Applied Analytics with Business Processes + Big Data + Information Rights

Georgian Partners has codified an interesting set of ideas around applied analytics as part of their core investing thesis. Generally, the idea is that B2B tech companies that provide a core business process (e.g. CRM, help desk, etc.), with the permission of their users to anonymize the data (information rights), can apply big data analysis to come up with meaningful insights to help customers get more value than they otherwise would from a basic tool. Meaning, the more customers that use a given application, the more valuable the app is to those customers because it can provide insights from across the customer base to any given customer.

Here are the 11 principles from the applied analytics theory:

  1. Understand the entire process
  2. Identify and prioritize the most valuable insights
  3. Create a dataset that is unique and broad
  4. Raw data is of little or no value
  5. Insights are more valuable the closer they are to being actionable
  6. Leverage the shortage of data scientists to your advantage
  7. Separate analytical insight from how it’s consumed
  8. Inject insights into business processes at the moments of highest impact
  9. It’s not about ‘owning’ the data
  10. Governance and compliance is a foundational discipline
  11. Lead by example

As a simple example, imagine an email marketing company with 50,000 customers. Using the dataset, the application can proactively notify users when they use words that are likely to trigger spam filters or provide a visual analysis of email open and delivery rates compared to similar customers. By proactively helping customers be more effective in an automated fashion, the company is actually creating a moat around the business that new upstarts will have a hard time duplicating (you can’t duplicate it unless you have a critical mass of customers, and it’s incredibly difficult to achieve that scale).

For entrepreneurs in B2B tech, they’d do well to read the applied analytics theory.

What else? What are some more thoughts on applied analytics with business processes, big data, and information rights?

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