u/lug2lug_co

Hey again! So my last post about the Lug2Lug visual search feature got a lot of positive feedback, so I figured I’d make a dedicated post about the app as well (link in the comments).

I am kind of a perfectionist in the sense that I don’t like to buy something unless I can convince myself it's the best option for me, and to make that assertion, I need to know what else is out there. I’m sure you know firsthand how difficult it is to actually discover microbrands if you’re not really in the know. 

So I built Lug2Lug to help me, and I hope it can help you too. 

A few things it does: it learns the kinds of watches you like, so your recommendations improve the more you use it. For any watch, you can pull up its alternatives, similar picks that are the same for everyone, objective and based on the watch itself. And it looks at your taste against what you actually own to find the gaps. Say you save some GMTs but don’t have one, it’ll notice. It made me realize that I should probably look for a rectangular dress watch next, which is true.

The app is definitely not perfect, but it has come a long way, and I’m proud to have made something I think is genuinely useful, and I hope you do too.

Some notable features:

• Customizable recommendation algorithm
• Frictionless collection tracking and sharing
• Snap a photo to identify a watch (the upcoming release drastically improves this as well)
• Community consensus (AI compiles a consensus from several sources and threads from around the web about a watch's pros and cons). All sources cited and clickable
• Community features, like posting wrist shots, publishing comparisons to ask the community, and discussion posts.

Which brands am I missing, and which features can be improved? 

Right now it’s available on the iOS App Store (link in the comments), but also let me know if any of you would be interested in an Android app.

UPDATE:
First off, thank you all so much for your feedback. It's been a ride building Lug2Lug, and it's great to see that so many of you find it useful. I will add as many of the things you've suggested as I can.

It's also very clear to me that a ton of you want an Android app, so I'll begin working on that immediately.

Finally, it looks like Apple approved the latest release! Try out adding your collection by just snapping a photo of your watches. It isn't perfect, but it's definitely improved compared to the previous versions. Once again, you can find the link in the comments :)

Happy fourth!

Long story short, I've been building a microbrand watch discovery platform and, in the process, am accruing a LOT of data (6,500+ watches and 370 brands). As someone who has experience generating figures from large datasets, I couldn't help but make a couple of plots (and actually found some pretty cool use cases). It isn't perfect: anything visual, like distinctiveness and boldness, relies on CLIP image-similarity, which only sees what a watch looks like, not its actual lineage. But I still thought I'd share it with you all as I find it quite cool.

Basically, you can plot the whole catalog on whatever axes you want (price, case size, thickness, water resistance, visual boldness, distinctiveness, dial color, movement, brand tier) across X, Y, and Z. Adding a Z axis rotates it into a 3D scatter. You can also color the dots by a fourth variable, including how well each watch matches your taste, if you've been using the site or app for a while. You can hover over any dot to see which watch it represents.

Then, and here's the fun part, you can lasso-select a region, and it filters the entire catalog down to those exact watches. And any of the site's pre-existing filters also apply to any plots you generate. As a quick example, lasso the cheap-but-nobody-else-makes-it corner of a price vs. distinctiveness chart, and it essentially surfaces "standouts" for anyone saying that they're too boring these days.

Microbrands score highest on distinctiveness of any tier. The other tiers sit fairly close to each other; what separates microbrands is that they skew toward the extreme outliers (one-of-a-kind watches), and those standouts are almost all under $2k and time-only 3-handers. My guess is it's a risk-reward calculus, less to lose in going weird. Seems obvious, but nevertheless cool to see in the data. Homages sit lowest, which is fair.

There are also clusters, which are t-SNE (where proximity of points is a measure of similarity), so it's useful for local groupings, but the distance between two far-apart clusters doesn't really mean anything. My favorite is clustering by design families. Watches that look visually similar (as determined by image similarity) cluster together onto their own islands: divers here, Bauhaus dress over there, skeletons, pilots, etc., and you can visualize these relationships for a ton of different watches and brands. Basically, "I like this one, what else looks like it?" across a vast number of watches.

Across all of this, you can also highlight by archetype to see how styles shift across the variables.

It's a desktop thing for now; the charts and clusters need the screen real estate. It's free, and you don't need an account to use it (though I'd appreciate it. I’m still trying to grow the platform!).

Let me know if you find it as cool as I do, if you come up with any interesting plots, if you have feedback/improvements, or anything else.

Enjoy!

The dial of this watch is so cool, and I get the historic appeal of hesalite, but I just prefer sapphire. What can I say…

Maybe a hot take but I prefer the 2824-2 movement over the H10. I like that 4Hz sweep and don’t really need 80hr power reserve. Plus serviceability.

Hi all,
(former) lurker here. I wanted to share something I’ve been working on for the past few months with the community.
As I’m sure many of you know, our hobby can be somewhat difficult for newcomers and even experienced folks to navigate, especially when it comes to discovering new watches and brands.

I made Lug2Lug to ease some of those difficulties. It's a watch discovery tool that combines a community-editable database (~3k watches, 84 brands as of today), a transparent recommendation algorithm you can tune yourself, an alternatives engine, real used-market prices, and integrated community features.

If you spot wrong specs or a missing watch, you can submit a fix or add the watch yourself from any page. The more people contribute corrections, the better the data gets for everyone using it. 

The recommendation algorithm is also fully tunable. You can first establish your preferences by choosing between pairwise picks, pinning reference watches, adjusting the weights yourself, and seeing why any given watch is being recommended to you. Under the hood, it uses perceptual image hashing of the dial, design-archetype tags, and weighted spec proximity to group similar watches. This also powers the alternatives feature, which surfaces microbrand alternatives, cheaper peers, and price step-ups from any spec page.

You can also load real used-market prices, build collections, post wrist shots tagged to specific watches, and compare watches side-by-side.

Open to any feedback or suggestions on brands or watches to add next.

Thanks for reading, and happy browsing

Love this watch. Breitling Top Time Deus homage. Super funky dial, and paired with a nice leather strap it looks easily 10x the price (I paid $120)

The color, the distortions from the double-dome crystal, the case size, heritage, everything is just glorious. I can't get enough of this watch.