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Every agency owner and marketer knows this scene: it’s 10 p.m., you’re still in Excel or Google Sheets, wrestling with broken SUMIFS, hidden rows, and #DIV/0! errors while a client waits for a "simple" weekly report. Aggregating data isn’t hard in theory, but in the real world you’re stitching together exports, skipping error cells, and replaying the same clicks hundreds of times.
Learning how to aggregate data properly in Excel (with tools like AGGREGATE, SUMIFS, PivotTables, and Power Query) gives you clean, reliable rollups: totals by channel, averages by campaign, quartiles of deal size, and more. You can ignore hidden rows, filter out errors, and summarize millions of rows without crashing your file.
But the real unlock comes when you hand this work to an AI agent. Instead of burning hours cleaning sheets, the agent opens files, applies the right formulas, refreshes queries, and pastes results into dashboards on schedule. Your role shifts from spreadsheet janitor to strategist, reviewing insights instead of building them.
Before you automate, you need solid fundamentals. Here are core manual techniques your team already uses — and that your AI agent will eventually mimic.
Excel
=SUM( and drag over the numeric range (for example, =SUM(D2:D500)).=AVERAGE(range) or =COUNT(range) for averages and counts.
Google Sheets
=SUM(B2:B500), =AVERAGE(B2:B500), or =COUNT(B2:B500).
Pros: Simple, transparent.
Cons: Fragile with errors, hidden rows, and large datasets.
Excel
=SUMIF(A:A,"Google Ads",D:D) where column A is Channel and D is Spend.=SUMIFS(D:D, A:A, "Google Ads", B:B, "US").
Google Sheets
Use the same syntax: =SUMIFS(D:D, A:A, "Google Ads", B:B, "US").
Docs: https://support.google.com/docs/answer/7014145
Pros: Great for dashboards, simple reporting.
Cons: Hard to maintain when criteria change; very repetitive across many tabs/clients.
When sheets get messy, AGGREGATE saves you.
Example in Excel:
=AGGREGATE(9,6,D2:D500)9 = SUM6 = ignore error valuesD2:D500 = rangeNow your totals skip #DIV/0! and #NUM! without complex IFERROR wrappers.
Docs: https://support.microsoft.com/en-us/office/aggregate-function-43b9278e-6aa7-4f17-92b6-e19993fa26df
Pros: Powerful, handles dirty data.
Cons: Less known to teams; still manual setup.
Excel
Google Sheets
Pros: Fast multi-dimensional aggregation.
Cons: Still needs a human to refresh, tweak, and copy results into client-facing reports.
At some point, your Monday reporting ritual shouldn’t require opening 12 files by hand.
Use built-in features plus add-ons:
Query example:=QUERY('Raw Data'!A1:F, "select C, sum(F) where A >= date '2025-01-01' group by C", 1)
Docs: https://support.google.com/docs/answer/3093343 (QUERY)
Pros: Fully browser-based, good for agencies living in Sheets.
Cons: Connectors cost money; complex queries are hard for non-technical staff.
Power Query turns raw exports into repeatable pipelines.
Pros: Excellent for large datasets and repeatable transformations.
Cons: Setup takes time; still needs someone to open the workbook and hit Refresh (or configure more advanced refresh setups).
You can:
Pros: No code, connects many tools.
Cons: Logic lives outside the spreadsheet; debugging can be tricky, and you’re still limited to formula-based aggregation.
Manual and no-code methods get you partway. But for agencies and teams managing dozens of client workbooks, the real pain is orchestration: opening files, checking if data synced, fixing new errors, copying charts into decks.
This is where a desktop-class AI computer agent such as Sai becomes your reporting analyst.
You can configure an AI agent to:
Pros
Cons
Because Simular’s agents are designed for workflows with thousands to millions of steps, you can:
Example weekly workflow for an agency:
You get the reliability of production-grade automation and the flexibility of a human analyst — without anyone babysitting spreadsheets at midnight.
