The Scenario
You are an email deliverability manager. Last week, your complaint rate spiked. Benchmark Email flagged two campaigns, your inbox placement has dropped, and your marketing director wants to understand what happened before the next send goes out.
You have 10 campaigns from the past month in a Google Sheet by campaign ID. You need to pull the abuse report data, find which campaigns drove the spike, and have a slide-ready summary for the marketing director by Thursday at 11 AM.
It is Wednesday morning.
The slow version:
- Click into campaign 1 in Benchmark Email, navigate to the abuse reports section, read the complaint count, write it down
- Open the sheet, paste the number
- Repeat for all 10 campaigns
- Calculate the complaint rates by hand because Benchmark Email shows counts, not percentages
- Format everything
- It is 4 PM, you have the raw numbers but no narrative, and Thursday is tomorrow.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that pulls abuse report data from Benchmark Email and writes the analysis in the same step, so you do not have to collect data and think about it separately.
Open the SheetXAI sidebar and type:
Fetch Benchmark Email abuse report data for all campaign IDs in column A of my sheet and write campaign name, send date, abuse count, complaint rate, and total sends into columns B through F. Highlight any row where the complaint rate exceeds 0.1% with a note in column G. Then in a Summary tab, write a short paragraph explaining which campaigns drove the spike and what they have in common.
SheetXAI pulls the abuse data for every campaign, writes the stats, flags the outliers, and produces the narrative summary. You have the full picture by the time you finish your coffee.
What You Get
A complete abuse report table plus a narrative:
- Campaign name and send date — columns B and C
- Abuse count and complaint rate — columns D and E, with complaint rate calculated as a percentage of total sends
- Total sends — column F
- Flags in column G — "Above threshold" for any campaign over 0.1%, blank otherwise
- Summary tab — a short paragraph identifying which campaigns drove the spike and what they share
The complaint rate is calculated from the raw counts. You are not eyeballing a percentage, you are seeing the math.
What If the Data Is Not Quite Ready
Deliverability investigations have a way of requiring more context than the initial brief.
When some campaign IDs in column A return no abuse report data
A few campaigns may have been paused before sending, so there are no abuse reports. You want to skip those without erroring out.
Fetch abuse report data from Benchmark Email for all campaign IDs in column A. If a campaign has no abuse report data, write "No data" in column B and leave the rest blank. For campaigns with data, write campaign name, abuse count, complaint rate, and total sends into columns B through F.
When you need to compare this month's complaint rates to the previous month
The marketing director wants to know whether this is a new trend or a continuing one.
Fetch abuse report data for all campaign IDs in column A. Write current month stats into columns B through F. Then write the average complaint rate across all campaigns into cell H1, and the average complaint rate for the previous 30 days (from the campaigns in the Previous tab column A) into cell H2. Write a comparison note in cell H3.
When you need to trace the spike to a specific list or segment
All 10 campaigns went to different audience segments. The spike might be segment-specific, not campaign-specific.
Fetch abuse report data for all campaign IDs in column A. Write campaign name, segment name (if available from the Benchmark Email API), abuse count, and complaint rate into columns B through E. Sort by complaint rate descending. In the Summary tab, note whether the high-complaint campaigns share a common segment or list.
When you need the full abuse analysis plus three actionable recommendations for the director
The data tells you what happened. The director wants to know what to do about it.
Fetch Benchmark Email abuse report data for all campaign IDs in column A. Write campaign name, abuse count, complaint rate, and total sends into columns B through E. Calculate the average complaint rate in cell F1. Flag campaigns above 0.1% in column F. In the Summary tab, write a paragraph about what drove the spike, and below it, write three concrete recommendations for reducing complaint rates on the next campaign based on what the data shows.
The pattern: pull the forensics and the recommendations in one prompt. The director gets the story, not just the spreadsheet.
Try It
Get the 7-day free trial of SheetXAI and open a sheet with Benchmark Email campaign IDs in column A, then ask SheetXAI to pull the abuse report data and surface the patterns. The Benchmark Email integration is included in every SheetXAI plan. See also how to pull campaign engagement stats for analysis or the Benchmark Email in Google Sheets overview.