This blog posts delves into the mobility data and trip hop movement patterns for one
Mobile marketers analyze billions of anonymized and aggregated mobile location signals or geo-cookies each day to understand why people are where they are and what is on their minds.
The proliferation of machine intelligence has made it possible to crunch massive quantities of geo-cookies to uncover how mobile users behave in the real world, without accessing any personally identifiable information.
The VC Geo-Profile
Per CityLab and Martin Prosperity Institute, the San Francisco Bay Area including Silicon Valley is the largest cluster of venture capital firms and VCs. No surprise there! But what does a typical day look like for a VC in the San Francisco Bay Area? Where do they venture into the real world when they are not screening and funding startups? Where do they lunch and dine? Where do they hang out? What are their go-to legal firms? What cars do they drive?
Below infographic shows the aggregated behaviors of Bay Area VCs based on their anonymized and aggregated geo-cookies or mobile exhaust data.
In alphabetic order, below is the list of top behavioral segments that stood out for Bay Area VCs.
- Avid Sports Fan
- Visits Cafe Daily
- Eats Out Daily
- Entertainment Enthusiast
- Financial Service Customer
- Frequent Healthcare
- Frequent Luxury Hotels
- Occasional Luxury Retail
- Gym Enthusiast
- Live Music Lover
- Luxury Car Owner
- Museum Goer
- Wellness Enthusiast
- Wine Connoisseur
Conspicuous by their absence were grocery stores, convenience stores, laundry and dry cleaners. We expect these services are personalized and delivered directly to their homes or offices.
Data scientists correlate geo-cookies from mobile apps and programmatic ad exchanges to map-based information about local places, businesses, brands, active deals, discounts, local events, experiences, and even environmental conditions. This allows mobile marketers to look for thousands of behavior patterns, from shopping habits to fitness trends to dining preferences to commute routes.
It is relatively easy to infer places of work like Sand Hill or South Park, based on the characteristics of repeating location signals.
In a world gone digital, NPR has written about "the business of VCs that can't happen online". As VCs move from meeting to meeting, and as mobile exhaust data continues to grow, our machines will eventually understand their likes and preferences, and know if they do indeed prefer cars with doors that open "like this".
Russ Hanneman, the "Trés Commas" VC from the HBO comedy series "Silicon Valley"