Data Science for Marketing

Read more about our in-house primary research, applying methods from data science for marketing and content experiences.

  • When Creating More Content Isn’t the Answer2:23

    When Creating More Content Isn’t the Answer

    In the first of this three-part series, data scientist Sinan Ozel explains why creating more content isn't the only way to increase views.

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  • Find out how to 7x your conversion rate in The Content Experience Report

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  • Content Tagging and Integrations: Layering on Knowledge for Human Interests

    Content Tagging and Integrations: Layering on Knowledge for Human Interests

    In this blog article, we investigate content management for audiences with data science to see why content tagging and integrations matter.

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  • When Frequent Content Generation Gets You Less: Lessons from Data Science

    When Frequent Content Generation Gets You Less: Lessons from Data Science

    This blog uses data science to show marketers that doubling their rate of content generation would result in only a small increase in views.

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  • The Marketing Blog and Readability: An Overlooked Aspect of the Content Experience

    The Marketing Blog and Readability: An Overlooked Aspect of the Content Experience

    Using data science, this blog shows how writing for the 6th and 7th grade reading levels is correlated with an increase in views on a marketing blog.

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  • Own the Journey: A Field Guide for Becoming a Marketing Explorer

    Own the Journey: A Field Guide for Becoming a Marketing Explorer

    Own the Journey: A Field Guide for Becoming a Marketing Explorer features tips and best practices for marketers to advance along their content marketing journey and focus on content experiences.

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  • Who Should Own the Content Experience in Your Organization?

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  • Shark Attacks, Ice Cream, and the Marketing Analytics Revolution

    Shark Attacks, Ice Cream, and the Marketing Analytics Revolution

    In this blog post, Uberflip's resident data scientist, Sinan Ozel, explores the econometric concepts of correlation, causation, and their influence on marketing analytics.

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