Taste VS Bimbala
Compare Taste VS Bimbala and see what are their differences
Create in-app experiences with the most straightforward product adoption platform — quick implementation, lasting
user engagement.
featured
Taste
Letterboxd
IMDb
And Chill
MovieLens
Simkl
Criticker
TasteDive
Bimbala
Canny
Upfeed.co
Featurebase
Frill
Nolt
CampTarget
Upvoty
Bimbala helps companies upgrade their support team letting them manage and collect product feedback more effectively. In his Bimbala board, the product owner will find all foundational feedback collecting interfaces combined in a single product. Each feedback item may be converted to a workable task and be tracked by the user base giving the transparency to the company.
BimbalaNo features have been listed yet.
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Bimbala's answer:
We are transparent.
Bimbala's answer:
We are versatile and not limited to software vendors only. What is more, our plans are affordable.
Bimbala's answer:
The software companies selling their own product.
Bimbala's answer:
That's an interesting question - we are two fellows that decided to start a side hustle when we were students.
Bimbala's answer:
PHP, Laravel, Redis, MariaDB.
Based on our record, Taste seems to be more popular. 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.
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: almost 3 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: almost 3 years ago
Letterboxd - Letterboxd is a social site for sharing your taste in film, now in public beta.
Canny - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.
IMDb - Internet Movie Database
Upfeed.co - Upfeed help companies get customer feedback & feature ideas. Get more customers. Get happier customers with feature-voting. Accelerate growth and build the product people want.
And Chill - andchill is a new way of enjoying movies and videos with your friends.
Featurebase - The all-in-one toolkit for managing your customer feedback.