[bambax]

Many, many big companies don't see any value in search. They simply use the defaults, and when those defaults are abysmal (like in the case of Confluence for example), well... they just suffer through it in silence.

I have so far mostly failed in trying to explain 1/ why search matters and 2/ that not all "search" functionality are equal and that building good search is an art form.

[marginalia_nu]

> I have so far mostly failed in trying to explain 1/ why search matters and 2/ that not all "search" functionality are equal and that building good search is an art form.

Yeah, it takes an absurd amount of tuning to make search work well. Given how poorly the average search field works in almost anything, it's fair to say this crucial step isn't happening.

I suspect a lot of organizations just don't have workflows that would tolerate someone spending a month tweaking search algorithm parameters. It doesn't look enough like work.

[andai]

Doesn't look like work, yet tragically, incremental improvements to "frictionlessness" represent order-of-magnitude improvements to user experience.

[marginalia_nu]

Oh yeah, it's definitely an organizational problem that's pretty widespread. I think it boils down to a general lack of trust, and a willingness to turn developers into a sort of assembly line workers.

[PaulHoule]

I went through a phase where I spoke to people who develop numerous enterprise search engines (e.g. OpenText) out of about 20 interviews I think I found one that did actual evaluation work on their search engine. The rest of them figured it was more important to have 300+ 'integrations' to various data sources and didn't think the relevance of the results was much of a selling point.

[_ea1k]

Quality is harder to sell to enterprise customers when compared to feature lists. You have to check the right boxes and entertain the right ears to sell.

Being more useful than the others isn't as easy to quantify.

[ankit219]

I can relate. I have had conversations about enterprise search and how it can help them especially when done with the help of embeddings + LLMs, but many do not see it as a problem. It's a classic case of people you would be selling to have hired analysts for the use case, and do not see it as a prominent problem anymore. Employees would like better search, but not as much that they would go to CTOs and vouch for it.

You can use analogies like:

1. Imagine the world before Google. Web search was a pain. <<Search for your company>> would be similarly transformative.

2. Every company has an encyclopedia - the guy who knows about the past efforts and is consulted whenever people are trying something new. Search makes that redundant and reduce times.

3. Same with repetitive work because the employees cannot find where the work was done previously.

search is a feature, and unless you address the central pain point that search solves (in terms of revenue), no one will go for it. When you do, you will end up solving the second problem about how leaders never have the issue but employees do.

[Grimblewald]

it may still not work, but try explaining using flashy analogies. For example, the internet without search algorithms is not the economic powerhouse we know it as today, and the quality of search made companies like google the giants they are. All this is because of the enormous economic impact good search has, say a user must make just 5 searches a day, but this turns into 20 because of poor search results, resulting in re-querying in an attempt to turn up the right result, multiply that wasted time by all employees and at face value you're costing yourself an enormous amount of money as a company, not to mention the compounding loss due to workflow interruption. With a graph or two you should be able to convince most of the fact good search = massive productivity gain.

[Tomte]

"we have no stemming support in Confluence" goes far beyond unfortunate defaults.

[marginalia_nu]

I didn't understand why Confluence's search engine works so poorly before I built my own search engine, and I especially don't understand why it works so poorly after. It's an absolute mystery and goes far beyond misconfiguration. Feels like they're just using a binary index and completely the skipping relevance ranking.

[sgift]

Which is the height of bullshit since Confluence uses Lucene internally, which obviously does support stemming (at least it didn't. Luckily, I haven't had to use Confluence for ages). Confluence search is what happens when some dev gets told "hey, add search, we need to mark a checkbox", searches for 30s for "Java search lib" and just adds Lucene without knowing anything about it.

[bambax]

JIRA gets a lot of bad press but it works ok. Confluence is an utter PoS with nothing going for it, nothing working the way it should or the way a random user would expect them to work.

How it survives (thrives) on the marketplace is a mystery.

[dumbfounder]

Good luck! I exited the search game because I felt it was a race to the bottom. Elastic was super successful, and has basically made search a commodity, but it's a shitty quality commodity. Developers just throw the data in and call it a day. Relevance is the hard part, and always has been, otherwise we would all still be using AltaVista and Inktomi. LLMs are changing the game though, and real innovation is now happening in search. I want back in.