[MRSallee]

Yes, you can make an image that compresses to a smaller raster image vs. SVG, and complexity is a good way to do that. Especially possible if your image/logo isn’t just solid colors, but contains gradients or textures.

I would guess, though, that if you make a logo that is larger as an SVG than a compressed raster, you’ve probably made a bad logo. Logos should be simple.

[Twirrim]

> Logos should be simple.

Agreed. Simple but important things to also consider with Logos include "What does it look like if printed in black and white?" It's a bit outdated advice in some regards, based as much on letter headers, fax machines, and news print adverts, as anything else. You'll notice that almost all memorable logos work really well in black and white, though.

[eru]

Black and white is a good exercise in general, eg also to check whether divers colourblind people will be ok. Or when you want to carve your logo into metal or wood etc.

[jordache]

"simple" that's a very subjective term.

Is there a way to quantify simplicity in terms of SVG? Can we say number of points & number of paths? What other constructs can be used to measure complexity?

[gvx]

There isn't really. Any of those things could be used as proxies (plus file size, number of XML elements, rendering time, and more), but the thing we are really interested in is subjective anyway.

File size after rendering to bitmap and lossy compression, like JPEG, might actually be one of the best quantitative proxies for simplicity, because lossy compression algorithms are designed to compress visual data that's interesting to humans well. Maybe an interesting experiment: take a whole bunch of logos and/or other images, let people rate them on a Likert scale or something on simplicity, and see if there's a correlation with JPEG file size.

[egypturnash]

For what it’s worth, JPEG is great at reproducing photos and terrible at reproducing sharp color translations in "simple" logos.

[ovao]

For SVG, stripped filesize is actually a fairly good indicator of complexity.