Case Study:
Google’s understanding of the Software sector

January 2021

Executive Summary

Google uses Natural Language Processing (NLP) routines to convert its understanding of text into topics and concepts (Entities). We looked out how much understanding Google misses using this approach in the Software sector.

InLinks analyzed the page content of the top 10 Google results (in the US Market) ranking for the phrase Native Trends and compared the Named Entities recognized by Google’s NLP API with the proprietory routines designed by Inlinks to uncover gaps in Google’s machine learning in the Software sector

The results showed that 24.8% of entities seen on the results in the Software sector SERPS (search engine Results pages) were positively identified by Google.

This compares to 18.5% average across all analyzed industry sectors.

How the Sector Compares

Different sectors tend to be analyzed with a different degree of accuracy by the search engines. This stems from two main challenges.

  1. the more demand there is by consumers within a given sector, the more the need for search engines to apply more sophisticated entity recognition to better answer user queries.
  2. the more sophisticated the industry is in creating search-friendly content, the more search engines can surface topics and concepts.


Software Industry Google Analysis InLinks Analysis
Avg. Number of words per page 883
Avg. Number of Topics per page 11.4 46
Benchmark - Avg. nb of entities/page (all sectors) 8.6 47.2
Of which, Topic types are:    
- Persons 9 0
- Organizations 29 29
- Cities & geo. areas 11 9
- Concepts 43 293
Semantic Density   5.8

How the research was conducted

Google’s Search API returned URLs for the following sites competing for this phrase:

#offers.nativeadvertisinginstitute,,, #alibabacloud, #facebook, #forbes, #redhat, #techrepublic

The texts of each page are then sent to Google’s NLP API, in order to determine which entities are identified by the search engine. These are important for search since Google is then able to link these to its Knowledge Graph to feed its services including Google Discover, Google search, Voice Search and Google News. (Although, correct identification does not guarantee inclusion in these results)

Here is first of all the synthesis of the results returned by Google:

  • 43 concepts, including Cloud computing (detected 4 times) Kubernetes (3) Amazon Web Services (3)
  • 29 organizations, including Microsoft (3) Apple Inc. (2) Google (1)
  • 9 persons, including Kubernetes (2) Microsoft Most Valuable Professional (1) Google Developer Expert (1)
  • 7 geographical areas, including United States (2) China (2) U.S. Route 95 (1)
  • 4 cities, including Bullhead City, Arizona (1) Morgantown, West Virginia (1) La Jolla (1)
  • 1 event, including SUSE (1)
  • 1 person, including Li Xuerui (1)

Errors in Google’s Detection Rate

Here are some errors in the categorization of entities:

  • Arizona categorized as a concept instead of geographical area
  • West_Virginia categorized as a concept instead of geographical area
  • California categorized as a concept instead of geographical area
  • Alaska categorized as a concept instead of geographical area

Most important entities (provided by InLinks), compared to those identified by Google:

  • Business (seen 5 times) => NOT detected by Google
  • Management (5) => NOT detected by Google
  • Fad (5) => NOT detected by Google
  • Information technology (5) => NOT detected by Google
  • Cloud computing (5) => detected by Google
  • Software development (4) => NOT detected by Google
  • Software (4) => NOT detected by Google
  • Data (4) => NOT detected by Google
  • Adoption (4) => NOT detected by Google
  • Customer (4) => NOT detected by Google
  • Service (economics) (4) => NOT detected by Google
  • Server (computing) (4) => NOT detected by Google
  • Google Cloud Platform (3) => detected by Google
  • Amazon Web Services (3) => detected by Google
  • Tool (3) => NOT detected by Google

How can the Software Industry benefit from this report?

By understanding where Google is failing to recognize important concepts within the industry, there is an opportunity for companies in the sector to write clearer content that Google can better understand.

Another option is to explicitly state these concepts in Webpage schema for machine learning algorithms to take into account. This would require using and the "about" and mentions" properties for important concepts such as Software development, Software, Server (computing).


Internal linking of topics topages dedicated to each important topic will also help to reduce cannibalisation of content in Google’s understanding of contect within your content.

In Summary

Google's understanding of the Software market, based on its NLP algorithms remains limited at 24.8% for this industry. Businesses either need to improve their schema or make their content more understandable by Google to improve its level of understanding.

SERP results

Kubernetes, Google, BigQuery, SUSE, Cloud computing, Hyperscale computing, Microsoft, Machine learning, Google Cloud Platform, Red Hat, International Institute of Information Technology, Hyderabad, Amazon Web Services, Microsoft SQL Server, OpenShift, Amazon (company), Apple Inc., VMware, Industrial internet of things, Cisco Systems, Veeam, New Relic, Pure Storage, Intel, Microsoft Most Valuable Professional, Internet of things, Google Developer Expert, Big data, DevOps, Git, AWS Lambda

Facebook, Arizona, Bullhead City, Arizona, Native Americans in the United States, Apache, Navajo, Opata, U.S. Route 95

Kubernetes, Cloud computing, Machine learning, Europe, North America, Asia, DevOps, Docker (software), Amazon Web Services, Apple Inc., AWS Lambda, Consul (software), Amazon Elastic Compute Cloud, Content as a service, Nginx, Prometheus (software)

Alibaba Group, Cloud computing, Cloud native computing, Yang Haoran, Luzhi, Yuquan Shenxiu, Microsoft, Kubernetes, China, Docker (software)

Meredith Corporation, All rights reserved

Amazon Web Services, Forrester Research, Cloud computing, Microsoft Azure, Alibaba Cloud, TechRepublic, Multicloud, ZDNet, Moderna, Lowe's, Etsy, Network security, Kubernetes, Pandemic, Microsoft

United States, PubMed, Infective endocarditis, West Virginia, Morgantown, West Virginia, West Virginia University, Aortic valve replacement, California, Mayo Clinic, La Jolla, University of California, San Diego, Analysis of covariance, Generalized linear model, Chi-squared test, Ampere hour, China

Kubernetes, Ovum Ltd., DevOps, Linux

Alaska, PubMed, Public health, Alaska Natives, Anchorage, Alaska, United States, National Cancer Institute, Li Xuerui

World Association of Newspapers and News Publishers, Native advertising, T Brand Studio, JP/Politikens Hus, Mediahuis Nederland

© 2019-2020 - - About us - Terms of Use - Privacy Policy