I never understood why the "collaborative filtering" approach never took off with most review options. Google Maps shows you what the average person thinks is a good restaurant, meaning the rich get richer faster and tiny statistical noise converts to durable competitive advantage.

Instead, I'd love for Google to understand me well enough to show me which restaurants I would disproportionately love compared to other people based on its understanding of my taste profiles. That way, the love can be shared amongst a much wider base of restaurants and each distinctive restaurant could find its 10,000 true fans.

On top of that, it actually gives me an incentive to rate things. Right now, you only rate from some vague sense of public service instead of "this can actively improve your experience with our product".

It's not just Google Maps, Netflix used to operate on the model of deep personalization that they've slowly de-emphasized over the years. I'm still waiting for Letterboxd to introduce a feature to give me personalized film recs based on the over 1000 ratings I've given it over the years as a paying customer but they seem in no hurry to do so. Amazon used to take your purchase history into account when ordering search results but I think that's also been significantly de-emphasized.

About the only arena this is widespread is streaming music services like Spotify.

I have a theory: They realized the right approach is to focus purely on the yes/no of what you choose to consume, rather than trying to optimize the consumption experience itself.

Remember how YouTube and Netflix used to let you rate things on 1-5 stars? That disappeared in favor of a simple up/down vote.

Most services are driven by two metrics: consumption time and paid subscriptions. How much you enjoy consuming something does not directly impact those metrics. The providers realized the real goal is to find the minimum possibly thing you will consume and then serve you everything above that line.

Trying to find the closest match possible was actually the wrong goal, it pushed you to rank things and set standards for yourself. The best thing for them was for you to focus on simple binary decisions rather than curating the best experience.

They are better off having you begrudgingly consume 3 things rather than excited consuming 2.

The algorithmic suggestion model is to find the cutoff line of what you're willing to consume and then surface everything above that line ranked on how likely you are to actually push the consume button, rather than on how much you'll enjoy it. The majority of which (due to the nature of a bell curve) is barely above that line.

I think Spotify and other streaming services have a problem very similar to the restaurants. Take an artist with a 40 year career and a dozen acclaimed albums and bags of songs almost everyone loves, and when that artist comes up it is always the same one or two songs. The most played songs, causing feedback and making the problem worse. In my mind, one of the core reasons for asking for recommendations is to discover something different, which means ignoring or maybe even penalizing popularity, because you are likely already familiar with the popular by definition.

I have horrible news for you. Google had it, then they killed it

https://www.reddit.com/r/GoogleMaps/comments/1737ft9/google_...

If the service actually shows you things you want to see, then you're less likely to click on ads (or "sponsored results") which you also don't want to see.

Perhaps more importantly, if such organic growth is possible, it lowers the incentive for businesses to buy ads.

>Instead, I'd love for Google to understand me well enough to show me which restaurants I would disproportionately love compared to other people based on its understanding of my taste profiles.

I don't want for Google to collect data on me, build a profile and "understand" me. I want Google just to return relevant search results.

I was part of the team that built exactly this. It launched in 2010. Some Googlers of that era are probably still annoyed at all the internal advertising we did to get people to seed the data. This is one of the launch announcements: https://maps.googleblog.com/2010/11/discover-yours-local-rec...

> Google Maps shows you what the average person thinks is a good restaurant

I'm fairly sure this isn't true. At least, I still get (notably better) results searching while signed in. Couldn't tell you what the mechanism for that is these days, though. But at least back in 2010, the personalization layer was wired into ranking. You can see in the screenshots how we surfaced justifications for the rankings as well.

Pretty much immediately after launch, Google+ took over the company, the entire social network we had was made obsolete because it didn't require Real Names(tm), and a number of people who objected (including me) took down all our pseudonymous reviews. Most of the team got split off into various other projects, many in support of Google+. As best as I can tell the product was almost immediately put into maintenance mode, or at least headcount for it plummeted like 90%. Half of my local team ended up founding Niantic, later much better known for making Pokemon Go.

As for why collaborative filtering didn't take off, I can offer a few reasons. One is that honestly, the vast majority of people don't rate enough things to be able to get a lot of signal out of it. Internally we had great coverage in SF, London, New York, Tokyo, and Zurich since Geo had teams in all those places and we pushed hard to get people to rate everything, but it dropped off in a hurry elsewhere. The data eventually fills up, but it takes a while. I'm told we had 3x the volume of new reviews that Yelp had at the time, but Yelp mostly only covered the US, while Google Maps was worldwide, so density was quite low for a long time. It was probably 5-10 years before I started hearing business owners consistently talk about their Google reviews before their Yelp reviews.

Another thing is that people are really bad at using the whole rating scale. On a 1-5 scale, you'll probably find that 80% of the reviews are either 1 or 5 stars. Even more so in a real life situation where you meet the humans involved. While you can math your away around that a bit, at that point you're not getting a ton more signal than just thumbs up/down (anecdotally I've heard that's why Netflix moved away from 5 stars). And then at that point, you might be getting better signal from "were you motivated enough to rate this at all?", which is why there's the emphasis on review counts. Many people just won't review things badly unless things have gone terribly wrong. I sat in on a few UX interviews, and it was really enlightening to hear users talk about their motivations for rating things, many of which were way different than mine.

> About the only arena this is widespread is streaming music services like Spotify

And even they can't get it right, and will give me promoted content before they give me anything related to my tastes. Pandora is the only recommendation engine that actually gives me what I would consider to be valid results. Shame they refuse to improve their audio quality, or I'd jump ship to Pandora. Until then, I'll keep using their free tier to curate Spotify playlists.

Beli is a pretty popular app with this functionality

related to your letterboxd suggestion, https://couchmoney.tv is quite good! it uses trakt instead of letterboxd but it's given me quite a few good suggestions. their FAQ describes a similar approach to what you've been talking about, it tries to find movies and tv you like disproportionately like.

> Instead, I'd love for Google to understand me well enough to show me which restaurants I would disproportionately love compared to other people based on its understanding of my taste profiles. That way, the love can be shared amongst a much wider base of restaurants and each distinctive restaurant could find its 10,000 true fans.

This kind of ties into "but your computer is broadcasting a cookie and you're being tracked" paranoia though.

People have been convinced by uninformed twaddle that somehow folk are looking through their screen at them to see what they're doing and that this is bad, but it also means you get fed an awful lot of adverts that really don't fit your demographic.

I don't mind if advertisers or supermarkets are profiling me based on things I like. You want to show me things I like? Good. The flip side is I'd prefer you not to show me things I don't like.

Youtube seems to be hilariously bad at this latter part, and all I get are adverts for a bank I'm already with and have been for 30 years, adverts for online gambling sites which I will never be interested in, adverts for Google's AI slop which I will never be interested, and adverts for online grammar-checking services that don't work in the UK because they convert everything into some weird North American creole dialect, which - again - I will never use.

Yes, take a look at my restaurant-using profile. Recommend stuff I like.

> Instead, I'd love for Google to understand me well enough to show me which restaurants I would disproportionately love compared to other people based on its understanding of my taste profiles.

I mean... this sounds like the perfect use case for a third party app like "My taste restaurant finder"? There are undoubtedly apps out there like this.

I don't think Google Maps (a general purpose maps app) should try to be everything for everyone. It's good enough for what it is.

The reason is money. Google (in spite of what they would have you believe) does not show you what is "good" for you, it shows you what it gets paid to show you (paid in various, sometimes very complicated ways).

I am sad that Google services are so popular, because it makes the world a little bit worse for everyone. This includes not only Google Maps, but also Gmail (did you know that Google is quite active at censoring your E-mail and you will never see certain E-mails?).

I would really like to see more competition, ideally without the ever-present enshittification (I'm pretty sure Apple Maps will go down the drain, too, because KPIs and money).