Data Application Creates Value

Anand Sanwal shares insights about building valuable data businesses, emphasizing that data's worth comes from its application rather than mere possession. Through his experience building CB Insights from selling PDFs to a nine-figure company, he demonstrates how even limited data can provide significant value when properly positioned and marketed.

Key Points:

• Data Value Fundamentals:

  • Raw data itself has no intrinsic value
  • Value comes from what you can do with the data
  • Small amounts of data can be valuable if it provides meaningful insights

• Three Critical Elements for Data Businesses ("ECO"):

  • Edge: Define what competitive advantage the data provides
  • Collection: Ensure sustainable way to gather data
  • Opportunity: Target markets with significant potential (financial services, AI companies, sales/marketing)

• Common Mistakes in Data Businesses:

  • People wrongly assume having data alone creates value
  • Running "100 miles an hour in the wrong direction" by not focusing on customer outcomes
  • Relying on single data sources or "hacks" that can disappear

• Successful Data Business Characteristics:

  • Target high-value segments where "some information is better than no information"
  • Focus on narrow markets initially
  • Build multiple data collection methods over time
  • Start with "data janitor work" and evolve to more sophisticated methods

• Pricing Strategy Insights:

  • Don't undervalue data products (Their PDF reports went from proposed $25-100 to $12,000-100,000)
  • Create tiered pricing structures
  • Use premium tiers as price anchors even if they rarely sell

• Building Trust:

  • Industry relationships and trust are crucial for data collection
  • Proper data anonymization and aggregation build credibility
  • Target industries where decisions involve large dollar amounts