🏰 A data moat is like a protective castle wall around a company. Done right, it can act as a competitive advantage that comes from having exclusive access to unique and/or valuable data.

Companies like Google and Amazon have built data moats. They know things others don't: user behavior, preferences, and trends. This knowledge helps them build better products and services. (Including selling access to some of that data.) 📊💡

Take Google Maps, for example. They've driven, walked, droned, and ballooned much of the earth. They create or combine data on traffic patterns, local businesses, and user reviews. No other mapping service can match its accuracy and usefulness. Many others have tried.🌍🗺️

N.B "droned" should be a verb with this meaning, if it doesn't already. YOU KNOW WHAT I MEAN.

Another clear data moat is Amazon. They track what you buy, what you browse, how you pay, where you send the products, and even how long you hover over a product. This data fuels personalized recommendations, making you stick around and buy more. 🛒📦

Facebook. Love it or hate it, Facebook's data moat is immense. They know your interests, connections, and habits. I watch cat memes & I cannot lie. 🐱 Advertisers pay big bucks to target specific audiences. Still. 📱👥

TikTok. Just...

Can't just throw any old data into a datastore & call it a moat, though. Privacy concerns, data quality, & security are real threats. 🐉 You've got to maintain against stale & protect against leaks.

Is your data that hard to duplicate? That valuable?🛡️🔍 Can you collect and organize data others can't? Can you customize to fit specific niches? Can you use proprietary map data, niche industry data, or specialized research? Can you do it in a privacy-protecting way?🌟

I "leave to the reader" very real concerns about WHAT data to collect, HOW to collect, & WHAT to do with it. Some believe "collecting any data at all is bad." I don't believe this. Of all the moats, though, data has potential to be creepiest. So: don't be creepy. I said it.