Code Story episode
S6 E27: Escaping the Social Media Algorithm: Building a $100M+ Community SaaS with Gina Bianchini of Mighty Networks
Jul 19, 2022 · Season 6 · Episode 27 · 31 min
The platform to build your thriving community
Gina Bianchini grew up in Cupertino in the 70's & 80's, which was a place where people were tinkerers and creators. What she learned from that experience was a deep appreciation for the interests and passions of people. When the early days of social tech happened, she fell in love with how they worked - specially around creating communities. Outside of tech, she played field hockey at Stanford and a solid career. Fun fact, you can't cross check in field hockey, which was news to me. Now a days, she loves to hike, read, and hangout with her friends, family and her husband.
Gina has created community tools before, and has discovered that people who are creating and participating in these online communities are phenomenal. So much so, that she set out to do it again, in order to unlock the power of community in people's lives.
This is the creation story of Mighty Networks.
Sponsors
ImmediateOrbitPostmarkStytchVerb DataWebapp.ioLinks
Website: https://www.mightynetworks.com/LinkedIn: https://www.linkedin.com/in/ginabianchini/
Checkout our episode stacks on Stacklist! https://stacks.codestory.co/
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
More episodes
Keep listening
Topics
Explore related conversations
Fractional CTO vs full-time CTO: which does your startup need?
A practical comparison of a fractional CTO and a full-time CTO: cost, scope, when each makes sense, and the questions to ask before you hire either one.
Scaling an engineering team from 5 to 50
How to scale a startup engineering team from 5 to 50 people: when to add managers, how communication breaks, what process to add at each size, and what to leave alone.
Engineering metrics that matter (and the ones that don't)
Which engineering metrics to track at a startup: DORA metrics, quality and reliability signals, what they tell you, and why measuring individual output backfires.