Apps Run on Data: Winter MyLibrarian Build In Public Blog

As CEO of MyLibrarian, I’ve decided to revive the practice of blogging about our company’s products. This blog is going to be pretty nuts and bolts, no frills, no romance copy. We may include it in our update to investors, but really it’s for aspiring product builders and for our team to track and celebrate progress. It’s for me, to keep all moving parts working together, as sometimes the best way to keep everything clear in the mind is to write it out.

Here’s our Winter Update:

Our main product, the MyLibrarian Book Discovery app, is going into the last stage of development for v4. We’ve taken the best parts of what we’ve built so far—an elegant front end build in React Native, an update of the Flutter backend that runs the Android demo, the Librarian Brain data set and the recommender algorithms we’ve implemented via Python, and now have a private beta that’s on TestFlight with 4000+ users. My team and I have developed all our products, which are now patent-pending.

If you are a book lover, this product is for you. Users can request book recommendations from MyLibrarian, and the app provides top picks, just for them. We have a user testing system in place, with prompts for feedback and where to submit feedback, ask questions and report bugs and other improvements. We love our book lovers, and readers seem to love the MyLibrarian app, based on the testimonials pouring in.

The MyLibrarian Book Club is now curating the Book Club (by MyLibrarian) for Joy of Mom, a community of 2.7M+, as well as expanding our growing MyLibrarian Book Club on Mighty Networks. Our first book pick for Joy of Mom is a huge hit, and reader discussion on the platforms is growing.

Next, we’re looking for a partner with whom we can build a better book discovery system in conjunction with. The rest of the this update is for more technical people who already know that Apps Run on Data.

We will integrate our API within a bookseller’s backend code. On the front end, in the sales experience interface, users will see recommendations from Librarians listed. Instead of “You might also like,” suggestions will already be curated by the Librarian Brain, and will read “Here’s Books Librarians Love.” When the user is logged in, more personalized selections will be available based on user tastes they opt in to give. And none of that creepy tracking based on what someone else at your address has ordered. Some online booksellers are in dire need of updating their recommendation systems, not only for usefulness, but to be more ethically-minded, too. Enter the Librarian Brain. We’ll be able to increases sales for online booksellers, if they’re willing to evolve.

Stay tuned for our Spring update, when we’ll be well into scaling our private beta through our book club, author and librarian communities.

Thank you for reading,
Michelle Z.