Rare Carat turned One (month old)!
We have been heads down just trying to keep up, thus the lack of blog posts. In our first month, we’ve seen:
- 200k page views
- 120k searches
- 45k users (5:10 min avg session)
- 2k conversations (our favorite part)
The love we have gotten from you all has just been awesome. But you’ve also given us countless ideas for fixes and features from which we’ve already implemented more than 100, small and large (advanced search filters, multi-shape search, AGS ideal search, performance speed doubled, tablet view pullout, bugs with vendor results, search button freeze, Safari issues, and others).
Rare Carat Updates
- Our mobile site is (finally) live!
- We’ve added four new members to the team, spanning SEO, SEM, Content, and Engineering.
- Digital.NYC named us the start up to watch for November 2016
- We’ve gone live with our API, and are on-boarding our vendors for faster search results
- 30+ vendors have reached out to ask to join the platform. We’re screening them now.
So much cool stuff coming on the product roadmap. Message us (bottom right) on your thoughts and we’ll prioritize accordingly:
- Logins: so you can save your searches, alerts, and pinned stones
- Images: allowing users to search only stones for which there are images, and showing them in results
- Watson artificial intelligence conversation bot: we’ve been up at IBM in Somers, NY with the Avijit, Dan, and John at the Competitive Projects Office. Things are looking freaking cool – it will intelligently talk a total beginner through the process, matching him/her with the best stone and the best retailer using some cool data science.
- Everledger partnership: met with Leanne and her team last week in New York, and they are doing incredible stuff that we’re excited to bring to our users. These efforts revolve around adding a trust layer to transactions with their work at MasterCard, and being able to see a stones journey from mine to ring in the blockchain. Planning for Q1 2017.
- Watson vision: we’re exploring how to read certification PDFs by machine to understand the placement and type of inclusions make our models more accurate.
Keep the feedback coming, we're listening. Our dev list is 100% driven by you all.
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