ArtRoomMockups – Easily Convince and Captivate Your Audience

Hacker News

ArtRoomMockups is a collection of 150+ captivating rooms in a PSD file that lets you place your artwork and photography into realistic settings quickly and easily. No subscriptions; buy once and use it forever. Key Features: - One-Time Purchase: No monthly fees. - 150+ Rooms: Living rooms, dining rooms, bedrooms, and many more. - Fully Customizable: Includes editable frames and smart objects in Photoshop. - In Their Words: “Exactly what I needed—saved me tons of hours for my new photography webshop!” It's certainly not perfect yet, so I'd love any feedback from the HN community! Cheers, Christian

Visit product View on Hacker NewsFeb 17, 2025

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2points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, 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: new · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, 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

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, monthly · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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