Search and demand
Google Trends data extraction
Search interest over time, regional breakdowns, and rising queries — pulled on a schedule so the series is yours, not a screenshot.
Trends is genuinely useful and painful to use at scale: one term at a time, a chart you cannot join to anything, and a comparison basket capped at five. The moment you want fifty terms tracked weekly against your own sales data, the interface stops being the answer.
We pull interest series, regional breakdowns, and rising queries on a schedule and land them in your warehouse, so seasonality and demand signals sit next to the rest of your data.
- Datasets
- Interest over time · By region · Related and rising queries
- Geography
- Country, region, and metro level
- Timeframes
- Hourly to five-year windows
- Categories
- Filtered by category and search type
- Scope unit
- Term set × geography × timeframe
- Refresh
- Daily or weekly
- Normalisation
- Anchor terms to keep series comparable
- Formats
- JSON · NDJSON · CSV · Parquet
- Delivery
- Postgres · BigQuery · S3 · Webhook · Sheets
Fields
What you receive.
The usual set. Fields can be added or dropped per project — you pay for what you take.
Google Trends fields
11- Search term and term group
- Geography and sub-region
- Timeframe and interval
- Relative interest index per interval
- Regional interest breakdown
- Related queries with relevance
- Rising queries with growth percentage
- Breakout flags on rising terms
- Category and search type filter
- Anchor term used for normalisation
- Capture timestamp
Used for
What clients do with Google Trends data.
SEO
Search result tracking, competitor visibility, and content research across search engines and the platforms that now rank inside them.
Use caseeCommerce
Competitor price, stock, and assortment monitoring matched to your catalogue, plus resale and marketplace pricing.
Use caseNews
Media, forum, and social monitoring for brand mentions, competitor moves, and sector developments, with alerting.
Questions
Asked before.
Does this give us search volume?
No, and nobody honest will tell you otherwise. Trends publishes a relative index scaled to its own peak, not absolute volumes. It is excellent for direction, seasonality, and comparison, and wrong for forecasting units sold.
How do you compare more than five terms?
By running overlapping baskets against a shared anchor term and rescaling to it. Done properly you get a comparable series across any number of terms; done carelessly you get numbers that quietly do not line up.
Can we join it to our own sales data?
That is the usual reason people buy it. The series lands in your warehouse with dates and geography, ready to join.
Next step
Get Google Trends data running.
Send the fields, the geography, and how fresh it needs to be. You will get back what is achievable and what it costs to run, usually within a day.