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Could you make game design as certain as physics, chemistry, and biology? Could you as effectively describe what rewards you can give players, with certainty?

That would mean creating theories for many things that we currently do, such as: Fun, Matchmaking, UIs, difficulty, retention, rewards, and accessibility. We are good at post-launch rationalizing, but can we predict what happens before that?

This would require frameworks that allow us to gather this data, compare, contrast, and share knowledge. Of course, the usual barriers would stop us: Time, and money. But wouldn't it be worthwhile to do this work, and create more certainty?

Valve tried some of this. The reason DOTA 2 has items to trade is Valve wanted to see if the item economy from TF2 would also work in DOTA 2. It was a research project, comparing and contrasting. Creating theories.

Another example: ELO distributions: Luck vs Skill vs Combination. There is data, so gather it, compare it, create theories, put them to the test.

Other data you can gather, through surveys: Quality of match, quality of teammates, Quality of yourself. By adding that last question, 12.5% of millions of complaint reports went down, because it made players realize that sometimes, they were a problem themselves. So they would try to improve.

So basically: Try and apply theory. See what you can learn to create your own theories. Save the data and things you learned, and share them.

Next: EEG or Not EEG, for World of Warships testing.

They found out that experienced players would customize the UI (hell yeah) to expand the radar minimap. And with tracking they found that new players navigate by looking at the world, but experienced players navigated by looking at the minimap.

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.

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.