We spoke with Jogonaut Founder and CEO Barry Carpe on the importance of data-driven design, and how he’s using analytics to continually provide the best user experience to his players. He also shared some great game marketing and development tips.

Why are analytics important?
Analytics provide insight into what is working well and what is under-performing in any product. Using the data Kontagent provides us, we’re able to quickly identify new retention and monetization opportunities, as well as track game-play trends to improve the overall experience for our users.

What are your primary business objectives as a game studio?
At Jogonaut, our primary business objective has been to curate and refine our content based on player funnels and develop a game that not only drives retention and monetization, but also adapts based on user trends to deliver a more satisfying, entertaining experience.

Kontagent has been instrumental in helping us achieve this goal—the depth of their statistical tracking has allowed us to double our revenue and attract noteworthy brands to our viability as a marketing platform.

What specific insights are you looking to gain—now and in the future?
We use Kontagent kSuite to gain insight on our player activation funnels. For example, we look at how many people take the first desired steps to get them engaged with the game, cost per install (CPI), retention rates, daily active users (DAU), monthly active users (MAU), average revenue per paying user (ARPPU) and session times.

(Read more on The Top 7 Metrics of Highly Successful Social Companies)

Having insight to all of these metrics means we’re constantly able to improve game play and entertainment value for our users, as well as tighten monetization efforts.

Furthermore, we are able to easily track and optimize user acquisition spend based on source, demographic and geography; therefore, we’re also able to build spending curves for each of our campaign segments to gauge the approximate lifetime value of a user. This helps us to determine who the best players are, and then we can focus our marketing dollars toward them.

How are you ensuring the right players find your game?
Our current marketing plan includes social engagement with players, email promotions, a player loyalty club and paid advertisements. Additionally, we’re in talks with several national brands discussing unique co-marketing opportunities.

Engaging our players on Facebook is a no-brainer. One of the first things we did was set up a business page where we could communicate with players and gather feedback about the game. The Facebook page also allows us to send players promotions that help our retention rates.

Research shows that email marketing is still the most effective way to reach an online audience, so we have built up a healthy list of players who opt-in to receive promotions and strategy tips. In addition to email and social marketing, we also have a loyalty program in place where top players in our game (based on spend and achievements) can receive special loyalty items and personal thank-you letters from our staff members.

Any lessons learned so far in acquiring these users?
One note to other gaming companies: When deciding on promotions it’s important to make them impactful. You’ll want to give away bonuses and discounted items that really help a player in the game. This will ensure your click or email-open rates remain high. (Read more on email marketing tips.)

Like most social gaming companies, we run paid ads to help reach new players. Most of the ads we run are Facebook ads though we’re experimenting with a variety of different acquisition channels to target the best, most engaged players.

We’re A/B testing these promotions now, and Kontagent is crucial in helping us determine which campaigns are performing the best, and bringing in the most high-value players. (We’ll be sharing the results in a later post.)

Specifically, what kind of ad campaigns, in-app ads, cross-promotions are you using?
Our main focus—no surprise—is running Facebook ads. That being said, we are diversifying a bit by including banner ads on highly targeted gaming sites and blogs.

Facebook ads are such a perfect fit for any company with a Facebook game though. Your audience is just one click away from playing your game when they see the ad. Another advantage is Facebook allows you to get hyper-specific when targeting users. A recent report suggests social gaming companies are receiving lower cost-per-click rates than brands because we are able to target so well—our own data shows this to be true, thanks to the data Kontagent provides us!

So you’re getting users to click on ads—great. What’s next? What about retention metrics? Are you making changes to your game based on those?
Definitely. In particular, our Agenda mission system is designed to set a steady pace for our users, and based on the metrics we’ve seen with the Agenda, we’ve been able to make subtle tweaks and adjustments to improve retention, monetization and ultimately, entertainment value.

Also, during our BETA phase we noticed that our Day-1 retention rate was quite high, but saw a significant drop-off on Day-7. To help improve these numbers for the official launch, we introduced the ability for players to interact with their friends. Not only are we seeing good signs that this social interaction is increasing retention, the feature is helping us build a great community.

Looking into the future, we see tremendous opportunities in increasing the avenues for social interaction and virality, competition and integration with real world events within OJO AGENT.

Without data, we might not have the insights into what appeals to players. With data, we firmly believe we have the insights to create core features that will drive long-term retention and revenue.

And, once you’ve tuned the game to increase retention rates, what are some other metrics you pay attention in order to iterate and fine-tune your game?
Retention is vitally important to us, but we’re also closely monitoring session time, daily spend, ARPPU and DAU. Now that we are using SpruceMedia in conjunction with Kontagent, from one dashboard we’re able to see our retention rates from user acquisition channels alongside these other important metrics.

This funnel shows player drop-offs from Level 1-8 in OJO AGENT.

Additionally, we’re always monitoring our activation funnels. All OJO AGENT players are guided through a brief tutorial (Level 1 in the image above) before they begin playing the game. We’re constantly checking to make sure there is minimal drop-off during this tutorial. And again, we’re also always checking to make sure the players who complete the tutorial are taking the first series of desired actions that lead to high Day-1 and Day-7 retention rates.

At Kontagent, we firmly believe that the ability to bubble up all the data into an easy-to-read dashboard that is accessible to the entire organization helps our customers all work in lock-step—same data, same goals. Tell us your experience with the kSuite dashboard.
That’s absolutely true. The data visualizations really help us to quickly recognize trends, and identify what’s working and what isn’t. This enables us to spend much less time digging for relevant data and insights, and allows us to instead use that time more efficiently to develop the creative aspects of our games.

It’s about opportunity costs—Kontagent definitely saves time and resources for everyone on our team, from marketing and user acquisition to game development.

An example of Kontagent kSuite dashboard. Note: This is not Jogonaut data.

Any tips/advice for other game developers?
Analytics are the cornerstone of our product development process and we couldn’t be happier with the results we’re seeing.

To say that Kontagent enables us to understand user behavior so we can optimally increase user acquisition, retention and monetization is an understatement.

We would highly suggest all game developers identify their KPIs and track performance over time using software such as Kontagent kSuite. They can group players by acquisition source, demographic and geo-location to identify the most attractive types of players. Then, most importantly, after they have that data, developers must optimize game play based on it. That’s the only way they’ll be able to survive in this free-to-play world.

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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.

by kScope guest contributor
Garrett Wilkin, Freelance Writer at ProgrammableWeb

AngelHack brings together start-up communities from around the country; participants build start-up ideas. The competition is judged by top angel investors.

I attended AngelHack in Boston over the weekend of March 3. My primary goal was to talk to developers about analytics. I wanted to see how many had heard of the new potential for deeper analysis of user behavior from service providers like Kontagent. Some of my questions included:

• How were they thinking about user behavior, if at all? Had they already decided that analytics was important?
• If so, which SDKs and tools did they plan to incorporate into their product strategy?
• Would they partner with a specialized company or would they prefer to build an in-house solution?

These were the questions I would seek to answer over the course of the weekend. With thousands of dollars in prizes and start-up perks up for grabs, this hackathon was a bit more serious. The result was a crop of ideas that incorporated a business strategy in addition to a novel technical approach. It was the kind of intellectually stimulating environment which categorizes a great hacking event.

After a short period of idea pitches, the hackers began to mingle and form teams. Several teams came to the event with well formed and, in some cases, patent-pending product designs. Discussions in the small teams focused around which features to include in the prototype and what technologies to use to build them. The idea of how to understand the ways in which the product will be used was not a topic of conversation. After personally speaking with nearly every team in attendance I can say that in general, the idea of tracking actions taken by a user was novel to most teams.

But, in a data-driven world, why was it a relatively novel idea?

Perhaps because we, as engineers, designers, and visionaries, tend to fall in love with our ideas. We tend to get caught up in the excitement of implementing the idea, and indeed, implementation is the focus of a hackathon. But when considering scaling projects well beyond the hackathon, it becomes important to consider how to steer the business strategy along. That requires a bit of detachment from the particular ideas encapsulated in the initial design.

In other words, we need to develop a strategy for knowing when and how to change our idea. Analytics can deliver that knowledge.

It is now possible to store large amounts of detailed user behavior data. More importantly, we have the ability to process these data sets into answers to the questions of design for the application functionality and user experience. Kontagent is one of the leaders in this area and here’s their selling point to hackers: Kontagent can track, store, analyze and compare the actions of millions of users in order to provide insights that can directly influence design changes.

This is a feedback loop that has not existed at this level of sophistication until recently. When a website or an application succeeds, we recognize the genius and creativity of the team behind it. When an app fails to gather users, the team wonders what went wrong. In either case, we attribute the outcome to some degree of mystery and luck.

Classifying and segregating users based on their behavior gives designers and implementers a way to understand exactly what matters in their app.

• Do users respond more to Feature A or Feature B?
• Which features do the most active users frequently use?
• Which features are used just before the app is uninstalled?

These are the types of questions that we should consider during the design of the minimum viable product. They all point to the basic question: is this a good idea or not? If not, how could we make it better?

That’s the fundamental question poised to each start-up as they explore their own specific niche. (And, if there are even deeper questions about user habits once they’re up and running, kSuite DataMine^TM may be able to answer a lot of them.)

Many of the brightest and most creative people still see this data-driven approach as novel, and this signals a great opportunity.

Companies who are already using user behavior as a feedback loop into product design have a head start on their competitors.

Additionally, service providers like Kontagent have the advantage of experience in successfully coaching companies to adopt analytics as a new component of their strategy.

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About the author: Garrett Wilkin is a technology enthusiast. When he’s not programming high-performance financial systems you might find him interviewing start-ups for API-focused articles at ProgrammableWeb or hacking in Node.js. (He’s fallen in love with the hackathon culture.) You can follow him at @garrettwilkin.

Kontagent at GDC 2012

We had meetings with hundreds of customers, leading industry thought leaders and prospects last week. And, we threw an insane GDC party at Vessel SF. Thanks to everyone for coming out and supporting us!

Special thanks to those of you who came by our booth, too!  We’re revolutionizing the way people measure and optimize their user engagement and monetization, and we’re stoked to share our vision with you.

Our GDC session, Mobile App Metrics for Success: Using Data to Drive Development, was over-subscribed. If you couldn’t get into the classroom session—we’ve made the presentation available for you here.

Finally, we’d like to thank all our customers and industry thought leaders for coming to our Kontagent Konnect roundtable. We had nearly 50 top-notch participants discussing relevant issues across the social and mobile app ecosystem. For those of you who missed it, we hope to see you at one of our future Kontagent Konnect events. Stay tuned for details!

Using customer data to understand and optimize your social or mobile application can produce huge returns. But, there are also dangers of relying too heavily on data without the proper level of controls, data science and overall process. Fortunately, there are now tools, technology and talent available that are enabling studios and devs to be more data-driven.

Here at Kontagent, we’re all about data: how to get it; how to store it; how to query it; how to interpret it; and, ultimately, how to make the best data-driven business decisions.

Our CMO, Dan Kimball, was invited to speak at Casual Connect in Hamburg this month on what it takes to become a data-driven organization. He shared lessons learned from our experience working with some of the top grossing social and mobile game studios. It’s actually a pretty fun presentation since he compared it to learning how to ski (Dan’s an avid skier). If you’ve ever hit the slopes, you’ll appreciate this.

Click on the image below to see the entire presentation–you’ll be able to evaluate your “data-driven score” as an org, and identify the seven keys factors to leveraging your data effectively. We’ll add a recording of the presentation as soon as it’s available from Casual Connect.

Click to view the presentation on Slideshare

What about you? Are you taking the same approach to creating a data-driven culture? If so, how has your business benefited from 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.

Now she’s spearheading Game Dojos, a San Francisco-based game start-up accelerator which offers a three-month mentor program to game start-up entrepreneurs. Through Game Dojos, you’ll meet many of the movers and shakers in the industry, learn how to optimally monetize your games, and even get help with funding, if that’s what you need.

We recently spoke with Burkett about what you can learn from the program, and how you can take advantage of the thousands of connections from Game Dojos’ staff and mentors. She compares developing games to driving a car, and here are her thoughts:

Don’t reinvent the wheel
Games need special help, but you don’t have to start from scratch. You can leverage a lot from proven game designers; they have already overcome some of the obstacles that are specific to creating games, e.g., design, monetization mechanics, which tools are best for specific purposes, etc.

They understand the best “free-to-play” strategies, subscription, or ad monetization techniques, game engines, game distribution networks and cross-promotions, or are experts in nursing entertainment IP for starters. Even for those companies that are building game platforms or tools or strong gamified apps, good game industry knowledge helps tremendously in understanding which ones work well and why and how to cater to specialized game markets.

Why would you waste precious time figuring these things out on your own when you can learn from others’ experiences?

Sometimes backroads get you there faster
The competition in games is fierce. For example, for mobile games, Game Dojos helps you solve the first issue you’ll face: discovery. Even if you create an awesome game or app, with the hundreds of thousands of apps released each day, how are you going to break through that noise? Many of our mentors are specialists in that area. Even more importantly, some own large discovery and distribution networks and you will meet them in the workshops.

We also keep a very sharp eye on new platforms, and help you to think differently. For example, sometimes, as a new developer, instead of competing in the saturated App Store or Android Market, it might make sense for you to develop your game on the Microsoft platform–the “small fish need to get out in front” sort of tactic.

Turn on your headlights!
Social games showed us that metrics matter. We’re still in the early stages of mobile, but the importance of metrics will continue. In fact, I think it will be even more important as the competition grows.

Social games were able to evolve so quickly because devs started looking at metrics to see what worked and what didn’t. And, once you have that knowledge, you can never go back. When devs are starting out, they should at least know the basics, i.e., where people are dropping off, how to fix it, etc. You can’t get to the ultimate goal–monetization!–if you can’t get past acquisition and retention. I use this analogy a lot: If you make a great game without metrics, it’s like driving with dim headlights. You may have a good idea where you should be going, but you might miss a turn and head down the wrong path. Analytics are like high-beams–you get much more clarity for what might be coming down the road.

In the coming weeks, kScope will go behind the scenes from Game Dojos to bring you in-depth stories from the accelerator’s workshops. We’ll also highlight some of the teams that have been selected to attend Game Dojos inaugural program. Stay tuned!

Learn more about Game Dojos
If you’re interested in learning more about Game Dojos, click here. They’re accepting applications for teams to join the first program, which begins later this month. Applications are due Feb. 15, 2012 (that’s today!).

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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.

The ARM funnel shows a typical customer lifecycle, which is comprised of three stages: acquisition, retention and monetization.

Mobile app developers and marketers can gain a huge advantage by looking at the way social app developers scientifically build and optimize their games around customer data on social platforms. They use that data to learn about what is and isn’t working in their applications, and iterate quickly for increasingly stronger returns. From Acquisition to Retention to Monetization–the three stages in the ARM funnel–successful developers have created entire organizations around data-driven design at each level and across all facets of their businesses.

At Kontagent, we’ve witnessed firsthand the ARM funnel’s crucial role in the success of a large majority of studios that publish games on Facebook–and now on iOS and Android as well. Insights garnered from this model help to focus resources and marketing investment. And, having a perpetual flow of data and a supporting data science infrastructure (with the expertise to act on it), has enabled game studies to acquire users more profitably. Teams of data scientists and developers at Zynga, Popcap, Crowdstar and Gaia, for example, have measured, iterated, tested and optimized relentlessly to acquire more users at better customer acquisition cost and with higher yield ratios than most. It’s no coincidence these are the same guys succeeding on mobile platforms as well.

I’ve broken down each branch of the ARM funnel at a very basic level below.

Acquisition: Figure out what audience performs best in your game and how to acquire members of that audience in the most effective, lowest-cost manner possible; from ads, to cross-promotions with other games, to install exchange networks, to viral channels. KPIs = Cohort Customer Acquisition Cost (Cohort CAC); Cohort ARPU and Retention by Channel; Cohort ARPU and Retention by Campaign; Acquisition Conversion Funnel

Retention: Keep that audience engaged for as long as possible. Find fall-off points where users leave. Learn how to encourage sharing with friends. KPIs = Avg. Session Length; Day 1 Retention, Day 7 Retention, Day 30 Retention; Custom Event Funnels; User Lifetime Event Distribution; k-factor (virality)

Monetization: Get these users to pay and to keep paying over time, optimizing their lifetime values (LTV) to the greatest degree possible. KPIs = % Paying Users; Avg. Revenue per User (ARPU); Avg. Revenue per Paying User (ARPPU); Purchase Conversion Event Funnel

As the free-to-play model continues to grow and dominate in mobile, just as it does in social, it’s no surprise that the ARM funnel is the right framework for measuring customer economics and per-user profitability in mobile as well. Just like social app developers, mobile app developers must understand and optimize acquisition, retention and monetization if they are going to succeed.

Still, mobile developers have a long way to go. As more social companies (including Zynga) move aggressively to mobile, getting smart about data is increasingly important. Kontagent believes those mobile developers who recognize the importance of data-driven app development throughout the ARM funnel will be well-positioned to lead the space.

I’ve outlined the biggest challenges and opportunities facing mobile game developers, relative to measuring and optimizing around the tried-and-true ARM funnel:

Discovery & Acquisition

Biggest Challenges

• The biggest hurdle is getting discovered and competing against companies with deep pockets who can muscle their way up the App Store rankings.
• Mobile ad networks are massively fragmented and difficult to target high-yielding cohorts of users (either through behavioral or demographic segmentation).
• Understanding ROI (on iOS in particular, tracking from ad/source to install to monetization used to be impossible).

Biggest Opportunities

• Reach large audiences at a relatively inexpensive cost-basis by advertising on cross-promotional networks and partnering with other developers with high daily active users (DAU) counts.
• Segment users by acquisition channel, and optimize around those producing the highest per-user ROI. Analytics make it possible to see differences between each source: organic, viral, cross-promotion and advertising.
• Build a great, highly engaging game! The better the experience, the more players will tell their friends. Word-of-mouth is a huge organic driver of installs for mobile devs right now, so focus on gameplay, and reap the benefits. Use analytics to tell you where users are losing interest in your app.

Engagement & Retention

Biggest Challenges

• Although testing and iterating is how social devs have found success on Facebook, rapid iteration is not so easy or fluid on mobile platforms like iOS. It can take from three days to two weeks to receive approval for each new version from the App Store, making it difficult to fine-tune to optimize on the fly.
• Many users don’t update their apps regularly, resulting in outdated, or “dirty,” data from the combination of “old” and “new” app version users. This makes it challenging to iterate and improve your app based on user data without being misled, unless your data tools easily filter users by app version.

Biggest Opportunities

• Design the app to use data-driven back-end systems to control user experience in-app when a connection is available on the device. This way, developers can dynamically tweak play balance, economy balance, etc., and then perform split-testing to further optimize customer economics.
• Use an analytics solution that allows filtering data by app version, location and device type (for Android). This is very important in addressing the dirty data issue, and in determining which platforms and devices in which to commit time, effort and resources.
• The free-to-use model proliferating on the App Store provides customers a risk-free opportunity to experience an application, which in turn provides app developers with free insights into their virtual economies and player incentives to gain the most effective conversion rates.

Monetization

Biggest Challenges

• Android users are still experiencing more friction in payments, resulting in lower average revenue per user (ARPU) and lower monetization rates in general.
• To gauge the quality of users, developers need insight into the in-app behavior of their paying users, which marketing channel they came in from, and ultimately how profitable their customers are by each marketing channel on an ROI basis.
• Developers need tools to monetize players that may not make in-app purchases.

Biggest Opportunities

• Optimize game mechanics that encourage purchasing, while balancing engagement. Use analytics to see how the two play out using custom event tracking and funnels.
• Individually track each and every revenue channel, from in-app purchase to advertising yields, understanding the best price points, for-sale item mix and conversion funnels–ultimately using data to understand and optimize the economy underlying the game.
• Employ messaging tactics to remain connected with users on new features/offers, e.g., push notifications and email. Oftentimes, re-engaged users will monetize at a higher rate if the user experience is tweaked and re-targeted to them.

To conclude, remember this: While social and mobile platforms have their differences, user behavior in-app is very much the same. To that end, using the ARM funnel to measure and optimize your mobile application is just as applicable as it is for social app developers. At Kontagent, we are strongly encouraging mobile app developers to not start from square one. Indeed, take advantage of the important lessons we’ve all learned on Facebook and other social platforms to improve the acquisition, retention and monetization of your game, and ultimately your bottom-line.

Click on the image to register.

If you’d like to learn more on how using the lessons learned in social can work for you in mobile, you can view our webinar, From Social to Mobile: A Playbook for Building Successful Games. We have an expert panel lined up, and will discuss the challenges of developing games and applications in mobile that didn’t exist in social, as well as provide tips and tricks for monetizing that you can use to improve the profitability of your mobile apps.

Republished from:
Social Times: How Lessons Learned in Social Will Give You a Head-Start in Mobile
Gamasutra: Applying Lessons Learned on Facebook to Mobile App Development

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About the author: Josh Williams is president and chief science officer at Kontagent, where he oversees strategic revenue projects, data science and R&D. A serial entrepreneur, Josh has led two successful start-ups to large exits (one in big data, one in gaming). Josh is an investor and loves collaborating with other entrepreneurs.

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.