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RESEARCH TO STRATEGY TO EXECUTION

Case Study #1: Pac-12 Networks​

I was hired a month before the Pac-12 tv networks launched. The network was started by the Pac-12 college sports conference. It had very little to start out with. The conference had press releases and a schedule on the website. The apps were just for watching the live network, no other content, and they were designed quickly by a 3rd party before I arrived. 

The Big Question

What should we do with the apps and the website (and social media) to engage fans and increase viewership?

Getting the Answer

I had previously managed the redesign of Yahoo! Sports and had done several cardsorting exercises to see how people related to, and organized, relevant sports content. This included scores, stats, game highlights, season highlights, player bios, everything. 

What I found is that people organized content around, and wanted the most information about, two things: games and teams.

In the Pac-12 context teams meant Oregon football or Stanford women's soccer. If your favorite team is Arizona men's basketball then all of their games have meaning to you. Or if a team or player is about to break a national record, that game might be meaningful to you, even if the teams involved aren't. 

What Content to Aggregate Around Games and Teams

Determining this depended on what fans wanted and also what we at Pac-12 created or had access to, and what others had access to, as well. We weren't going to beat ESPN at college football stats. But we did beat most competitors at video content. Especially for all the sports and teams that ESPN didn't focus on. And if we made tune-in notifications etc on social media more specific to individual Pac-12 teams then the team and school accounts would share it. 

The content we prioritized around these games and teams were options for tuning in, video highlights and features, behind the scenes content and content from the schools/teams themselves. 

I led the redesign of the Pac-12 website that prioritized automated individual game pages (event templates) for every Pac-12 event. This gave us a great long tail of content that performed well on Google. 

Pac-12 Reaching & Engaging Fans

Pac-12 Event Templates

I then layered on flows to the Event Templates that enabled people to more easily find out how to watch the games and also set game or team alerts. 

How to Watch

Then I pushed to replicate the team and game focus (with videos!) on our apps. 

App Redesigns

(Each individual project page outlines the outcomes for the projects.) 

Case Study #2: Sigma Computing​

The Big Question

Sigma had historically sold their BI data analytics product to data teams within SMBs and enterprise companies. They wanted to sell directly to business (less technical) users. But which ones, and how?

Getting the Answer

I took a two-prong approach, find out which existing business users were successful in Sigma and identify why, and also find out from external non-Sigma users what data analytics use cases mattered most to them. 

The existing business users whose qualities correlated most to extensive Sigma usage were users with decent spreadsheet knowledge and a basic understanding of how data works in databases. And it correlated to people who tended to push through and find answers when they were stuck. Overall, this meant people in Operations and Product departments.

We also included Marketing as a target department because that department tended to have a larger budget and be willing to spend it on tools. 

Identifying Use Cases Once Departments Had Been Identified

Once we'd identified target departments (Marketing, Operations, Product), and also Finance I identified ideal use cases to use to showcase Sigma's capabilities. These use cases had to be both common to that department and important/valuable to them.  

For Marketing users and prospects this meant Campaign Spend Attribution and for Operations folks this meant Logistics Optimization.  

For Marketing I worked with designers to create a DIY data experience for marketers to see how easy Sigma was to use, and incentivize them to try with their own data in a Free Trial. 

Sigma: Identifying Ideal Customer Profiles

Sigma: Selling to Marketers

Sigma: Improving Product Usability

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