What is the Frase Topic Score and how does it work?
The Frase Topic Score is a key component of Frase's Content Optimization workflow. This article explains how Frase recommends topics, and scores your content against competitors.
How does Frase determine the topics for a search query?
Frase recommends topics by analyzing the top Google results for your keyword, and performing NLP analysis over them.
In a nutshell, Frase extracts content from each URL, and then leverages proprietary Named Entity Recognition to extract topics.
More specifically, this is how Frase goes from search query to list of topics:
|1||Search Google||input search query|
|2||Analyze SERP||process top 20 Google Search results and extract key topics per page|
|3||Aggregate Topics||aggregate topics as one list across all results, and collect topic frequencies|
|4||Cluster Topics||automatically group topics into semantic clusters, while removing low quality outliers|
|5||Rank Topics||various ranking factors are considered, including term frequency, cluster relevance, among others|
|6||Score Pages||score all pages with an algorithm that measures topic coverage|
The resulting list of topics is displayed on the right panel in the "Optimize" on Frase's right-side panel in a document:
These topics can be previewed in 3 core ways:
- Top Topics: list of topics sorted by relevance.
- Topic Clusters: list of clusters, where each cluster has a set of topics.
- Long Tail Topics: list of topics two words or more
Frase Topic Scoring works in 8 languages (English, Spanish, French, German, Italian, Danish, Dutch and Portugese).
How does the topic scoring algorithm work?
Once we have the list of topics for your search query, Frase scores all pages with an algorithm that measures topic coverage .
The result is an Average Score, a Target Score, and the User Score.
The User Score is displayed as a percentage value on the left side:
How to increase topic score
Your score will increase in 2 scenarios:
- In progress (orange): mention the topic at least once, but below the suggested frequency
- Completed (green): mention the topic at the suggested frequency
For example, in the example below, we got a point for "social media marketing" because it got mentioned at least once, but we will need another mention for it to change to green, allowing us to get another point.
Keyword density penalty
High density occurs when a topic represents over 2% of your content. This usually means your content is too short, and you will need to increase your word count.
Your Topic Score will decrease for every topic with high density.
Topic Clusters with Scores
Topic Scores are also available at the cluster level. The cluster score is simply an aggregate of the topics inside.
Using SERP Scores/Topic Heatmap
You can also view all the topic scores across individual sources in "SERP Scores", and also topics each individual competitor is using via Frase's Topic Heatmap. Click the "SERP Scores" option in the topic dropdown to see that view (as shown below)
Then, click "Topic Heatmap."
Once opened, you'll be able to easily visualize all the topics and keywords that each of your top competitors are using. This is a critical tool for identifying keyword gaps in your competitors' content.
This visualization shows you each topic as well as the number of times that each competitor is mentioning that topic. Topics that are shaded yellow or grey indicate that the corresponding competitor is mentioning that specific topic too sparingly.
In the below example, the topics "social media marketing" and "digital channel" appear to be keyword gaps. You can paste topics directly into your document by clicking the button in the screenshot below (red arrow), and reopening the Heatmap will update it. You can flip between "Long Tail Topics" and "Top Topics with the map (circled in red below)