Case Study: How Just One Cookbook reclaimed its top-ranking position and increased pageviews 

Featured creator

Namiko Hirasawa Chen,

Just One Cookbook

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Challenge

Nami historically approached content creation by using Google to research, then choosing keywords based on what seemed likely to do best. Her method was working —until the pandemic hit.

Competition for her target keywords increased drastically, causing her posts to lose ranking on search results pages. 

Nami’s goal was to reclaim her top-ranking position by adopting a consistent, data-backed SEO process that addressed reader search behavior and Google’s search engine without compromising the authentic recipes and cultural context her readers loved.

Approach

As a Raptive creator, Nami has access to Raptive’s AI-powered Content Optimization solution. Creators use it to generate data-informed briefs with suggestions for optimizing new and existing posts based on a target keyword. The briefs have two sections: Content Research and Content Grader.

Section 1: Content Research

Content Research instantly pulls all of the relevant data together in one place. Nami didn’t have to dig into Google to do research for each post because it was already in the Research tab.

Content Research Feature	Feature Description
Competitive Analysis	List of top-ranking posts from Google for the target keyword, with additional metrics like Domain Authority and content grade.
Questions to Answer	Commonly searched questions on the topic from People Also Ask, Google Suggest, and Quora.
Topics to Cover	The subtopics your readers expect to learn more about are sorted by frequency.
Outline Generator	GPT-3 suggests titles, descriptions, and outlines based on data, and creators can build an outline to pass off to writers.

For example, the Content Research section showed Nami that people searching for miso soup recipes often wanted to know if the soup was vegetarian. Nami incorporated details like this into her content, making her posts easier to find in search results and giving her a competitive edge.

Section 2: Content Grader

The Content Grader uses AI to identify patterns across top-ranking content for similar topics to help creators understand what readers want. It then lists related keywords in order of popularity and issues a grade based on how comprehensively your post covers the main topic. The Grader uses GPT-3 to group semantically related topics and questions, making it easier to see how to improve your content to match search intent.

Outcome

Once Nami updated her existing posts, she used built-in performance insights to measure the impact—pageviews on optimized posts increased by an average of 15%.

Based on these results, Nami made Content Optimization a standard part of her SEO process for updating existing content and planning new content. Her writers use the briefs to get a stronger sense of what people want to see, which enables them to prioritize what content they should create. 

“Ever since we started using Content Optimization, we’ve seen a steady climb. We’re checking the traffic every day and it’s going up, especially posts that went down. It’s pretty simple and straightforward.” 

Namiko Hirasawa Chen