We have $1.3m in commitments and we’re now in the midst of negotiating the last pieces of the round. With the round closing & cash in the bank, we’ll again be able to put all of our focus in growing the business and squashing the problems that are currently bottle-necking our growth. While there are a few solvable issues holding us back from growth, the largest bottle neck is around contractor quality & consistency. Below you’ll see steps we’re taking to automate & streamline our process.
// Key Performance Indicators //
// Learnings //
Somewhat obvious but people who are pursuing photography as a hobby or passion perform significantly better during remote training and cause the company less issues at listings (forgetting rooms, camera setting errors, etc). We do have quite a few people who do not do photography as a hobby or profession so in those cases the key is finding those who care about doing a great job.
We’ve implemented group training to speed up the process of getting photographers in the field. This looks like 4-5 contractors showing up in person and being trained all at once.
Since we’ve revamped our job descriptions and modified the application process, we’re getting a great amount of applications for UI/UX Researchers. We now need to either continue to modify the application process/description of the Engineering roles or recruit in a different way to get the talent we need.
We’ve been iterating on the Android versions of our photographer mobile app. We’re still in the iteration phases but moving forward photographers will be able to perform all of their work on their phone & potentially a 360 device. That being said, we’ve been working through multiple issues getting approved by the Apple App Store to launch our app into the Apple ecosystem.
Over the last several weeks, through discussions with our new investors for the seed round, Birchmere Labs & Zero G Capital, we’re aiming to test out additional services through our ordering process that include cleaning & staging. This should not only make it easier for our customers to have all the services performed that they need, but also add network effects and defensibility as we grow.
// Product Progress //
In the images below, you’ll see the first version of our machine learning algorithm automatically pick the best photos and correct for crookedness. These algorithms are working off of our existing data set of 200,000 photos and will continue to get better as we collect more data over time. Implementing these machine learning algorithms into our process will enable us to deliver photos to the customer in a matter of minutes instead of days as well as increase our margins by 12%.
// Shoutouts & Thank You’s //
James Garvey from SelfLender, Julien Denaes from Alpin.io, Matt Talbot from GoSpotCheck for several investor introductions!
Eric Marcoullier, John Funk, and Natty Zola for the help with navigating fundraising negotiations.