Frequently Asked Questions For Surfer NLP

Since the BERT Google update in October 2019, Google has looked to incorporate NLP (natural language processing) into their search algorithm to deliver more accurate search results for users.

Once that happened we have worked to harness Google’s NLP API to provide a tool that allows our clients to optimize their content according to how Google is analyzing content.

The following questions are the most frequently asked questions we get asked about NLP. If you have a question that is not covered here, please contact us, our client success team will be happy to help.

  1. What is NLP

  2. How Surfer uses NLP

  3. True Density vs. True Density + NLP

  4. Which Languages Are Supported in NLP?

  5. How To Check Sentiment in SERP Analyzer?

  6. NLP in Content Editor

  7. Pricing and Plans for NLP Analysis

What is NLP?

NLP stands for Natural Language Processing. During the BERT algorithm update Google increased their understanding of content by creating new metrics to analyze the content on the page, through machine learning.

BERT analyzes the context, entities and sentiment of the page. Which means that Google is much more accurate at understanding content context, user intent and the sentiment of the content.

Read an in-depth article that walks you through all the specifics to NLP to find out more.

How Surfer uses NLP?

  1. Google has a NLP tool that analyzes content

  2. We are using it to extract the data about entities and sentiment

  3. Then we cross that data with Surfer’s True Density calculation

  4. We follow a similar process with IBM Watson to measure sentiment of the overall page content.

If you’re interested in finding out more about our decision to use IBM Watson for page sentiment, Slawek explains it in our article on NLP and onpage SEO.

True Density vs. True Density + NLP

Standard True Density

  • We crawl top10 results for given query

  • Then we extract the data about popularity of common words and phrases

  • Based on the competitor’s content, we determine the density of each word and phrase from the list.

  • Next, Surfer analyzes your content in terms of the length and use of individual phrases and words. At this point, you already know which terms you should add and which should be reduced, as well as some specific actions recommended for optimal optimization.

True Density + NLP

  • We send the content from top10 results for given query to the Google NLP API

  • We cross the data from Google with Surfer’s calculation

  • We compare your site content to the calculation result

The ultimate goal for implementing the NLP is to provide you even more relevant terms to use within your content.

Which languages are supported in the NLP feature?

As the NLP features run in connection with Google’s NLP API we are only able to support the languages that the API supports, which are:

  1. English

  2. French

  3. German

  4. Italian

  5. Japanese

  6. Korean

  7. Portuguese

  8. Russian

  9. Spanish

  10. Simplified Chinese

  11. Traditional Chinese

How to use the NLP feature in the SERP Analysis

  • After logging in, you will arrive at the main dashboard. Here you are to create a query in the SERP Analyzer.

  • If you want to include the NLP feature, simply click “Additional Options” (as illustrated in the image below) and you will be presented with the NLP options to select for this query.

  • Once you’ve run the query you’ll be presented with the standard query result page, with some added features

NLP Sentiment

It’s important that you understand the overall sentiment of the page. Is it positive neutral or negative. and if so, how strongly is it?

  • You can access this data from the left sidebar.

  • Once you’ve opted to see sentiment by ticking the box, the graph will be updated to include the sentiment score.

  • The sentiment score ranges from 1 to -1. The higher or lower the score the more strongly that sentiment is expressed.

    • 0.25 to 1 means the page has positive sentiment

    • 0.25 to -0.25 means the page has neutral sentiment

    • 0.25 to -1.0 means the page has negative sentiment

The general rule is it would be more difficult to rank a page that has negative sentiment if the top ranking pages all have positive sentiment. This is most likely how Google understands user intent for the search query.

The sentiment score is displayed in the graph.

NLP entities

NLP entities are identified by the NLP badge next to the phrase, which can be seen as you open the audit and scroll to the True Density section.

NLP Entity Explained:

The entity is a word or phrase that represents an object which can be identified, classified, and categorized. Examples of objects are persons, consumer goods, events, numbers, organizations, etc. NLP’s job is to select and evaluate entities from your content. Since Google distinguishes those entities, the search engine is capable of utilizing obtained information in order to satisfy the user and provide better search results. Therefore, if we focus on these we are creating content that Google wants.

Average sentinement & relevancy


On the True Density section of a query audit you’ll find a positive, negative or neutral sentiment grade.

Why Sentiment?

When we are analyzing phrases we can also look at the sentiment of the phrase and the relevancy score of the word.

The average sentiment is scored:

Positive Negative Neutral It’s always a good idea to ensure you’re using the word with the same sentiment as competitors who are ranking high because it suggests that is how Google understands the user’s query.


You’ll find the relevance score on the True Density section of a query audit. It’s scored as a percentage with 100% being the most relevant term.

How to understand Surfer relevancy

Treat relevance as prioritization of your optimization process, but don’t make it a cap for using a term. They are all important, make sure to include as many as possible to make your content comprehensive.

Example: if the relevance score is 100 that means it’s a word or phrase that’s been used by all the top 10 pages.

How do I use NLP in the content editor?

First thing you need to do is make sure it’s switched on. This works similar to using NLP on the SERP query.

Once you’ve done that, the rest of the process is automated. It simply incorporates NLP into the True Density analysis and search term suggestions. Simply optimize the content as you would using Surfer normally and you are simultaneously optimizing for NLP as you are standard True Density.

Pricing and Plans and NLP

Each sentiment and entities analysis costs one credit. You can customize your query within the new input in SERP Analyzer and Content Editor.

The most “expensive query in SERP Analyzer costs you 3 NLP credits. In such a case, you get NLP Entities, NLP Sentiment Analysis, and NLP Sentiment for Entities.

In Content Editor, there’s only one option for NLP Analysis (entities).

Check out the latest Surfer pricing and packages