookie behavior (duplication across devices, confusion between multiple users and deletion frequency) plays a critical role in ascribing veracity to summary reports and aggregated data. A secure grounding in userinterface design across multiple devices is necessary for proper interpretation of customer conduct. Search data comes with its own question marks as keyword reports arrive with an ever-increasing percent shown as “not provided” thanks to Google’s new methods. Social media metrics are still so new that there is nothing remotely standardized about enumerating mentions, much less quantifying sentiment polarity. A fine arts master might dedicate an entire career to working with one type of wood or one paint medium. A data artist must be a master of all digital media –ad networks, email campaigns, YouTube channel measurement and more – to create valid insights worthy of using as foundations for business decisions. Page 2 of 11
  4. 4. Using these raw materials to create a workable representation of the marketplace and customers, data artists must understand the strengths and weaknesses of each data stream. As sculptors must know the maximum stress a given material can tolerate, data artists must know how much weight to place on a given type of information for their organizations: • Transactions are more reliable than attribution models. • There is a stronger correlation between social media mentions by close friends and celebrities and purchases, than between viral video views and brand affinity. • Social graphs and interest graphs reveal more psychographic information than mailing address. • Location data is more revealing than Facebook Likes. Like an architect, the data artist is designing a structure many will rely on and that must reliably support the anticipated load. With a firm grasp of the nature of various raw data streams, our data artist relies on the tools of the trade to transform mere data into information − and then into insight to support business decisions that drive P&L. The Art of Analysis - Mastering Tools The technical advances that let us collect and store more and more data brought new challenges in analyzing that data. The higher volume of a wider variety of data – showing up faster than ever – are the hallmarks of Big Data. Understanding the raw materials (the data) is even more difficult because each data type engenders a variety of tools dedicated to the capture and analysis of that particular dataset. Case in Point - A Data Artist and Flexible Tools U-T San Diego started by internally publishing near real-time readership data for all of its writers to see, thereby creating a competitive environment while still maintaining high journalistic (editorial) integrity. The news organization also started publishing near-real-time advertising data for all of its advertisers to see, thereby allowing advertisers to optimize their ad spend, while maintaining high publisher integrity. This way, authors (and management) know exactly which articles get attention, and advertisers know exactly which ads get noticed. None of this is something that comes out of a box. The Anametrix analytics system used at U-T San Diego is flexible, powerful and straightforward enough that Joseph could exercise his data creativity to shape it to his vision. Continue Page 3 of 11
  5. 5. It’s a significant challenge bringing together data from an assortment of websites and trying to correlate it with data from a multiplicity of ad networks, social-media platforms and third-party data providers. The data has to be extracted from each proprietary system, re-structured (transformed) so that it can be correlated and then loaded into the ultimate analysis tool where creativity can flourish. Many still suffer from the legacy of batch processing where data is extracted transformed and loaded once a day. The next 24 hours is spent analyzing yesterday’s news. In the last 20 years marketing has changed to more closely resemble the stock-market trading floor than the voting-booth outcome tally. Streaming customer behavior is a competitive advantage for those who can cash in on it. Sadly, the creative side of the job is not the daily experience of the vast majority of data workers and scientists. Their ability to flex their artistic muscles is severely cramped by the need to perform the mundane task of getting reports out the door. Reports Are a Destination - Analytics Is a Journey Let’s switch allegorical gears for a moment from art to transportation. This will allow us to more easily consider the most common problem in analytics today. A successful city bus offers enough predetermined destinations to service as many potential riders as possible. Like a city bus, digital-analytics tools strive to offer enough predetermined reports to service as many potential clients as possible. Standard analytics reports might be very flexible (as a bus is flexible in the number of times it stops at a given location), but both are only valuable to commuters, not to explorers. Digital analysts who are tasked with cranking out periodic reports are commuters. For them, standard reports, with slight modifications, produced on a regular schedule, is sufficient. Digital analysts who want to make a significant contribution to their organization by honing their analytics artistry are explorers. Here, the goal is to continually push known boundaries to break new ground and discover new insights. The city bus simply does not provide sufficient flexibility to support an explorer intent on investigating uncharted territory. Unfortunately, the more sophisticated means of taking these journeys have their drawbacks, as well. A helicopter is wonderfully flexible. With six degrees of freedom, it can go anywhere and land on almost any flat surface. Unfortunately, it requires months of training, the backing of a sophisticated ground crew and is prohibitively expensive. What works? An automobile that, while it cannot fly and is more expensive to operate than a city bus, offers unprecedented flexibility, autonomy and range. Like buses and helicopters, digital-analytics tools seem to come in two flavors. Some are very straightforward, low cost and great for general reporting. Others are wonderfully powerful and flexible, but require two Ph.D.s to operate and are impractically expensive. Page 4 of 11
  6. 6. The ideal analytics tool would offer enough flexibility to allow for true analysis – not just reporting – without requiring a team of technologists, mathematicians, data scientists or investors. Case in Point - A Data Artist and Autonomy When asked, Joseph points to the typically desired qualities of the toolset he uses. Anametrix is highly customizable but it’s also easy to use. And it’s at a far better price point than the other Big Data web analytics and marketing optimization tools out there and doesn’t take entire teams to run it. Anametrix had a lot going for it from the start, but I have the option to customize - which I need so I can constantly tweak what data is collected, how it gets brought together and how it gets reported out. That’s a big change from previous systems where I could submit change recommendations to the vendor or modification requests to my own IT department and it would take an act of god to get anything done. Joseph also points to the speed with which he can onboard new analysts. This is more like Excel where you can just play with the data and not like Microsoft Access where you really have to take classes to make something of it. This is more intuitive, more graceful. Continue The Art of Analysis - Envisioning Outcomes Analytics without goals is an idle pastime. Entertaining, fascinating, sometimes even educational. But the value of analytics is in solving problems and no problem is worth solving unless it is clearly identified. It turns out that this is primarily a political issue. Every organization has its own priorities when it comes to the three universal business goals: raise revenue, lower costs, drive margins, and increase customer satisfaction. The priority depends on the state of the company, the comfort zone of the people setting the agenda and the power struggles that permeate human organizations. Within an organization, every marketing department has its own, currently popular priorities when it comes to the universal marketing goals: • • • • • • • Raise Awareness Improve Attitude Influence Influencers Inspire Interaction Generate Sales Engender Advocacy Increase Customer Lifetime Value Page 5 of 11
  7. 7. Top-notch data artists know what their “patrons of the arts” want and strive to deliver. But they don’t just guess. They listen, negotiate and agree. To be fully fathomed, organizational goals must be well defined and have specific desired outcomes. It’s not enough to set raising revenue as a goal. The goal must identify by how much and how soon and how efforts impact margins. For the data artist to “succeed,” the prioritized organizational goals must also be politically aligned from the corridors of power to the cubicles of the knowledge-factory floor. If the problem to be solved is not universally understood, approved and treasured, delivering insights to solve it will produce no value. Case in Point - A Data Artist and Flexible Tools U-T San Diego wanted to increase readership and advertising, but nobody knew exactly what that would look like when all was said and done. That’s because nothing is ever completely said and done. Reports are a destination; analytics is a journey. Once the data artists determined which editorial sections and authors were attracting the most readership, they realized there was a great deal of additional information they could leverage. • Which sections enjoyed longer visits and more pageviews? • Which sections had more ad positions? • Which authors engaged more people on social media? • Which types of photo galleries get more views? • Which photographers are most popular? These creative questions opened the door to bookkeeping questions. • How do we account for the same ads showing across three pages of the same article? • How do we account for a whole gallery of photos loading at once? • How do we categorize articles beyond editorial beat to determine what our readers want? At each step, the analytics tools must bend to the will of the Data Artist. At the very start, we didn’t think we’d need to identify each photographer or even the person who selects the photos for a given gallery and writes the captions. But each of these variables has a measurable impact on the bottom line, so we needed to create new page attributes to capture these bits. We needed to know what drives the business, so we need to create new attributes as we think of them. You collect the data, tweak it and tweak again. Getting those tweaks instantiated into our previous analytics tool was so hard that we had to strictly prioritize which we would bother with. So we needed something that would let us actively work the data instead of ask for new reports that wouldn’t show up for weeks. The bonus benefit was how the transparency enabled by analytics fostered a culture of healthy co-opetition among the writers and editors, further driving audience reach and engagement. Continue Page 6 of 11
  8. 8. The Art of Analysis - The Creative Process With trustworthy data, a suitably powerful and flexible analytics system and a problem worth solving, it’s time for the data artist to get inspired. Whether mining, massaging or modeling data, the data artist first relies on the craft of the trade; the techniques of master craftsmen; and the basics of analytics. The data artist looks for patterns or anomalies in the data, applies segmentation to create cohorts and guards against dozens of cognitive biases. The data artist works the data to ask: • What can be omitted? • What if we tackled the problem from the other side? • What if we changed the time scale? • What additional data would be dispositive? • What if we focused on the outliers? This is where a flexible and effective analytics tool is paramount. If the data artist’s imagination is restrained by technology, the potential for significant insight is limited, as well. When the data artist can flex that creative muscle, curiosity is liberated. The ability to ask – “What sells at what times of day?” − resulted in Seven-Eleven Japan stores selling twice as much as American stores in less than half the space. The ability to ask – “How are people configuring our products on our website?” − resulted in Ford Motor Company altering its production and distribution allocations, significantly lowering the cost of transportation. The appropriately optioned trucks were already waiting for customers. The ability to ask – “What’s the geographical distribution of people who buy from us online?” − resulted in MEC opening a new retail store in Montreal. Having the freedom to ask, re-ask and then pivot the question spurs creativity. It allows the data artist to try new things instead of being consumed by cranking out the same old reports all day, every day. Page 7 of 11
  9. 9. Case in Point - A Data Artist and Corporate Culture This is where Joseph’s work started to pay off in an incalculable way. Once we started using Anametrix and could make more changes fast enough, we could have a real impact on corporate culture. We start the conversation when we try to build a model. People realize that we really can identify the investment and how we would track the return – we follow the money. For example, we found that entertainment content demanded the highest price and was the most sold out. Findings like this can give management the information they need to support article-investment decisions. We get management to discuss its vision of the business model, and then we can build the math model. You never know everything going in, but being able to answer ad hoc requests in the same day is huge. When a department head had a brainstorm in the morning and Joseph could return with a prototype in the afternoon, everybody in the organization began to really appreciate the power of analytics. Given this new appreciation, analytics started getting baked into the product development process. Now, new projects always pay attention to metrics. When a new technology for photo gallery display comes along, they pull us in on the ground floor to get the right attributes plugged in. That conversation has resulted in business-model changes because now everybody is always thinking about tracking. When junior people are messing with pages – adding new content or spreading articles across multiple views – they are now well aware that they have to account for dozens of different data fields representing key attributes across almost a dozen page tags. Continue Page 8 of 11
  10. 10. The Art of Analysis - Delivering Insight Unearthing a true nugget of insight after hours of data mining, massaging, or modeling is often its own reward. Sadly, it’s also often the only reward. Until that nugget can be polished and presented in the right way at the right time to the right person, and that person takes action, that nugget might just as well have stayed buried. Data artists must have a talent for communication or their great works will remain unknown and no positive action will result. As is often repeated about engineers: Q: How can you tell an extroverted data artist? A: When he talks to you, he looks at your shoes instead of his own. There are many ways to make data artists more comfortable with presenting their discoveries, not the least of which is Toastmasters. But the most important factor for all data artists to keep in mind is to constantly consider their listeners’ motivation. Once data artists understand what’s important to the people on the receiving end, the rest falls into place. Whether listeners are interested in getting a promotion, increasing their paycheck/budget/staff, taking on more challenges or simply raising revenue, they are much more interested in how to achieve their goals than they are in the data artist’s fascinating journey to arrive at the insight. • • • • • • A data artist should tell stories, rather than delivering reports. A data artist should leave off the gruesome details of data mining. A data artist should not confuse the audience with scientific details. A data artist should tie insights to the bottom line. A data artist should help others achieve their goals. A data artist should share opinions and hold back the numbers for reference, if needed. Page 9 of 11
  11. 11. Case in Point - A Data Artist Delivers on the Promise Joseph is also working on U-T San Diego’s cable-television-station analytics. With 12 hours of live broadcast a day, he can combine and correlate streaming viewership with Nielsen ratings. Understanding true reach across multiple channels of content consumption has long been a major aspiration, especially with changing demographics. Bringing more data streams together enables better fine-tuning to increase ad monetization. Soon, his advertisers will know exactly which video ads are driving user action traffic and which web ads are driving video views. This, in turn, gives more information to advertisers and shows them how and where to spend more with U-T San Diego. When pressed for the secret to his success, Joseph discusses three factors: upper management sponsorship, flexible technology and the power of relationships. I couldn’t do what I do if the top brass wasn’t dedicated to this approach. They have a specific view of the world and a gut feel for how to operate a business, but their perspective is always open to change when the numbers paint a different picture of reality. They want everybody to be aware of - and on top of - the numbers. That’s how they manage the business. They exercise their intuition after it’s been informed by the facts. The analytics tools we use give me the power and flexibility to give people the information they want. That helps me understand their business goals. That means I can show them other metrics they don’t even know exist, yet, and help them meet their goals better and more quickly, as well as support decisions with more conviction. Without that technology, I can’t convince them that analytics is worth the effort. But with it, it’s like I have X-Ray Specs when looking at data sets. I can get business people, who are trying to solve business problems, to start thinking like analysts without them even being aware of it. We get into these ‘what if’ conversations, and they run with it. It’s like a cross between brainstorming and problem diagnosis with real data. It feels like reality hacking. Working like that with people is really more art than science. My focus is on helping people be successful, which I can do because I work hard on the personal relationship side of things. It’s more important to know what motivates people and to create relationships with mutual respect because then you can get anything done – even without an ‘act of god.’ When the data artist ties together the science and the creativity, then editors, authors, photographers and advertisers can more easily assess progress, more realistically set goals and more directly monitor progress. When the power and flexibility of analytics are properly combined, the results are concrete and measurable, and they directly impact the bottom line. This, in turn, cannot help but impact corporate culture. As Peter Drucker famously said, “Culture eats strategy for breakfast.” Page 10 of 11
  12. 12. About the Author Jim Sterne is an international consultant focused on measuring the value of the online marketing for creating and strengthening customer relationships since 1993. Sterne has written seven books on using the Internet for marketing, produces the eMetrics Summit and is co-founder and current Chairman of the Digital Analytics Association About Anametrix Anametrix transforms businesses with marketing analytics. We collect, analyze and make sense out of data across all marketing channels in real time to enable marketers to discover new truths about customers, prospects and the market at large. Anametrix delivers 360-degree visibility into business data to uncover new trends and hidden correlations, explore new relationships and deliver a bigger and more predictable impact on revenue. Founded in 2010 by the trailblazing web analytics team behind WebSideStory, Anametrix has headquarters in San Diego, Calif. For more information, visit our Website, Twitter, Facebook, Google+, and our Blog. Page 11 of 11