Most users struggle to see the full value of a product within the first 14 days (if ever).
That's why we built UserGuiding, a no-code user onboarding platform that helps increase adoption and reduce churn using interactive walkthroughs. Guide your users and display help articles they can read without ever leaving your app.
The best part? You can do it all without breaking the bank and with zero technical expertise, thanks to our drag-and-drop interface. Try UserGuiding today to get your user onboarding up and running in minutes, literally: https://userguiding.com/
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Based on our record, Taste should be more popular than UserGuiding. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I do some work with https://userguiding.com/ and I find them to be a good compromise between features and pricing. It's one of the more affordable user onboarding platforms out there but comes in packed with functionalities, and it looks nice, too. Source: over 2 years ago
Use user guides to onboard customers flawlessly (https://userguiding.com/). Source: about 3 years ago
Try taste.io, you cannot find users, but it will suggest you movies that people with similar tastes liked. Source: almost 2 years ago
On a social website (taste.io) I read a comment complaining about ‘bi- and homophobia sprinkled throughout [Elementary]’. The site doesn’t allow to react to comments so I couldn’t ask the person, but their comment got me thinking and I would like to hear people’s opinion: Do you think the show has some problematic moments in regards to lgbt+ representation and if yes, can you provide concrete examples? Source: over 2 years ago
It's John from taste.io, I think it depends on the method you want to use and where you're able to retrieve data to train the model. With a short amount of time and limited resources, you won't have the luxury of creating a collaborative filtering model....content-filtering is possible if you can also be resourceful with APIs + build crawlers. But, the results might be mediocre...meaning, the recommendations... Source: over 2 years ago
I have been asked to build a recommender system for TV shows at large scale, meaning thousands of users across the entire libraries of services like Netflix, Hulu and Amazon Prime. Something like taste.io but completely focussed on TV shows and not movies. My main concern is the complexity of this project, I have read up on recommender systems, and they seem fairly straightforward, its the scale that scares me. Source: over 2 years ago
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