This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
What Next
Recommends TV shows based on aspects of your last watch
Tell us the show you just finished. We'll figure out what you'll miss about it. We also provide IMDb ratings, the platforms the shows are on, and a viewer profile.
I was inspired to build this because a big problem my family and I have had has been figuring out what shows to watch. I figured that if we could find a show similar to other shows we all enjoyed together, then the process of finding a new show would be a lot easier.
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About What Next on Product Hunt
“Recommends TV shows based on aspects of your last watch”
What Next was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #18 on the daily leaderboard. Tell us the show you just finished. We'll figure out what you'll miss about it. We also provide IMDb ratings, the platforms the shows are on, and a viewer profile.
What Next was featured in TV (5.6k followers), Streaming Services (42.9k followers) and Entertainment (2k followers) on Product Hunt. Together, these topics include over 10.8k products, making this a competitive space to launch in.
Who hunted What Next?
What Next was hunted by Vikram Iyer. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how What Next stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Vikram Iyer