Not quite. It's first a search engine, so I index latest HN posts and a few other sources. There's then an algorithm that classifies new feeds as either "good" (personal blog, little ads, first person writing etc) or not. Then yes, it's those RSS feeds ranked chronologically. But the point is, it's not a curated or set list of blogs.
Thanks! I actually read your note on `use Cache-Control max-age HTTP headers for a "do not poll again before" time: savings of 10x or much more are likely if the feed server is set up well: an unnecessary feed poll avoided entirely is the cheapest kind!` and realized I don't currently, so adding that tonight.
Yea. Though, GA does (at least) two things: analyzes your own data, and, uses the data they collect from all their other sites to improve your experience via better bot detection, recommendations, insights. Google's network is useful, like it or not, for a) their cross device graph - they know which mobile devices and which desktop browsers are the same user (ish) and b) from that, building better MTA models than you can with pure first-party data - especially if most of your traffic isn't logged in.
But I agree, the future is pointing toward a world where privacy and empowerment is more in the hands of the user, and that's a good thing.
Yea, I think we're saying the same thing. Ultimately both the best choice (for privacy, performance etc.) and the one that's most likely (given adblockers and and ever increasing push for privacy from browsers and OSs) is to stop trying to find a way around adblockers, and simply invest in the technologies that work - http, cookies, sessions, logins, and os on.
Server-side tracking has been around for a while (indeed this article is dated Nov 15, 2020; and of course, you could argue simply parsing your Apache/nginx logs to get visitor stats has existed forever). The article I think conflates several different pieces.
There's probably a few actual use cases marketers may care about for tagging/tracking/analytics:
1. Simplest: I want to know how many people use my site/app, how many come back, how many are real (not bots), which pages are popular, etc. I'd like to see all this in a nice UI where I can cut and filter the data.
2. Same as #1, but I'd like to do it across devices. Still all within my own site/app, but simply connecting a non-logged in session across desktop and mobile web. Google and FB probably have the largest available dataset on this.
3. I'd like to enrich all this information with data from other sources, for example to target ads, serve ads, etc.
Site owners/marketers then try and tackle these in a few ways, the first 3 equally bad:
1. Just dump a bunch of scripts into your site (GA, FB, Segment, whatever). Pros: easy. Cons: very easily blocked, so your data is super biased.
2. Self host some of these scripts, or CNAME them. Pros: maybe a bit better for performance? Cons: still rather easily blocked with content signatures etc. A nightmare to ensure consistency if self-hosting.
3. Run your own JS that sends events to your server, and then your server fans out to whomever. Pros: much harder to block, and likely quite performant. Cons: its unlikely your self built lib is going to give all the same 'features' as GA (features meaning device fingerprinting and so on).
4. Just get everything from HTTP logs. Pros: very performant, can't be blocked. Cons: much more limited data to work with.
Personally, I think #4 is the future (and also where we started 20 years ago). What I don't think anyone is doing yet is relaying that data out to all the other parts of the stack: GA, FB, Mixpanel, whatever. If you could solve both - giving users privacy and performance and giving marketers the same tools they're used to - sounds like a win. You might argue "well we'd be missing a bunch of user data", but you're already missing it with adblockers and iOS privacy features.
Hey, first up really amazing work you’re doing, hugely inspiring for us! Thank you.
Whilst our focus has been delivering a consumer layer on top of all this data, yea, very open to exposing our underlying graph to others. Want to drop me a note at dan at alma.app?
As you mention elsewhere, half the battle is cleaning the data and getting quality.
Yep basically - looking at the network of grants (who funds who), people (who works where over their careers), social media and news (who’s referenced or cited alongside whom) and so on. You start to see interesting clusters of nonprofits that are funded by the same groups and work together extensively.
Yea can totally work - it gets at a lot in the zeitgeist in tech recently. I left Airbnb and started https://alma.app for similar reasons. We help companies with strong social missions (and their employees and their customers) connect with charities that share the same broad goals.
Many people I worked with would I think not only want to work with an agency that supports charities, but you could go a step further and also help those employees use their skills at the charities to volunteer, the companies support them too.