Topmarq – Online Peer to Peer Vehicle Marketplace

Hacker News

Hey HN, I’ve been flip flopping on whether to post this here as I know there have been some arguments about whether HN is too broad an audience, but ultimately decided it would be interesting to see what comes of it from the tech focused side. I wanted to get some thoughts on my new (first for me) online marketplace. Topmarq (https://www.topmarq.com) is a peer-to-peer luxury vehicle marketplace striving to make the buying/selling process hassle free for even the most vehicle-ignorant users. We work with sellers to get pictures, videos and a mechanic inspection, and then present it online in a way that gives buyers full transparency. We shift the model from the current listings which are really just teasers to get you to see in person, to listings that provide every little detail of the car you would be buying. You can see some of our early listings up here (https://www.topmarq.com/listings/). The entire transaction can then occur online via escrow which keeps both parties protected. By building a marketplace that buyers can trust, we aim to remove the dealer from the equation and give those savings back to the buyers and sellers. We take a set fee from the transaction but are upfront about it. I think the trend on pricing is to move away from confusing fees and extras and just charge what your service costs and be done with it. At this point I’d expect most people who watch TV to have at least heard of Carvana or Vroom and how they sell vehicles purely online. While it may seem that this is becoming the norm, there’s still only a very small percentage of cars (<10%) sold online in the US each year. With the pandemic shutting everything down you would think that the number would skyrocket yet it hasn't. One of the main drivers are the dealers as their sales reps want people in the building to upsell (that’s how they make money). Btw also looking for some additional tech talent should anyone else be a SWE with a passion for cars.

Visit product View on Hacker NewsMar 3, 2021

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

85%85% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

57%57% 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: video, users, way · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos

22%22% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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