SlideShop

SlideShop

AppSumo

Captivate your audience with show-stopping presentations

Share card

Actual performance

21reviews
Did not reach leaderboard

Traction signals

Rating3.7 / 5
Purchases2,276

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
85%85% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: presentations · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Xp
Xprim – To engage your audience during presentations34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Xprim – To engage your audience during presentations

Hacker News2
Slideasy
Slideasy37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Interactive surveys and presentations for your audience

Indie Hackers1$20/mosaas
Ko
Korl.co - Product presentations tailored to each audience in seconds36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Korl.co - Product presentations tailored to each audience in seconds

Hacker News9
Lo
Lobste.rs for an African audience23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lobste.rs for an African audience

Hacker News3
Pr
Presentations for your webcam, not a projector64%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Presentations for your webcam, not a projector

Hacker News246
Wa
Waymark – Roadmaps for product presentations55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Waymark – Roadmaps for product presentations

Hacker News47
A
A quicker way to author Impressive presentations48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A quicker way to author Impressive presentations

Hacker News2
CraftSlide
CraftSlide60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI presentations in about 2 minutes

Indie Hackerscommitment-side-project
St
Stopping Revenge Pornography Deepfakes46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Stopping Revenge Pornography Deepfakes

Hacker News1
St
Store Front and Audience23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Store Front and Audience

Hacker News1