The Scenario
It is the third time this month the content team has been asked to prioritize the editorial calendar without real demand data. The content strategist has 60 topic ideas in column A of an Excel workbook — product review angles, how-to guides, comparison posts — and needs Google Trends scores to make the case for which ones to greenlight for Q3. The editorial planning meeting is tomorrow morning.
The bad version:
- Open Google Trends, search topic 1, screenshot the interest-over-time chart, note the rough average, type it into column B
- Search topic 2, notice that Trends compares relative to itself rather than giving an absolute number, and realize the scores across separate searches are not directly comparable
- Spend the afternoon reading Trends documentation, conclude that a consistent comparison requires running all topics together in a single multi-term query, discover that Trends allows maximum five terms at once, and do the math on how many batches 60 topics requires
The planning meeting is not going to wait for your Trends methodology to resolve itself.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the topic list in column A, calls SerpApi's Google Trends endpoint for each keyword with consistent parameters, and writes the interest scores back — all 60 rows, with comparable methodology across every entry. One prompt.
For each keyword in column A, get the Google Trends interest score for the past 12 months in the US and put the score in column B
What You Get
- Column B receives the 12-month average interest score (0-100 scale) for the US
- Scores are produced with consistent query parameters across all topics, making them comparable row to row
- Topics with insufficient Trends data get a note in column C rather than a zero that would skew any ranking you build from the data
What If the Data Is Not Quite Ready
You want both US and UK scores side by side
For each keyword in column A, get the Google Trends interest score for the past 12 months in the US and in the UK, and write the US score in column B and the UK score in column C
You want peak score, not average
For each keyword in column A, get the Google Trends data for the past 90 days and write the peak interest value in column B and the average interest value in column C
Some topics in column A are too broad and need sub-topic lookup
For each keyword in column A, search Google Trends via SerpApi and if the term returns a disambiguation (multiple topic matches), use the first suggested topic entity rather than the raw keyword string; write the resolved entity name in column B and the interest score in column C
Full scoring, ranking, and editorial flag in one prompt
Pull Google Trends 12-month interest scores for each keyword in column A (US, past 12 months), write the score in column B, rank the topics from highest to lowest score in column C, and flag in column D any keyword with a score below 20 as "low demand — reconsider"
The scoring and the editorial flag land together.
Try It
Get the 7-day free trial of SheetXAI and open your editorial planning workbook before the next content review, then ask SheetXAI to pull Google Trends scores for every topic. Also see the spoke on bulk-searching YouTube for content benchmarks, or the hub overview of all SerpApi workflows.