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With EEG they compared how active players were depending on what ship they use. Battleships, cruisers, destroyers, carriers. So they can see the actual boring vs active parts the players experience, with real brain data.

Torpedoes trigger brain responses. Especially mood goes up if they hit something during battle.

The methodology is limited I some ways. EEGs are sensitive to noise, it's subjective between subjects, and it cannot measure emotions, only Valence or mood. And eye trackers have calibration and accuracy issues. It's also sensitive to eye colour. It calibrates more quickly with light eye colors

Also, both hardware and software is very expensive. Then add crew and time, and it's costly. It can easily cost $15.000 a year for hardware and software rent, for example.

EEG can help with the discovery stage of the double diamond. Eye tracking and EEG are advanced tools. Classic tools like interviews and observations are still good and baseline. You have to have those. But if you can get more, then EEG adds new insights that can be helpful

Essentially it becomes particularly helpful if you need to justify a certain cost, venture, or push. (So if the choice is a very expensive choice, or a one way door choice, then it can be nice to really know for certain how players think and feel. But be very clear about what you measure!)

Can you change the first time user experience of a game 7 years after launch? Let's find out in our next talk, featuring June's Journey. A hidden object game, free to play, on mobile, it's a flagship title for Wooga

They have new content every single week for the last 7 years. It would take you 4 years to go through all content if you started playing right now. (Woah) But as always, retention is tough.

For their peers in the space, retention is going up. But for themselves, it's going down. That's bad, so let's fix it. (Also yes the Y axis marker is missing. He cannot share hard data, but the gist is clear)

So let's find out: Legacy UX, do you rebuild or repair, and what is the lost knowledge of the original onboarding of users? Why was it done that way?

Starting off: Lots of primary research of players. Which creates a lot of data, and it was hard work to organize it all.

Data clearly showed issues on day 2, 3, and 4. Some kind of issue must be present there. What could it be?

Turns out users were grinding scenes without rewards. Progression was too slow. Users were unsure how to unlock new scenes.

For secondary research, playtests were held with the team. This is valuable, but solutions are often thought of too quickly. There is a risk of confirmation bias, and to not solve the actual underlying problems.

It still created valuable data though. You spot things you may not have otherwise spotted, also because you know what to look for from the initial user data.

Example: Even a screen with two buttons can be confusing for a new player. What does a blue button mean? What is a green button? Is the left button the most important button? Even the basics are hard!

Goal: Increase retention by 1%

They made the start screen just one button. Moved connection button to top right, much smaller. This improved retention by 2.5%

They added a hint button to help players. This reduced retention by 2.2%. Players would just hit the button all the time, and the game became a chore instead of playing an actual game and having to think.

They added an overlay on how to play the game. This increased retention by 1.8%

Key takeaways: Keep it simple. User stories can save your sanity. Always include your team. Build your research process. So that when you need to apply research, you can do so right away.

(I missed the last two talks as I had a long and good discussion with someone about hyped technology systems and confirmation bias. I'll link some things here that I think are important to relate: 1. mikelovesrobots.substack.com/p/wheres-the... 2. metr.org/blog/2025-07...

(3. @edzitron.com's work: www.wheresyoured.at/ai-is-a-mone... 4. The video I made recently in relation to blockchain, metaverse, and LLM AI in gamedev: youtu.be/CeZ_rcDQg6Q?... The earlier talk today that mentioned confirmation bias made me realize this is all related to those hypes.)