Multi-Platform Autocomplete Keyword Research with Google Search, YouTube, and Places APIs (Notebook)

Manually brainstorming keyword variations and search intent patterns is limited by human imagination—this comprehensive Google Colab notebook automates keyword discovery by tapping into four different Google autocomplete endpoints (Google Search, YouTube Search, Query Autocomplete via Places API, and Place Autocomplete via Places API) to generate hundreds of real user search suggestions for any seed keyword. Created by Lazarina Stoy for MLforSEO, this workflow is specifically designed for SEO professionals and content marketers who need to discover actual user search behavior patterns, long-tail variations, and location-based query modifications by leveraging the same autocomplete data that powers Google’s search suggestions—revealing what real users type when searching for topics related to your seed keywords. The multi-platform approach captures different search contexts: Google Search autocomplete reveals informational and navigational queries, YouTube autocomplete uncovers video content opportunities, Query Autocomplete identifies location-based search patterns (like pizza near Paris), and Place Autocomplete surfaces business and venue searches—providing a 360-degree view of how users search across different Google properties.
The notebook implements four independent autocomplete modules with flexible parameter configuration for the Places API sections. For Google Search and YouTube autocomplete (implementation details hidden in collapsed cells), the workflow likely queries their respective autocomplete endpoints. For Places API modules, you upload a CSV file with a Keywords column containing your seed terms, enter your Google API key (requires enabled billing on Google Cloud project), and optionally specify parameters like language code (default en), location coordinates (latitude/longitude for geographic bias), search radius in meters (default 50,000), country components, and place types. The Query Autocomplete module fetches location-based query predictions (ideal for local SEO and geo-targeted queries), while the Place Autocomplete module returns business and venue suggestions (perfect for local business research). For each seed keyword, the script makes API requests with a 0.5-second delay to respect rate limits, retrieves all autocomplete predictions returned by the API, and compiles results into downloadable CSV files with two columns: Seed Keyword (your original input) and Suggestion (the autocomplete prediction). The Places API responses include structured data with human-readable descriptions, matched substrings, and geographic details—enabling immediate use in keyword research, content planning, or PPC campaign organization.
Use this for:
‧ Multi-source keyword discovery by collecting autocomplete suggestions from four different Google platforms in one workflow—capturing informational queries, video content ideas, and location-based searches
‧ Local SEO keyword research using Query Autocomplete to discover how users modify searches with location qualifiers (near me, in [city], near [landmark])
‧ Business and venue keyword mining with Place Autocomplete to find how users search for businesses, restaurants, services, and points of interest
‧ Content gap analysis by comparing what autocomplete suggests versus your existing content—revealing topics and variations you haven’t covered
‧ PPC keyword expansion for local campaigns by discovering location-modified queries and place-based searches that trigger high-intent traffic
‧ YouTube content strategy by uncovering video-specific search patterns and trending topics through YouTube autocomplete data
‧ Geographic keyword variation analysis by setting location parameters to see how autocomplete suggestions differ by region or city
‧ Language-specific keyword research using the language parameter to discover search patterns in different markets for international SEO
This is perfect for SEO specialists, content marketers, local SEO consultants, and PPC managers who need comprehensive keyword discovery beyond traditional keyword research tools—particularly valuable when exploring new content topics, building location-based keyword lists for local SEO campaigns, researching YouTube content opportunities, discovering long-tail variations for niche markets, or validating keyword ideas with real autocomplete data that reflects actual user search behavior across multiple Google platforms rather than relying solely on search volume data or manual brainstorming.