Technology Intelligence Data-driven decision-making — Elizabeth Cholawsky // HG Insights

Show Notes

• 02:27
  The definition and evolution of technographic data

  Technographic data is narrowly defined as the technology installations at a company. Over time, the view of technology intelligence has expanded to include contracts, IT spend information, near real-time signal data from the internet, historical data, and technographics.
• 04:06
  Applications of technology intelligence

  Applications of technology intelligence include corporate development, strategy, campaign execution, and competitive takeouts. Product management and other teams have also embraced technology intelligence for problem-solving and decision-making.
• 05:06
  Leveraging IT spend information for strategic decision making

  Large corporations can utilize an IT spend report for market planning and budget allocation in the upcoming year. Additionally, that report can be leveraged to make strategic decisions for companies in terms of identifying growth and opportunities within market segments.
• 07:52
  Leveraging HG Insights granular data for strategic decision making

  HG Insights' big data set enables regional and global technology landscape analysis and the comparison of cloud vendor market share and trends. Furthermore, the granularity of the intelligence is useful for large companies making major decisions like funding growth in a region.
• 09:28
  How marketers are using technology intelligence

  Marketers are using technology intelligence primarily for competitive campaigns. Competitive campaigns enable marketers to identify trends, target companies with a higher likelihood of switching from their current technology, and find whitespace opportunities in other companies.
• 10:19
  Contextualizing intent data with technology intelligence for effective marketing

  HG Insights intent data is sourced from bitstream data, making it a long-term viable intent signal. By overlaying this intent data with their technology intelligence, they can differentiate between buying signals, enabling marketers to focus on genuine buying opportunities.