Introduction
Welcome to the 12 Days of Data, our look back at the data that made marketing in 2019. We’re looking at the year that was from an analytics perspective to see what insights we can take into the next year and decade. Sit up, get your coffee ready, and let’s celebrate some data.
Content Republishing Statistics for 2019
On Day 10, we examine the phenomenon of content republishing, the act of taking an existing piece of content, potentially making changes to it of some kind, and then publishing it again on a new date. This practice has become far more commonplace in the last few years as publications of all kinds have focused on enhancing SEO strength (continually reposting their best content for new inbound links) as well as journalistic publications facing staffing shortages simply republishing to fill a content queue. But does content republishing work?
Let’s first look at the big numbers. Out of 107 million English-language pages published in 2019…
- 4.97 million or 4.64% of pages have been republished
- Of those republished, 3.56 million (71%) of the republished pages were originally published earlier in 2019, intra-year
- Republished pages garner a median of 1,378 readers, a decrease of 148 readers from original content
- Republished pages garner a median of 104 social shares, a decrease of 140 shares from original content
- Republished pages are a median of 108 words longer than original pages
- Republished page domains have a median domain authority of 83, 6 positions lower than original page domains
In short, republished content performs less well than original, new content. Much of the republishing occurs in the last 30 days as well:
We see that the content treadmill is most active within the last 30 days.
Key Takeaways
Republishing content is a useful technique to refresh and update old content, but new, original content performs better. With this insight, it’s important to weigh the considerations about a republished page versus a new page. If you don’t have the resources to consistently crank out new, high-quality content, republished content is better than poor quality or no content, but it’s less than optimum.
This is also a marketing opportunity for those who excel at creating original content. If you identify a publication in your industry or niche which is relying heavily on republished content just to keep the lights on, you may be able to submit new, original content for publication that is better than what they’re recycling and have a very low bar of entry for your content. That in turn can be used as leverage to publish content on ever-increasing quality publications, as you develop a reputation for being a source of high-quality, original material.
Methodology
Trust Insights used the AHREFS crawling engine to examine 107 million English-language pages published in 2019, then subsetted them to 4.97 million pages republished in 2019 with at least one republication date. For republished pages, we sampled 118,796 unique republished pages from the 2019 index. The criteria for selection was the top 10,000 articles per month by organic traffic. The dataset was merged, then de-duplicated by article URL. Articles were limited to the English language. The measure of centrality used for this study was the median. The period of the study is January 1, 2019 – December 17, 2019. The date of data extraction is December 19, 2019. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors.
[12days]
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.
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