Centrality of participation:
This is clearly inspired from the choice-driven examples we showcased, and I think it follows the invitation pattern well. I’m glad you were able to mock this up in HTML; that really helps understand how it feels to go through the interactive.

Rationale for design choices:
The interactive matches the idea of an online car magazine pretty well. The results of the interactive are a little hard to read – I think further iteration is needed to make it clear and self-explanatory.

Layers of reading:
The article and the invitation to put in your own criteria are the main layers here. The results visualized add more in. I can see the path to further information, but would appreciate a stronger link fro the quiz back to the accompanying article (because I think the quiz is a lot more shareable online). You suggest this in the video, and I think it is a good idea.

Appropriate data use:
Your sample selection is justified well. I like the addition of the price data and the rationale for it. The bar chart of pollution vs. cost has an aesthetic feel that matches the idea of a car magazine (for me), but doesn’t really match the rest of the visual treatment. You’re highlighting a bunch of the dimensions of comparison here, but I think you aren’t remembering some of the lessons from the “charts and graphs” sketch – ie. echoing the story of the chart with text above, removing extraneous decoration, etc.

Suitability for audience:
Casting yourself as a car magazine obviously resonates well with the dataset you’ve chosen to work with. I think the data dives would appeal to the technically minded of those readers, that that glut of charts probably makes sense here.

Narrative:
The story that pairs with the interactive has a nice lead in – focusing in on sports cars and pollution. I think have a tighter link between it and the interactive would help us understand how they fit together.

Call to action:
The audience here is those thinking about buying a car, so your goal of informing them more based on the data about the cars makes sense. The interactive accomplishes that well.

I think integrating the data into an algorithm is a smart way to make this tool — so the average car buyer doesn’t have to think about any of the small details. One suggestion I would have is that I think many tools to help consumers pick cars based on a preference quiz do exist already, so I would be interested in a feature or design that might make your tool more unique. For example, I think graphics and design can do a lot to communicate to a particular audience. Anyways, thanks for sharing!

One thing that might be helpful for the user is to suggest options that are considerably better for the environment but lie slightly outside your selection, for example, if the user has selected a standard SUV and there’s a greener small SUV option, that sketch could also suggest that.

One minor suggestion if you were moving this beyond the sketch stage would be to integrate the choices with the graphs a bit more (perhaps side-by-side), so it feels more interactive. That way, it is easier for the user to switch between options and see what changes.

I think that the encodings in the pollution to price comparison can be a little bit confusing to read. The lines connect across discrete (I think) score ratings, and for a single score, it is not clear that the different points represent parts of the same distribution. In addition, I would question whether you need to encode the avg price with thickness when you already have the 50th percentile as an “average” measure.