Amplifying the Voice & Face of our Customers

ABOUT - Storm Runners set out to be Amazon's first successful mobile game, but at the start, we didn't know the kind of game we were going to make. With a small team of 14 and an ultimate business goal of Nk/day, we had to figure out what we were going to make and why. The team combined what the creative director and designers were passionate about making and market research data to guide our decisions.

MY CONTRIBUTION - I worked closely with our Product Manager to research deeper into the "what and why", exposing connections, marketing strategies and play motivations. I designed and conducted surveys for competitor players and set the foundation toward a collective vision by combining competitor data and secondary research archetypes to create personas and amplify the voices of our intended players.

DESIGN CHALLENGES - In games it can be hard to convince the team that they are not the player since most people in the industry are actually gamers. The concept of different types of players and designing for how they play specifically is newer to a lot of developers so keeping it transparent and collaborative was key to getting buy in. We came out with 2 personas that we had high confidence in but 1 that we deemed as a growth market, so finding overlap in the game design was a balancing act when trying to satisfy different needs.

‍

PROJECT  
Storm Runners - Amazon Games

TIMELINE
8 Weeks

TEAM SIZE
6 people

MY ROLE
Research, Persona Creation, Graphics, UX maturity

‍

Data Informed Foundation

  • We set the mobile game "Game X" as our nexus because as a group we felt they had "found the fun, were within our monetary goals and that we could improve upon it." I used Data.ai's (Formerly App Annie) cross-usage feature for the game's top 3 monetizing countries and the US to see what other games these audiences were playing or would be interested in.
  • "Game X" had broken top 100 grossing in at least 10 countries. 3 places it hovered around or above top 20 consistently were South Korea, France and Sweden. Looking at players' Actual Usage (what a "Game X" player is actually playing at the same time period) and their "Affinity" (how much more likely a "Game X" player is to play another game when compared to the general population), I took the games that had numbers that were close together, but were also over 10% actual usage to find patterns in what a larger portion of these Players liked.
  • We saw a high frequency of solo/high adrenaline games and social/strategy games. I paired this data with secondary research on marketing strategies that worked for Game X, gaming motivations and overall Mobile Gaming Trends.
  • Our PM and I then created 3 buckets of players - the early adopter, the mass market and the potential growth market as our starting point.

‍

Data.ai's cross game usage and affinity gave me the data I needed to create a full comparison chart that allowed me to see the patterns of the types of games these players liked.

‍

Data helped us get to the high level pitch of what kinds of games we wanted to make. Having this direction allows us to then narrow down player types.

‍

Digging Deeper for Play Styles and Motivations

  • I created and launched a survey on Usertesting.com to gather feedback from real word "Game X" Players. My goal was to get a deeper understanding of loves and frustrations of our competitor game, the genre as a whole, validate our secondary research and build accurate language for the most realistic Personas.
  1. 58 Players, ages 18-45, 5 players ages 14-17, Android and iOS, played "Game X" more than 20 times.
  2. 30 questions - 15 directly related, 15 to capture overall gaming motivations and behaviors
  • After the surveys were complete, I created an affinity map to build up our 3 personas and highlight opportunities to the team.
  • Players that liked this game needed more challenge, yet wanted it to be easier. Pairing this with players wanting more control, our business goals and looking at the strategy games people were playing, we were able to build out our growth market further. We created a hypothesis that this high action game could gain a new audience by adding strategy and exploration to it. They wouldn't be as bored with "the grind" if there was more to the game. We also knew that we needed social elements as a secondary goal.
Affinity map created from the survey data

‍Meet our Players

  • Taking all the above and cross referencing it with well established gaming behavior models such as Quantric Foundry's Gamer Motivation Model, we finalized our Personas. Giving faces and names to our Players allows our team to easily reference who we are building for. "This is a Sondra feature", "I'm worried this might affect Amir". We bring them to the meeting room or reference them in discussion.
  • These Personas become our screeners for external Play Tests and helped foster conversations with marketing.
  • All my personas push for representing the gaming audiences' richness. Showing diversity is especially important in tech and games where the teams tend to lack this representation. This type of work has even been able to spark organic conversations that lead to others overcoming their unknown biases.