Revealing the needs / customer value

After the initial pre-research scribbling phase, my googling went straight to answering:

What are chatbots and Turing tests and where are they at?

And then, when I realised I was skipping the actual value, I returned to the heart of the matter:

Why play games at all?

The true need here is to enjoy yourself. This is, after all, a little game app. A bit of fun. Light entertainment.

Sure, it might have the potential to learn from millions of chatbot ‘trainers’ all over the world and create the ultimate more human than human AI, but that all hinged on the game actually being FUN and GOING VIRAL. Serotonin needed to be released. Tongues needed to wag.

Taking a passing glance at the research around why we play games, scientist Nick Yee who did a big famous study on online gaming and suggests that there are three key motivation components:

The Achievement component —a desire to advance in the game, the interest in the rules and system of the game, and the want to compete with others.

The Social component — a desire to form connections with others, liking to chat and help other players, and the want to be a part of a group effort.

The Immersion component — creating and customising a character to play in the unique story of the game as well as wanting to a escape from real-life.

Meeting those needs

Based on the problem definition above I came up with the following mission statement.

Enjoy competing with friends and strangers to develop the ultimate chatbot that is “more human than human”.

This will be achieved via these three goals:

Provide a simple bot competition and upgrade system with clear achievements, current ranking and match performance stats. Easily share successes with others and invite friends to play Allow players to customise their bot, not only in personality (learned Q&As), but in Operating System, accessories, and a modular look and feel to the avatar.

Design

Now we know what we want to achieve through so we can start designing…

Focusing on fun guessing games, and my wife being an avid boardgamer (Euro-style, not Milton Bradley), I immediately thought of the French card game, Dixit. It has the following attributable elements:

Trying to convince the other players of something

Clever rules to promote ‘grey-area’ thinking, rather than absolutes

It is great fun!

Persona — 19 year-old Michelle

As we have no market research of any kind, choosing an ideal user group is kind of hard. That being said, it is much easier to empathise with a real person rather than a hazy, demographically ambiguous crowd.

I decided to pick a friend of about 19 years old, called Michelle. Despite being an adult she still loves lego, Minecraft and her programmer Dad has infected her with nerd. She is the sort of person who likes playing games, learning and sharing experiences with friends at university. She might be an amalgamation of three people I know ;)

My aim here is to reflect on what she would find engaging, or too hard to follow in terms of complex interactions or technical language.

Game Rules

After some discussion with my wife, we came up with this sequence for a round of play:

Write an opened-ended question (not a yes/no) and submit for the round (this saves waiting for people to think of one after being matched) Get matched with 3 random humans and a bot (everyone is anonymous) Answer each question as they pop up (including your own), looking at other player’s answers to see who might be a bot. Note — your own bot will autofill the answers! You can submit them as is, or overwrite with your own improved answer. This is how you train your bot and improve their knowledge. Your bot will therefore ‘learn’ new and better answers. Once all the questions are answered, everyone makes a secret vote for who they think the bot is. Once everyone has voted you see a summary score showing if you guessed correctly or not, and if anyone suspected you were the bot.

Points are awarded in the following way:

You guess the bot player correctly — 16pts

A player didn’t guess you were the bot — 3pts each (for a total of 9)

So you can earn between 0–25 points per round. I wanted the points to reward being as human as possible, but not get into negatives. (People should feel they are moving forward with each round).

I’m sure some Game Theory students are shaking their heads, but hey, this is UX design challenge! It’s enough to start designing. Assemble the rectangles!

Sketches and wireframes

Below is a first stab at the core user flows. Here I’ve covered the Bot summary screen, which is essentially the home-screen. From here you can jump into a game. I’ve also included a basic onboarding with an intro screen, a place to choose your default bot Operating Sytem, and then a coach marks / overlay screen for the Bot summary screen.

Not shown — the Trophy screen (accessed from Bot screen), the Shop where you can buy all manner of accessories (also accessed from Bot screen), and a general menu area for the usual account management stuff.