Columns

Columns

AppSumo

Customers appreciate Columns for its ease of use, beautiful and functional charts, and the founder's responsiveness to feedback. Some users have noted minor drawbacks such as limited mapping functionality and a learning curve.

Customers appreciate Columns for its ease of use, beautiful and functional charts, and the founder's responsiveness to feedback. Some users have noted minor drawbacks such as limited mapping functionality and a learning curve. With an overall rating of 4.7 and positive feedback from 30 reviews, Columns is a solid buy, especially with its 60-day money-back guarantee.

Share card

Actual performance

30reviews
Did not reach leaderboard

Traction signals

Rating4.8 / 5
Purchases1,765

Launch Intel predictions

Analyze your own launch →
AppSumoStrong fit for a featured deal · Strong signals: reviews, overall rating, users · Missing: plus, platform, intuitive
87%87% predicted probability of success on AppSumo, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

BannerBoo
BannerBoo89%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

'Customers appreciate BannerBoo for its ease of use, extensive template library, and quick ad creation. Some users have noted minor drawbacks such as occasional glitches and limited text styling options.

AppSumo276
Innerbox
Innerbox44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Onboard your customers with ease.

Indie Hackers2b2c
Userdome
Userdome58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Acquire the first feedback with ease.

Indie Hackers1b2b
Nuxt Charts
Nuxt Charts53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Beautiful charts with Vue and Nuxt

Product Hunt+4
LegittMate AI
LegittMate AI52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

'Customers are raving about LegittMate AI, praising its ease of use, quick deployment, and effective AI agents. Some users have mentioned limited widget setup options and difficulty in customizing certain features.

AppSumo7
Ng
Ng-classy – Use Angular 1 and ES6 with ease38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ng-classy – Use Angular 1 and ES6 with ease

Hacker News23
Ma
Mapping Manhattan's vacant storefronts44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mapping Manhattan's vacant storefronts

Hacker News4
Pr
Projection Mapping with HTC Vive44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Projection Mapping with HTC Vive

Hacker News3
Ma
Mapping Tornadoes w/ D348%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mapping Tornadoes w/ D3

Hacker News6
Ma
Mapping the middle of nowhere with D3 and lasercutting46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mapping the middle of nowhere with D3 and lasercutting

Hacker News1