Ranking Factor Content Freshness: The Importance of Up-to-Date Content for Visibility and Conversion
If you have the choice between fresh, delicious-smelling bread from your favorite bakery and the loaf from last week gone stale in the bread box--which one do you prefer? If your answer is option #1, you're like the majority of bread fans--and, by the way, also like Google, since you decide for the "fresh product." But what does this mean in the context of search engines, and what do you as content manager, SEO, or editor have to pay attention to?
What Does Google's Content Freshness Mean?
Since the Freshness update a few years ago, Google has changed its algorithm to list current search results before outdated ones. It doesn't matter whether the page was newly created or not but rather, how up-to-date it is. If content has been refreshed, it is likely to be up to date and therefore more relevant to the reader than older texts that may contain outdated information.
This Is How Important Content Freshness Is in E-Commerce
We did the test and searched Google for "What's the best 55 inch TV?". The search result:
The first 3 organic search results all date from 2023 and are therefore no more than 4 months old. Coincidence? Probably not. By favoring current content, Google helps users to find their way around and to locate the most helpful test report.
For online shops this means: An update of product content is enormously important to be classified by Google as a relevant provider. Whoever has been promoting the iPhone 5 or the 42-Inch Full HD TV in his product text as a high-end product for the past 3 years, not only confuses the reader, but also becomes increasingly irrelevant for Google over the course of time. This is also shown in the following graphic:
How Do I Manage to Update My Content Regularly?
Updating texts manually is not only annoying but also time consuming. When new products are constantly added, there is not enough time to keep updating stock descriptions and features. This is where automated content generation can help: You create a set of rules for a product division once and then generate texts for each product fully automatically--now and in the future. If technologies develop further, you adapt the set of rules at one point and then generate all text again afterwards with the updates you have made. This is feasible thanks to natural language generation (nlg).
The quality of the content is consistently high because you provide the input yourself. And thanks to various text variance features, you can ensure that no text sounds the same.