Exactly. The default of the major search engines is we type in what we're looking for and usually get results. The commenter had a different experience with DuckDuckGo enough times to avoid it. We immediately know it gets inferior results to the status quo search engines. Many will avoid it on that basis. Other commenters might show up with detailed information on what kinds of queries succeed or fail. People wanting to use a mix of search engines, esp surveillance-oriented & private, might find that information helpful.

Yet, the original comment was sensible just because of two things:

1. Everyone on the Internet that uses a search engine knows what a good or bad one is. It has one purpose: turn your query into information you can use. If people say it doesn't or it's "shitty," then it's not doing it's job as a search engine effectively. All we really need to know.

2. The more specific information is better directed at the DuckDuckGo support or development teams to help them improve their alogrithms. Posting piles of data in Hacker News comments would only seem useful for the use-case I described above, people studying effectiveness of search engines via terms + results (better done elsewhere), or people reverse engineering DuckDuckGo's algorithm. I don't see why we'd expect people to produce or post that data as it's a lot of work and screen space.

1) Users do not know how to tell a good search engine from a bad one. There has been a lot of research on this, and it has been shown in many different ways. Here is one paper that is ranked highly by google scholar. It shows users cannot reliably tell a good result ordering from a bad one -- the result presentation is more important than the ordering. Other research has used more sophisticated techniques than "ask the user" to show that there are, indeed, "good" and "bad" orderings. http://onlinelibrary.wiley.com/doi/10.1002/asi.20941/full

2) There is at least one ddg developer here (not me), and HN is generally a good source of constructive feedback for startups. Maybe the original commenter's query string would help ddg or a competitor improve their product.

> Users do not know how to tell a good search engine from a bad one.

I am sure there is a presentation bias. I am sure that there are plenty of cases where a user cannot tell if a set of results are good or bad for a specific query. I am sure some users have trouble communicating why they think a specific result is good or bad.

However can people tell the general quality of a search engine? Absolutely. Google's simple aesthetics certainly helped them, but they didn't become the top search engine by luck and aesthetics alone. AltaVista, Yahoo, Lycos, Excite were all junk compared to Google, even the first version. It was very obvious.

I totally agree that google blew its competitors out of the water in the 90's. I switched to Google literally ten seconds after running my first query!

The research I'm citing is from the late 00's. At this point in the game, differences in search relevance are in the measurement noise.

1. Ill look at the scholarly results later out of curiosity. So far, the "found what Im looking for metric" is very strong anecdotally with widespread acceptance. Maybe Ill change my mind. We'll reject all opinions on the effectiveness of the engine in favor of whole, search histories on DDG and Google with terms and resulting HTML files as sole form of feedback in HN comments. Each user will do it for same terms for reproducibility or countering per-user generation biases. We'll discuss these specifics. This will lead, instead of claimed "good" or "bad" results, to claims of X terms or Y category having Z probability of accuracy or acceptance. Our discussion of DDG will be objective, scientifically accurate, possibly free QA for DDG, and likely be ignored by almost everyone everywhere (including most HN readers) outside CompSci or startups studying search engines. Im game, though, if there's a consensus here that we only discuss search constructively, objectively, and scholarly. ;)

2. DDG has contact info. I maintain that it's better to send data directly to them if one is troubleshooting it or helping them improve the product. Hoping a random employee is on same tech forum is a stretch despite it happening here more often than average. So, if we all did search data, we'd post it on a dedicated forum they host after we email them about the project.