Google Cloud

Google Cloud is Google’s platform of cloud services: computing, storage, databases, analytics and a large catalogue of machine learning APIs and models. For SEOs and marketers it matters mainly as the home of ready-made ML services you can call with an API key, such as the Natural Language API and the Knowledge Graph Search API, without building or hosting any models yourself.

How it works

Everything in Google Cloud lives inside a project. To use an API you:

• create a project in the Google Cloud console,
• enable the API you need (for example Cloud Natural Language API),
• attach a billing account, even if you stay within free usage, and
• create credentials, usually an API key for quick work in Sheets or Colab, or a service account for production scripts.

Your script or spreadsheet then sends text or data to the API and receives structured results back, such as entities with types and salience, sentiment scores, content categories or knowledge graph matches. Usage is billed per unit after a free monthly allowance; for example, the Natural Language API’s pricing page lists the first 5,000 units of entity analysis each month as free.

How it’s used in SEO and marketing

• Natural Language API for entity extraction, entity sentiment, sentiment analysis, syntax analysis, content classification and moderation.
• Knowledge Graph Search API to check whether Google recognises an entity and how it is typed and described.
• Vision API for image labels and colours, useful for image SEO and ecommerce clustering.
• BigQuery for storing large keyword universes and Search Console bulk exports.
• Gemini models, served through the platform formerly called Vertex AI, for generative tasks.

Example

A content team wants to know whether its key guides are clearly about the entities it targets. It creates a Google Cloud project, enables the Natural Language API, pastes the key into MLforSEO’s no-code entity template, and runs the main text of 50 guides through it. The output lists each page’s entities, types and salience, which shows where a guide’s main subject is buried.

Limitations and things to watch

• Billing must be enabled, so set budgets and alerts in the console before running large jobs.
• Restrict API keys to the specific APIs and, where possible, to known referrers or IP addresses.
• Product names change. Vertex AI was folded into Gemini Enterprise Agent Platform in April 2026, so older tutorials may use outdated menu names.
• Check data residency and processing terms before sending personal or client data.

Learn it on MLforSEO

• How to do Entity Extraction with Google’s Natural Language API in Google Sheets (Apps Script)
• How to do Text Classification with Google’s Natural Language API in Google Sheets (Apps Script)
• Comparing NLP APIs for Entity and Sentiment Analysis (vs Generative AI)
• Text Classification with Google Cloud Natural Language API in Python (Google Colab Notebook)
• The Introduction to Machine Learning for SEO course, which sets up Google Cloud APIs in its practicals