Life is Strange 2
Life is Strange is venerated by fans. Several Player Researchers even hold it among their favourite games ever, to the extent they have tattoos and Masters theses on the subject. It’s a unique experience, built from a combination of complex, relatable characters, captivating, socially-conscious narrative, and choices with meaning and consequence.
After the first game’s success, Square Enix and DONTNOD Entertainment wanted to make a sequel, boldly taking it in a different direction, exploring novel themes, with a new cast of characters, all while maintaining the series’ fundamental chemistry. At this early stage the team naturally had a lot of big decisions to make that would ultimately impact the finished game, so they sought to be as informed as possible when making them. Grounded in previous successful partnerships, they came to Player Research, looking to understand how people would play and experience the new game, Life is Strange 2.
Could players understand the overarching plot, and would it truly captivate them?
Building off these goals, we worked with Square Enix to generate some core research questions: How would the shift in setting be perceived? Would players empathise with the new characters? Would each choice feel important, and their effects impactful? Could players understand the overarching plot, and would it truly captivate them?
The first step of any games user research strategy is to partition the experience into critical components amenable to investigation: For Life is Strange 2, these boiled down to people’s desire to continue playing, their perception of characters, choice and consequence, narrative comprehension, gameplay ease-of-use, and overall, unified sentiment. We offer UX strategy consulting and training
An adaptable schedule of tests was designed to harmonise with the production timeline, providing coverage to all research objectives.
In synchrony with Square Enix and DONTNOD, an adaptable schedule of tests was designed to harmonise with the production timeline, providing coverage to all research objectives. Even before each episode’s gameplay was available, we started by testing the basic narrative in written form, using branching logic to simulate choices and consequences in a choose-your-own-adventure story read-through. We fleshed this out with early concept art to help players establish representative mental imagery (see image below). Research in such an early phase of pre-production provides some of the best return on investment.
Later, we would iterate towards full experiential playthroughs of close-to-finished gameplay, allowing us to understand how players experienced the cumulative results of the dev team’s efforts. Data collection was through bespoke-designed surveys at carefully chosen moments in the game, sometimes supplemented with post-hoc player interviews.
Testing against core goals throughout production provides assurance, action points, and protection against nasty surprises.
Playtesting a game split into episodes is an operational challenge. For instance, we had to ensure a sufficient supply of players who were up-to-date in the story. We couldn’t, of course, test Episode 3 with people who hadn’t played Episodes 1 and 2. Our participant coordinators designed new recruitment procedures, and booked extra “catch-up” lab sessions to ensure that when it came to testing later episodes, playtesters would be available who had experienced all prior episodes up to the one under investigation.
Our participant coordinators designed new recruitment procedures, and booked extra “catch-up” sessions
Similarly, it was important that when participants played each episode, the story path reflected the choices they had made in previous episodes. Given the game’s episodic nature, the technical infrastructure to save and load past choices was always in development. Researchers therefore had to meticulously catalogue every participant’s in-game choices so that they could be manually input for each one before they returned.
We delivered reports after each test, detailing rich insights into what players understood, felt, and did during the episode, focusing on key areas of characters, story events, and choices. In many cases, the insights reassured the team, with the actual experience players were having conforming to their intent. However, through focused investigation we were also able to pick up on crucial, targetable issues, and understand them well enough for the team to take action.
Our focus was always on providing useful information, applicable as an instrument in the iterative design process.
Our focus was always on providing useful information, applicable as an instrument in the iterative design process. It was not enough to report that players simply liked or disliked something, but to help the team understand the detail of why this was the case; to understand the grey areas and how to proceed.
Square Enix and DONTNOD Entertainment were strongly invested in making a superb game, and enhancing it through research. They cared about the findings, devouring our reports in depth and coming back with further questions. As a result, the value of the research can be felt throughout the game; in the plot, the dialogue, and the choices.
Let’s consider an important example. Early on, the team impressed on us that in-game choices should feel meaningful and complex, and that there should rarely, if ever, be an easy decision. From this we derived the general hypothesis that, if choices were as challenging as intended, we should observe a balanced split of players picking each option. This was now an operationalised objective – something we could test. If we saw a strong tendency for players to pick one option over the other in any of the major game-changing choices, we would hone in on it and try to understand what made that option more attractive. We wanted to know why players made the choice they did. What were they weighing up in their minds when they made the decision?
If choices were as challenging as intended, we should observe a balanced split of players picking each option
This approach was particularly valuable when it came to one of the game’s biggest decisions in the season finale. Early testing showed a huge imbalance, with the vast majority of players picking one option over the other. Through careful, well-timed questions to our players, and detailed qualitative analysis, we unpacked players’ motivations, and isolated their roots in the narrative.
Empowered with this level of understanding, the team could re-tune their emphasis on different aspects of the plot, and thereby counterbalance the antecedents of the choice to make it a more nuanced decision with no easy option. A much more even split in follow-up testing revealed how effective this intervention had been – something we see replicated in large scale analytics from the released game.