Manual Data Creates Value

Anand Sanwal shares insights about the value of private data collection and cleaning, drawing from his experience building CB Insights to nearly $100M in revenue. He emphasizes that successful data businesses are built on manual work and pain tolerance rather than sophisticated technology.

Key Points:

• Data Collection Philosophy:

  • Success comes from willingness to do "nasty work" in Excel spreadsheets
  • Valley companies often try to "splash machine learning on it" instead of doing manual work
  • 99% of people won't do the manual data collection work, creating barrier to entry

• Framework for Successful Data Businesses:

  • High Consideration: Customers have significant risk or money involved
  • Highly Opaque: Information is hard to find or access
  • Variable SKU: Product can't be easily compared in a simple table

• Value of Private Data:

  • GPT and AI make private data more valuable
  • Previously companies would share data for backlinks/Google traffic
  • Having access to private data becoming increasingly important

• Data Collection Strategy:

  • Use mechanical turk or hire people to make calls/collect data
  • Build data assets through manual work others won't do
  • Focus on data that requires regular refresh to maintain subscription value

• Business Model Advantages:

  • "Build once, sell multiple times" model
  • Unsexy nature keeps smart competitors away
  • High margins possible once data asset is built

• Practical Example:

  • Could hire someone to go door-to-door collecting pool pricing data
  • Sell data to both consumers and pool companies
  • Start niche (like one geographic area) and expand from there