The Scenario
The quarterly product roadmap review is in two weeks. You're a product manager and you've spent the past month collecting feature name candidates — seventy ideas that came out of customer interviews, support tickets, and internal brainstorms, all sitting in column A of a sheet. The exec team wants to see which features have real market momentum before the team commits to the next development cycle.
Google Trends is the cleanest proxy you have for relative public interest. SerpHouse can query it. But seventy rows is seventy individual Trends lookups, and each one involves choosing a time window, a geography, and a category — then manually reading the interest score and typing it back into the sheet.
The bad version:
- Open Google Trends, type in feature idea one, set the time window to 12 months, US geography, note the peak interest score and current trend direction
- Switch back to the sheet, find the row, type the values in
- Repeat sixty-nine more times, keeping track of which ideas you've already done and which you skipped because the name was too generic to search cleanly
By the time you're done, the roadmap meeting is tomorrow and you still haven't done the analysis part.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads the feature name list, queries Google Trends via SerpHouse for each term, and writes the interest score and trend direction back into the columns you specify — in one pass.
For each keyword in column A, get the Google Trends interest score for the past 12 months via SerpHouse and fill in the score and trend direction into columns B and C
What You Get
- Column B receives the relative interest score for each feature name (0–100 scale, normalized to the peak within the set)
- Column C receives the trend direction — rising, stable, or declining — based on the slope of the interest curve over the period
- Rows where SerpHouse returns no Trends data for a term are marked clearly rather than left blank, so you know which feature names may be too niche or too new to have a signal
What If the Data Is Not Quite Ready
Some feature names are too generic and need category scoping
For each keyword in column A, search Google Trends via SerpHouse scoped to the "Technology" category for the past 12 months, and write the interest score and trend direction into columns B and C
You want to compare two time windows side by side
For each keyword in column A, get the Google Trends interest score for the past 12 months via SerpHouse and write it into column B, then get the score for the past 90 days and write it into column C, and flag column D as "Accelerating" if the 90-day score is more than 20 points higher than the annual average
You want to cross-reference with competitor feature names from a second tab
For each keyword in column A of the "Feature Ideas" tab, get the Google Trends interest score via SerpHouse for the past 12 months and write it into column B, then look up whether the same term appears in the "Competitor Features" tab and mark column C as "Overlap" if it does
You want to clean duplicates, score everything, rank by interest, and flag the top tier in one shot
Deduplicate column A, get the Google Trends interest score for the past 12 months via SerpHouse for each unique term, write the score into column B, sort the sheet by column B descending, and mark column C as "Prioritize" for any term scoring above 60
The roadmap conversation starts with data. Getting the data shouldn't be the thing that takes the week.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a list of feature names, product topics, or content ideas — ask SheetXAI to pull Google Trends interest scores from SerpHouse and populate the columns. See also localized SERP research or go back to the SerpHouse overview.