Process
Step-by-step actions
About halfway through our project, we found ourselves in a situation where we had to go through significant Google algorithm updates. Among them was the Helpful Content Update, which caused a dramatic drop in the ranking of many websites. Our client's website survived the introduction of HCU and continued to rise despite the constant fluctuations in the algorithms!
The third month of work resulted in 40 additional articles and 6 high-quality links. At this time, we began to lean towards programmatic SEO and artificial intelligence-based content created on a large scale. With this approach, we created an impressive 1,200 pages in the 4th month alone. Each one was optimized for SEO.
1
SEO audit and implementation of changes
We started with an extensive SEO audit. We detected problems with the site's structure, ineffective internal linking, too many plugins, data structure issues and much more. In the next step, our team implemented the necessary changes.
2
Content and outreach strategy
We researched the sustainability niche and formulated a comprehensive strategy, taking into account potential traffic sources, monetization options and content gaps. Our goal was to create a strong link profile that matched this niche. At the same time, we began using artificial intelligence to create a large amount of content to build topical authority.
3
Programmatic SEO and Content Gap.
Along with a standard content and outreach strategy, we decided to implement programmatic SEO. With the help of artificial intelligence, we were able to develop and publish nearly 1,500 new URLs, in addition to regular high-quality articles. This set a new pace for our content cluster, while helping us fill any content gaps and build authority in our client's niche.
4
Link Building
We started our link-building efforts with 10 links from highly ranked sites in the sustainability niche, such as Earth.Org.
5
Content based on artificial intelligence
We developed a content plan to build a new section to fill the content gap. The goal was to prepare a dataset of more than 1,200 brands (including reviews, photos and videos!) and turn it into a comprehensive review database using sophisticated AI tools. We optimized the existing content catalog and enhanced it with the first batch of 40 human-written articles to fill in the word gaps.