The Line as Rows
Interest over time comes back one row per point — date, term, and the nought-to-hundred value — for anything from the past hour to the whole run since 2004.
Google Trends has no API and no absolute numbers. AllyHub pulls the data with its parameters attached, so the figures still mean something later.
A Google Trends chart is a picture of a ratio, and the ratio changes when you change the question. AllyHub takes the numbers behind it — the timeline, the map, the related queries with their growth figures — with the term, place, range, category and search type recorded on every row, across as many terms and windows as you want, and out as a file.
Interest over time comes back one row per point — date, term, and the nought-to-hundred value — for anything from the past hour to the whole run since 2004.
Interest by country, and by region or city inside it, as rows rather than a shaded map — so you can sort by where the term actually indexes highest.
Related queries and topics, split into top and rising, each carrying what Google prints beside it — a growth figure like +250%, or the Breakout label when it has no ceiling yet.
Term, country, time range, category and search type ride along with the value, because a Trends figure detached from its query is a number nobody can reproduce.
Run a set of terms together, or the same term across several countries and date ranges, and it all lands in one table you can line up.
Take CSV, JSON, or Excel — or hand the same pull to AllyHub’s trends analysis when you want the reading rather than the record.
Say the terms, the places, and the window — and get the numbers rather than the chart.
Name one term or a set, the countries, the date range, and a category or search type if it matters. Plain sentences work.
It records the interest-over-time points, the regional and sub-regional breakdown, and the top and rising related queries and topics — each row stamped with the query that produced it.
Take the file, or send it on to be read. Save the term set and its parameters as a Playbook so next quarter is pulled the same way.
Google Trends gives you a chart, no API, and numbers that only mean something inside your own question.
Trends reports search interest, not searches. The peak inside your window is set to a hundred and every other point is a fraction of it, so widening the range or switching country recalculates the lot — the searches didn’t change, the scale did.

Pull one term over five years and again over ninety days and the two shapes will disagree; neither is wrong. Running both on purpose, in the same table, is the difference between reading the data and being caught out by it.

Most exports flatten related queries into a list of strings and lose the part that carried the information — the percentage beside each one, and the Breakout label Google uses when a term has gone up too far to put a number on.

Quarter-on-quarter comparison only works if the range, the country and the category were identical, which is exactly what nobody remembers three months later. Save the pull as a Playbook and the parameters come with it — and because AllyHub never starts from scratch again, the refresh costs a sentence.

Analysts, multi-market researchers, newsroom data desks, and category teams who need the numbers behind the chart with their parameters intact.
The pain: you want search interest as an input to a model, and what Google gives you is a picture with a CSV button that hands back one chart at a time. Take the points as rows, with the query recorded, and the series is something you can join to the rest of your data instead of retype.
The pain: the same term in eight countries means eight charts, each scaled to its own peak, and a screenshot deck that quietly compares things that aren’t comparable. Pull them together with the geography on every row, and at least the comparison is being made on purpose.
The pain: you want to cite a Trends figure in a piece, and a reader — or an editor — will ask which window it came from. If the parameters aren’t stored beside the number, the answer six months later is a shrug. Store both and the claim survives the fact-check.
The pain: the quarterly review sets this quarter’s Trends numbers against last quarter’s, and last quarter’s were pulled over a different range by someone who has since left. Fix the parameters once and the two quarters are finally measuring the same thing.
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What people ask before pulling Trends data — what the numbers are, what you can set, and which tool does what.
It takes what Google Trends draws — the interest line, the regional breakdown, the related queries — and returns it as records instead of a chart. AllyHub takes the brief in ordinary sentences, handles several terms, countries and date ranges in one pull, and writes the query parameters onto every row.
Yes. One term over one range and one country runs on the free plan. Sets of terms, several geographies or windows in a single pull, scheduled re-pulls, and handing the result on for analysis are what the paid plans cover.
No, and this trips up more Trends work than anything else. Google publishes search interest: each point is divided by total searches for that place and period, then scaled so the highest point in your selection sits at 100. A term at 40 is at forty percent of its own peak, not forty of anything absolute — and changing the window makes the same underlying searches produce different numbers.
There isn’t one, which is most of the reason this category exists. AllyHub reads the Trends interface itself, so there’s no key to obtain and nothing to keep credentialled, and no waiting on an API Google hasn’t shipped.
The ones Trends itself offers: worldwide down to a country and the regions inside it, ranges from the past hour through to 2004 onward including custom windows, plus the category and search-type filters. Whichever combination you pick is recorded with the data, since it’s what the numbers are relative to.
Use this when you want the data — rows to join, to chart, or to archive. Use Google Trends Analysis when you want the reading: what the shape means, where the cycle sits, which way momentum points. The same pull can feed straight into it.
Trends exports one chart’s CSV at a time, without the parameters written into the file, and it won’t do a set of terms across several countries in one go. AllyHub pulls the lot in one job, stamps each row with the query behind it, and keeps the whole setup as a Playbook — so it compounds with every task rather than being reassembled each quarter.