While I agree that building a great and relevant search experience with a Lucene-based engine requires lots of extra time and effort to get right, there are other non-TFIDF based solutions that provide a much faster path to great relevance with far less effort (https://blog.algolia.com/inside-the-algolia-engine-part-1-in...), and it's possible to have semantic ranking without too much machine learning (https://blog.algolia.com/promote-search-results-query-rules/). Not to discount the value of machine learning - we're finding that for specific usecases ML can be a very valuable way to help surface more pertinent content for individuals based on their profile/preferences etc. (https://blog.algolia.com/personalization-announcement/).
This may be along the lines of what you mentioned around "commoditizing" complex traditional search workflows. I'd be curious to hear more about what kind of use-cases you think are trickiest without SS.
Got it. Would you send me an email at [email protected]? I'd love to show you how you could implement a non-modal flow with Onboarded in ~5 minutes. Would love your feedback.
We don't think developers should have to reinvent the wheel, or cobble things together to build a customized experience. You're usually not writing 50 lines of javascript one time only and calling it a day - you are changing your flow all the time, as soon as you see evidence for how to make it better. Onboarded is a tool that will make that process of learning and iteration much more efficient (and thus faster and cheaper). And there's no reason you couldn't integrate with Segment too.
The thing is, we're just focused on the free tier right now. When you've onboarded lots of people and decide you like the product, pricing is an open conversation.
The key point about Onboarded is that it's made for developers. It makes it simpler and faster to completely customize the user experience that you want, integrated as you see fit with your app's existing functionality and look/feel.
One of the goals we had when we designed Onboarded was for it to be unobtrusive yet flexible. It can be used to accomplish just what you are saying. The styling as overlay/modal is just a default to get you going. It can be made into a fullscreen flow or inline, or however you want. Onboarded makes it easier to do all those things stylistically, as well as bind event handlers, post data, etc.
We built Onboarded to provide user onboarding as a service to developers and startups. Our goal is to make it much easier and faster to build, measure, and change user onboarding flows in your app.
If you have questions or comments about the product, or are interested in user onboarding, I'll be here to chat or email us at [email protected]; all feedback is greatly appreciated!!
While I agree that building a great and relevant search experience with a Lucene-based engine requires lots of extra time and effort to get right, there are other non-TFIDF based solutions that provide a much faster path to great relevance with far less effort (https://blog.algolia.com/inside-the-algolia-engine-part-1-in...), and it's possible to have semantic ranking without too much machine learning (https://blog.algolia.com/promote-search-results-query-rules/). Not to discount the value of machine learning - we're finding that for specific usecases ML can be a very valuable way to help surface more pertinent content for individuals based on their profile/preferences etc. (https://blog.algolia.com/personalization-announcement/).
This may be along the lines of what you mentioned around "commoditizing" complex traditional search workflows. I'd be curious to hear more about what kind of use-cases you think are trickiest without SS.