Why marketing needs a data shift

Show Notes

• 02:17
  The rise of generative AI and data driven strategies

  The rise of generative AI technologies makes it crucial for marketing to shift towards more data-driven strategies. These technologies are data-based and have democratized complex technology, leading to rapid adoption and exciting opportunities for go-to-market efforts.
• 04:09
  Marketers and data challenges

  Marketers have long faced the challenge of handling a lot of data and making it actionable. But now, we approach it with more experience and flexibility, allowing us to test, optimize, and refine our strategies over time.
• 05:01
  ABM's impact on marketing

  ABM has not created more confusion; instead, it has opened up new opportunities. While ABM technologies focus on account-level data, the challenge is activating that data to create personalized and delightful customer experiences, a solution the market currently lacks.
• 06:49
  Creating a comprehensive view of the buyer journey with data

  The goal is to go beyond delivering the right message to the right person at the right time by understanding context. Marketers must combine first and third-party data to form a comprehensive picture of the buyer journey and to be more actionable with their data.
• 08:56
  Balancing first party data with third party data for actionable signals

  Marketers must learn how to augment first-party data with third-party data for meaningful signals specific to their buyer journey. Third-party data can help to shape your messaging and go-to-market strategy when its well-balanced with your proprietary data.
• 11:43
  Building flexible data foundations

  Instead of focusing on more data, it's crucial to construct foundations for a flexible data mindset. Our tech stacks must support adaptability and nimbleness, allowing marketers to scale efforts and optimize based on changing market dynamics.
• 13:57
  Stitching together data with a BI tool

  To combine data for a comprehensive picture, use a business intelligence tool. This standalone technology is crucial for looking across your data, mapping it intuitively, and creatively applying your data model.
• 15:02
  The starting point for effective data management

  The key to improving your data model is to focus on the fundamental questions and problems you aim to solve in your marketing efforts. Start by understanding the questions you need answers to, ensuring that your data and technology can provide meaningful solutions.
• 16:18
  AI and the future of data management

  AI technology is still in its early stages and will evolve rapidly soon. Consequently, the tools, processes, and approaches we use to manage our data now will likely change in pace with the evolution of AI technology.