Big Data And Real User Stories

This project was a collaboration between Daniel O'Neil from The Understanding Group and Eric Kushner from Project Two Paths, Ltd.

It has never been easier to get or analyze data for your organization. Massive data sets that used to be available almost exclusively for the Fortune 500 exist all around us, usually collected almost by default, and at minimal cost, by the systems that we use to run our companies.

From Google Analytics to our merchant and fulfillment systems, insightful customer-centered marketing strategy is just a spreadsheet away! What is key about this explosion of data is that it requires an even greater commitment to story-driven strategic marketing. If data is not judiciously applied to the human narrative, marketing departments can be pushed into reactive, tactical activities against tiny bits of information. We think you should go big instead, and use the data for high-level marketing strategy and planning.

The approach uses three major principles:

  1. Marketing teams know their audience and should tell stories about them.

  2. Those stories should be testable with data.

  3. The collaboration between storytellers and data analysts should end with compelling user stories that drive focused, specific marketing campaigns.

Recently we had an opportunity to apply this framework to GamerSaloon, a brokering service for players who wanted to find opponents for cash video game competition. GamerSaloon’s revenue model is largely driven by frequency so they asked us to determine how to maximize player engagement based on the large dataset that contained ten years about players, the games they played, and their win-loss records.Players who sign up for GamerSaloon have a wide range of usage patterns, from playing multiple times a week for years, to trying only a game or two before moving along. A significant portion of accounts on GamerSaloon were inactive—that is, the player had signed up but had never actually played a game. We were asked to find out what these players needed to continue playing or why they never played in the first place, then develop a marketing strategy to engage them.

Getting Started: The Creation Of Initial Theories

We started by doing stakeholder interviews with the marketing and customer support team, as well as creating accounts and playing a few games. Our findings allowed us to create several customer segments, each one of which represented a story about a kind of player behavior. Our titles were designed to be human and memorable. Here are three examples:

  • Hey big spender: Players who deposit larger amounts initially are more likely to play again

  • The power of first impressions: The outcome of the first three games has an impact on long-term player value.

  • Interval training: The shorter the pause between the first deposit and the first game, the greater the long-term player value.The core concept used for the marketing analysis for GamerSaloon was an engagement funnel, where long-term, repeat game play was the desired end state. The initial theories were chosen with an eye towards inputs that could, based on our experience, be turned into specific messaging campaigns to improve the performance at targeted points in the engagement funnel from initial site visit through early game play.

The Acid Test: Checking The Theories Against User Data

Once the hypotheses were created, we examined user behavior data through three lenses:

  • How many of the theories were actually testable given the state of the data?

  • Were the theories supported or refuted by the data?

  • What additional patterns seemed to emerge from the data analysis that can be applied in actionable marketing campaigns?

The quality of the data on the player platform was extremely high, so we were able to test almost all the theories. As is typical when using this approach, about half the theories were supported by the data. Among the most notable findings was that the size of the initial deposit had a negligible impact on a player’s lifetime value and that a sizable number of depositors had never played a game. We also found a significant correlation between a player’s long-term value and their win-loss record in the first few games.

The most notable pattern that emerged from the data analysis was the identification of an inflection point for lifetime value in new players. We were able to define the numbers of games we needed to foster for a new user to substantially increase the likelihood that he’d be a "golden goose" versus a "one night fling."

Tying It Together: Creating An Actionable Plan

Once we gathered the data, we used them to support initial hypotheses, each carefully crafted with if/then clauses that could be effected through marketing strategy. The answer to each question illuminated a revenue optimization or customer acquisition strategy, and if it didn’t, we set it aside. The findings were valuable because we took the time to identify the addressable variable and approached it with ideas on how findings would impact our marketing recommendations. With a few clear options pre-conceived, we knew that regardless of the findings, we could act on them to positively impact the business. And again, in the instances where that was not the case we tabled the the hypothesis.

Where did these notions come from? We started by examining the mechanics of customer acquisition with our client’s business as well as their revenue model. At the end of the day, there are a finite number of ways to drive more revenue and they are as simple as they are universal:

  • More prospects

  • More customers

  • More frequent transactions

  • Higher value transactions

  • More transactions over the life of each customer

There are nuances, of course, such as time to peak spend and cost of customer retention and customer service and the like, but those are the nickels and pennies. Work through those after you’ve uncovered the quarters and dimes. Final tip: Start at the top of the funnel and work your way to the revenue end of it. Enhancements at the top compound on one another and earn the marketer the time to work at the narrow end of the funnel where the stakes are higher and the audience, narrower.

Outcomes And Final Thoughts

Identification of user experience obstacles for first time site visitors resulted in the development of a new user registration wizard that, combined with targeted email interventions, drove conversions up by nearly 7%. Similarly, the data revealed that many users failed to leverage the full breadth of the community. An issue that we mitigated with an email primer series that boosted game play from new users in their first two weeks by more than 100%!

What’s most notable about this project is how, even after years of cheap, widely available data, most companies are not making the effort to address their marketing channels with this approach. There are huge opportunities by creating user stories and big data for companies and organizations of all sizes to better serve their customers, grow their company, and increase their bottom line.

How Do You Balance Conflicting Demands On Your Website?

You probably have a range of people creating content for your website, and their goals probably conflict with each other regularly. That’s a pretty common situation, given all the jobs that a website has to do. The problem is, if a site tries to meet everyone’s goals equally, it will be mediocre and confusing. If you want a good site that holds together over time, you need to address these tensions and agree on how to balance the conflicting demands.

For example, an online news site may have one group that wants to emphasize local news that people can’t get anywhere else, and another group that wants to emphasize national news that people are interested in. One of the key functions of information architecture is to address competing interest. To do that, we use an intention model, which acts a continuum. An intention model provides a nuanced way of talking about what good means. It is an excellent tool for modeling the goals of big, mixed groups of stakeholders.

intention model

intention model

In this example, we'd make one side of the continuum is local news and the other side national news. Both are important, but having a clear, agreed upon sense of where to strike the balance between them will enable the team to make better, more consistent, and more successful decisions, right away and into the future.

On the continuum, stakeholders indicate where they think the website strikes the balance between the two ends today, by marking an X somewhere along the line. People do this for the current state, and for the desired future state. The results and discussion are powerful in aligning goals.

For any website, there are many sources of tension that need to be balanced—we typically identify 10–20 continuums.

To sum up:

1. Discover your continuum questions.(e.g., local v national news)

2. Survey your stakeholders to see where they land on the continuums

3. Discuss the results with all the stakeholders and develop a consensus for the future state

Need an alignment job?

Over the years, TUG has developed a proven process for translating competing goals into a plan that aligns your vision. The result is a digital place that will delight your visitors. We’d love to hear about your project and how we might help

the most concise definition of organization is simply agreement
— Dee Hock