Be the Brad Pitt Billy Beane of the Social and Mobile Web

What do Kontagent data scientist Martin Colaco and Billy Beane have in common?

On the surface, probably not much. But, when it comes to analytics, Beane changed the game for baseball. Colaco could be doing the same for business.

Moneyball is based on Michael Lewis’s book, Moneyball: The Art of Winning an Unfair Game. Faced with a relatively meager budget, Oakland Athletics manager Billy Beane (played by Brad Pitt) uses a groundbreaking, sabermetric approach—the specialized analysis of baseball through objective, empirical evidence that measures in-game activity—to recruit a competitive baseball team. (Read more on how sabermetrics works.)

Beane goes against convention, taking advantage of more empirical gauges of player performance to build a team that could successfully compete in Major League Baseball. He analyzes stats that are not generally considered top priority in the traditional scouting process. While most managers pored over stats like running speed, stolen bases and batting averages, the sabermetric approach, developed by baseball statistician Bill James, predicts other factors are better indicators of a player’s offensive success, e.g., on-base and slugging percentages.

Beane basically stared the “old guard” of baseball recruiting in the face and said, “Suck it.” And it worked.

Using sabermetrics, the Oakland A’s were able to put together a competitive team on a $41 million salary; by comparison, the New York Yankees spent more than $125 million in payroll in the same 2002 season. It paid off: the Athletics led a 20-game winning streak, and Beane shifted the paradigm of baseball scouting forever.

When it comes to Web business analytics, it’s not a bad idea to take a page out of the Moneyball book. Sometimes you have to look at data through a different lens in order to better make predictions and optimize opportunities. In baseball, Beane approached player stats differently and got different results. In business, data scientists like Colaco say there’s a similar shift happening in the world of Web 3.0.

Moneyball lesson #1: Challenge the status quo.
There’s a scene in Moneyball where Beane and his scouts are arguing over which players to recruit. His scouts want the highly sought-after players. Beane can’t afford them. Frustrated, he says, “You guys are talking the same non-sense. We’ve got to think differently.” Thinking differently, it turned out, made all the difference in the world.

It’s a good lesson to remember when it comes to business. With the explosion of social and mobile applications, we have to move away from the “old guard” of analytics and begin measuring KPIs around virality, engagement, retention, and monetization. It’s no longer about page views; it’s about users. What are these users doing within your applications? Every click of every action of every second. How can we use that information to win? We’ve got to think differently.

Moneyball lesson #2: You can compete with the New York Yankees.
Companies like Zynga, Playdom and CrowdStar aren’t wildly successful just because they’re in the social gaming space. No, these companies are behemoths when it comes to data. And, they’ve figured out how to collect, store, analyze and optimize all this data to succeed.

But what about the little guys who are trying to compete in this space? They may not have the infrastructure to support such massive amounts of data (or the hundreds of thousands of dollars needed to get that infrastructure in place). How do they (think: Oakland A’s) go up against Zynga (think: New York Yankees with the deep pockets)?! Luckily, analytics platforms like kSuite by Kontagent now provide the infrastructure needed to access data for organizations of all sizes.

Okay, great—you have access, but now what?

Moneyball lesson #3: Look at the data that really matters; it may not be obvious at first.
In Moneyball, Beane relied on Yale economics graduate Peter Brand (Jonah Hill) to help him make sense of all of the stats. It was Brand who took the core data and interpreted it so that Beane could make better scouting decisions.“Your goal shouldn’t be to buy players; your goal should be to buy wins,” he says.

The lesson here? Good data is useless if it’s mismanaged.

The right analytics solution needs to give you not only access to big-data analytics, but also an easy-to-understand dashboard and support from data scientists (your own team of Peter Brands!).

Data scientists can help you understand what the patterns of data are telling you to find the users with the greatest potential for monetization and lifetime value. What might appear obvious could be deceiving when you slice the information differently. And it’s these users that you want to understand and develop. It’s these users you need to understand. In. Order. To. Win.

Call it leveling the playing field.

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About the author: Catherine Mylinh is a member of Kontagent’s storytelling team, where she is head of content marketing. In her former life, Catherine was a news anchor for CBS and NBC. She credits her journalism and computer science roots—she was once a programmer!—for her love of learning and writing about all things high tech. You can contact Catherine at @cat_mylinh.

Kontagent CMO Dan Kimball attended the Pivot Conference in NYC, where he spoke with brand leaders who are using gamification to engage their audiences in an effort to bridge the gap between their brands and the rising social consumer.  Dan was joined on stage by other noted experts in the space, including:

• FreshPlanet CEO Mathieu Nouzareth speaks about surprising trends in social user behavior and engagement, and how the company is developing a game for one of the world’s largest cosmetic firms.
• Lee Boykoff, who leads digital media analytics and distribution for A&E, discusses the decision-making process on building a game for the channel’s TV series, “Pawn Stars,” and shares the results.
• Badgeville CEO and co-founder Kris Duggan reveals successful gamification strategies.

Watch as we try to separate the hype from the real business opportunities.

Gamification in the Brand Marketing Environment, Part I

Gamification in the Brand Marketing Environment, Part II

Check out kScope in the coming days. Dan will summarize the key takeaways he learned by attending the conference.

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Dan Kimball is Kontagent’s CMO and resident storyteller. His drive to make sense of complex concepts and solutions comes from his unique background in philosophy, quantitative research and brand marketing. Prior to joining Kontagent, Dan held several senior marketing roles in various industries including financial services, consumer Internet and B2B SaaS. Most recently, Dan served as CMO and head of product management for Jobfox, one of the web’s leading job boards and an innovator in the emerging social recruiting space. Even when not in the office, Dan is still telling stories…usually to his two daughters…and usually about princesses, not analytics.

Your users may be engaged, but are they being monetized?

Another great article about moving beyond traditional Web analytics.

Fast Company blogger Shawn Graham takes a look at the changing landscape of user analytics; we are now inundated with customer data, but we need to sift through it to figure out what’s meaningful–and that can be daunting.

In Are User Behavior Analytics the Real Predictors of Customer Engagement?, Graham credits social gaming start-ups with pioneering the process. It’s no longer about the page views; game developers have learned to “rapidly interpret and develop meaningful insights from billions of data events each day. They [use] customer data to drive engagement, fuel product development, improve the user experience and ultimately increase ROI.”

Other industries can take advantage of this, too. “Businesses now have an unprecedented opportunity to deeply understand and optimize their customer economics,” says Kontagent President and Chief Science Officer Josh Williams.

Williams says businesses need to find the levers that “drive effective user acquisition, engagement, retention and monetization…by acting on real-time insights that affect their bottom line.” It will be the only way to survive in this new Web 3.0 world.

Does customer engagement really lead to increased revenue?
We’d like to take the old-school vs. new-school analytics topic a step further. Businesses are now measuring engagement, but they could be missing the point if they’re not tying it back to the user–and ultimately, ROI. Engagement alone doesn’t increase revenue. We need to pinpoint the moment the user becomes a paying customer. But, well before that even happens, we need to predict which users will become customers, and we need to nurture them.

For example, say you’re shopping for jewelry at an online shopping site. You find a necklace you’re completely in love with. You share the link with your Facebook friends or you tweet it for the world to see–but you have not purchased the item. That’s customer engagement. A week later, you find the same necklace for 20% less at Jewelmint after seeing an ad on Facebook. You pull out your wallet and make a purchase at Jewelmint. That’s ROI.

So, if you’re that first website, have you missed the beat? Could you have better nurtured me and turned me into a paying customer? Social games have mastered the art of nurturing users into paying customers. The rest of the social industry can pull the same levers to optimize their customer economics.

This is the science of user analytics. And it can take thousands–even millions–of events (not page views) to lead to a sale. That’s a whole lot of data. Do you have the support and insight needed to nurture your best customers? User analytics is about making sense of that data–and acting effectively on it.

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About the author: Catherine Mylinh is a member of Kontagent’s storytelling team, where she is head of content marketing. In her former life, Catherine was a news anchor for CBS and NBC. She credits her journalism and computer science roots—she was once a programmer!—for her love of learning and writing about all things high tech. You can contact Catherine at @cat_mylinh.

You need the right lens to look at big data effectively.

Imagine you are two inches tall, and you are inside a giant kaleidoscope. You’re nose to nose with thousands of little bits of color. Lots of different shapes and sizes of all different materials and compositions. You sift through the pieces and try to form patterns. After trying your hardest to move the pieces around, you realized you’re too deep in the pile to identify any discernible patterns. You simply don’t have the ability to step away to gain perspective, while at the same time arrange the pieces in a way that makes visual sense.

What you need is the right lens. You need a simple way to peer into the pile and analyze its structure and composition. You also need to be in a position where you can creatively manipulate its appearance, pivoting your view in any way, and forming new patterns each time.

Welcome to the Kontagent Kaleidoscope (or the kScope for short). The significance of our decision to name our blog after a kaleidoscope, if you haven’t already guessed, is that a kaleidoscope is a basic metaphor for our view of the approach you need to take when trying to analyze and interpret mountains of data.

At the very basic level, a kaleidoscope is a lens into a world composed of lots of individual pieces that enables the viewer to see patterns that they would not otherwise be able to see. In some magical way, it takes seemingly random items and transforms them into beautiful patterns. It’s an eye-opening experience for sure.

Now, consider big data.

The issue now is less about how to process large data sets or whether it can be done. That is largely a commodity now. It is more about what you do with the data to make sense of it. The patterns that you can find, that may be hiding within terabytes of data. The insights you can develop to form action plans rooted in data science.

A “big-data kaleidoscope” of sorts.

Our company, Kontagent, provides a unique view into this big-data kaleidoscope. We process over 1.5 billion ‘events’ every day (making us only 2nd to Zynga in the social gaming space) and currently track over 150 million monthly active users.

We use this data to provide a new perspective (or, a lens, to keep the metaphor alive) to companies who process a ton of customer data–like social game companies, social commerce sites, mobile applications, etc.–but don’t have the right lens to see the patterns and make sense of the information.

Take, for instance, one of our clients: Gaia Online. Gaia is an incredibly successful game developer that launched their blockbuster social game Monster Galaxy on Facebook last year (8 million users strong!). While the marketers, analysts, engineers and product managers are extremely intelligent about gameplay and designing engaging experiences for their users, they didn’t have one consistent view of the performance of their application across the entire organization. Kontagent provides Gaia with that view, giving them access to their customer analytics, an easy-to-understand dashboard and a team of data scientists who help them to make smarter business decisions. Altogether, Kontagent is Gaia’s big-data lens into the millions of interactions that occur on their game on Facebook and iOS every single day.

Our job here at Kontagent is a lot of fun. We get to play with reams of data. Organize it. Interpret its meaning in light of business objectives. And, ultimately stay at the forefront of trends in social and mobile that most companies simply cannot do.

The Kontagent Kaleidoscope will be a place where you too can come and take a peek through our lens, and engage in content you won’t see anywhere else. This blog:

• Is for developers, product managers, marketers, C-levels and anyone else who plays in the social, mobile or Web space, and wants to both learn and contribute ideas.
• Is a way of doing business in an age when customer data is abundant, but not used to its full potential.
• Is a celebration of businesses that have achieved success–or are on their way–because of their commitment to building more engaging digital experiences for their users.
• Is smack in the face of the way many companies view their online businesses today, and what they think they need to focus on to be successful but could actually be to their detriment.
• Will show you trends in social and mobile user behavior that you won’t believe and will challenge your very rational perspective.
• Will examine how BIG DATA is playing a BIG ROLE in data analytics today, and why it will become even more relevant in the future.
• Will try to be entertaining and not serious enough, but it will most definitely open readers like you to an entirely new way of seeing the matrix behind social and mobile worlds.

We’d like to formally welcome you to the Kontagent Kaleidoscope. If you have any ideas of topics you’d like to see here, feel free to add a comment at any time. Our team of data scientists is always open to new challenges.

P.S. Sign up for our blog newsletter, and get alerts whenever we post new stories.
P.P.S. Another great way to keep up with us is on Twitter: @Kontagent

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About the author: Dan Kimball is Kontagent’s CMO and resident storyteller. His drive to make sense of complex concepts and solutions comes from his unique background in philosophy, quantitative research and brand marketing. You can contact Dan at: @dmkimball05.