The 6 Obstacles to Using Data Science

It would be great if we all had data to drive our decisions and processes — and used it. But the obstacles are so daunting that most of us can’t. Here are the top 6:

  1. Leadership from the top is mostly lacking.
  2. Data quality issues are omnipresent.
  3. Data science in marketing is not established (it may exist for production operations).
  4. Marketing lacks the technology platform for effective lead generation. Among the best prepared, the technology platform is full of holes.
  5. Operational tasks and organizational responsibilities are not identified and assigned.
  6. Skills for developing and executing methods to create data, analyze it, and communicate findings are very scarce.

Published by Sue Aldrich

As a leading authority on worldwide customer requirements, practices, technologies, and governance for personalization, Sue researches the technologies and practices that help marketers get the most useful content in front of customers at the right moment: recommendations, search, discovery, targeted marketing, and web content management. Aldrich is an expert on optimizing the methods that help customers find what they need to make buying decisions and/or to solve problems. She helps clients develop personalization, marketing, discovery, and content management practices that will engage customers and improve results.

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