{"id":15002,"date":"2022-07-29T12:49:33","date_gmt":"2022-07-29T12:49:33","guid":{"rendered":"https:\/\/www.searchenginejournal.com\/content-marketing-metrics-insights\/458929\/"},"modified":"2022-07-29T12:49:33","modified_gmt":"2022-07-29T12:49:33","slug":"content-marketing-metrics-analytics-5-types-of-data-insights","status":"publish","type":"post","link":"https:\/\/marketingnewsbox.com\/?p=15002","title":{"rendered":"Content Marketing Metrics & Analytics: 5 Types Of Data Insights"},"content":{"rendered":"
<\/div>\n

Content marketers are increasingly tasked with making sense of large and unwieldy data sets.<\/p>\n

However, they often lack the skills to process this data, creating a paradoxical relationship between executive decision-making and on-the-ground implementation.<\/p>\n

On the one hand, 94%<\/a> of businesses feel that data is essential to their growth.<\/p>\n

Yet, at the same time, 63%<\/a> of employees say they struggle to process data in a workable timeframe.<\/p>\n

As digital publishing moves towards a data-driven model, deep analysis is required for companies that want to remain competitive.<\/p>\n

Content marketers must adapt their skillsets and build advanced, privacy-focused tech stacks that can handle first-party data.<\/p>\n

This, in turn, enables them to create highly relevant, credible, and engaging content that meets Google\u2019s EAT (Expertise, Authoritativeness, Trustworthiness) criteria<\/a> and ranks well in search engines.<\/p>\n