1. Manual aggregation methods (Excel & Google Sheets)

Before you automate, you need solid fundamentals. Here are core manual techniques your team already uses — and that your AI agent will eventually mimic.

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1.1 Basic SUM, AVERAGE, COUNT

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Excel

1. Select a cell where you want the total.
2. Type =SUM( and drag over the numeric range (for example, =SUM(D2:D500)).
3. Press Enter.
4. Repeat with =AVERAGE(range) or =COUNT(range) for averages and counts.
   Official docs: https://support.microsoft.com/en-us/office/sum-function-043e1c7d-7726-4e80-8f32-07b23e057f89

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Google Sheets

1. Click the result cell.
2. Use =SUM(B2:B500), =AVERAGE(B2:B500), or =COUNT(B2:B500).
3. Drag the fill handle down to reuse formulas across rows.
   Docs: https://support.google.com/docs/answer/3093991

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Pros: Simple, transparent.
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Cons: Fragile with errors, hidden rows, and large datasets.

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1.2 Conditional aggregation with SUMIF / SUMIFS

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Excel

1. To sum spend for a single channel: =SUMIF(A:A,"Google Ads",D:D) where column A is Channel and D is Spend.
2. For multiple conditions (e.g., Channel + Region):
   =SUMIFS(D:D, A:A, "Google Ads", B:B, "US").
   Docs: https://support.microsoft.com/en-us/office/sumifs-function-c9e748f5-7ea7-455d-9406-611cebce642b

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Google Sheets
Use the same syntax: =SUMIFS(D:D, A:A, "Google Ads", B:B, "US").
Docs: https://support.google.com/docs/answer/7014145

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Pros: Great for dashboards, simple reporting.
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Cons: Hard to maintain when criteria change; very repetitive across many tabs/clients.

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1.3 Excel AGGREGATE to ignore errors/hidden rows

When sheets get messy, AGGREGATE saves you.

Example in Excel:

• =AGGREGATE(9,6,D2:D500)
  • 9 = SUM
  • 6 = ignore error values
  • D2:D500 = range

Now 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

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Pros: Powerful, handles dirty data.
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Cons: Less known to teams; still manual setup.

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1.4 Pivot tables (Excel & Sheets)

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Excel

1. Select your table (Ctrl+A inside the data).
2. Go to Insert → PivotTable.
3. Place the pivot on a new sheet.
4. Drag Channel to Rows, Month to Columns, Spend to Values.
5. Change Value settings (Sum, Average, Count) as needed.
   Docs: https://support.microsoft.com/en-us/office/create-a-pivottable-to-analyze-worksheet-data-a9a84538-bfe9-40a9-a8e9-f99134456576

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Google Sheets

1. Select your data.
2. Click Insert → Pivot table.
3. Choose a destination.
4. Add Rows, Columns, Values, and Filters.
   Docs: https://support.google.com/docs/answer/1272900

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Pros: Fast multi-dimensional aggregation.
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Cons: Still needs a human to refresh, tweak, and copy results into client-facing reports.

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2. No-code automation for recurring aggregation

At some point, your Monday reporting ritual shouldn’t require opening 12 files by hand.

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2.1 Scheduled imports into Google Sheets

Use built-in features plus add-ons:

1. Connect your CRM or ad platforms via a connector (e.g., from the Google Workspace Marketplace).
2. Configure a scheduled refresh (daily/weekly).
3. Build pivot tables or QUERY-based summaries on top of the raw tab.

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)

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Pros: Fully browser-based, good for agencies living in Sheets.
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Cons: Connectors cost money; complex queries are hard for non-technical staff.

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2.2 Power Query in Excel

Power Query turns raw exports into repeatable pipelines.

1. In Excel, go to Data → Get Data (From File, From Web, From OData, etc.).
2. Load your source (CSV, database, OData feed like Northwind).
3. In Power Query Editor, group and aggregate:
   • Right-click a column like Order_Details.
   • Click the expand icon, choose Aggregate.
   • Pick Sum, Average, Count, etc.
4. Click Close & Load to push the aggregated table back into Excel.
   Docs: https://support.microsoft.com/en-us/office/aggregate-data-from-a-column-power-query-14b85bee-aec4-4816-96d7-372a1439cf5b

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Pros: Excellent for large datasets and repeatable transformations.
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Cons: Setup takes time; still needs someone to open the workbook and hit Refresh (or configure more advanced refresh setups).

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2.3 Workflow tools (Zapier, Make, etc.)

You can:

1. Trigger on a schedule (every day at 7 a.m.).
2. Pull data from your CRM/ads tool.
3. Append it into a Google Sheets or Excel Online table.
4. Let built-in formulas/pivots recalc the aggregates.

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Pros: No code, connects many tools.
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Cons: Logic lives outside the spreadsheet; debugging can be tricky, and you’re still limited to formula-based aggregation.

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3. Scaling aggregation with AI computer agents

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 Simular Pro becomes your reporting analyst.

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3.1 Agent-driven Excel and Sheets aggregation

You can configure an AI agent to:

• Open Excel workbooks and Google Sheets in a browser.
• Import the latest CSV exports or trigger Power Query refresh.
• Insert or adjust formulas like AGGREGATE, SUMIFS, or QUERY.
• Rebuild PivotTables if schemas changed.
• Copy summarized tables into a clean "Client Report" tab or a Google Slide.

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Pros

• Hands-free execution: the agent does the clicks, keystrokes, and navigation across desktop, browser, and cloud.
• Works with messy, real-world interfaces (not just APIs).
• Transparent: every action is logged and replayable.

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Cons

• Requires initial setup and clear instructions.
• Best value at scale (multiple clients, many reports).

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3.2 Multi-step, high-volume workflows

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Because Simular’s agents are designed for workflows with thousands to millions of steps, you can:

• Run nightly aggregation across all client folders.
• Let the agent detect errors (failed formulas, #VALUE!, broken links) and repair them using AGGREGATE or alternate logic.
• Post results into CRMs, project tools, or email summaries.

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Example weekly workflow for an agency:

1. Agent opens each client’s Google Sheet and linked Excel model.
2. Refreshes data sources (API connectors, Power Query, CSV imports).
3. Validates key metrics (e.g., total spend vs. platform numbers).
4. Regenerates pivot tables and charts.
5. Exports PDFs and drops them into a shared folder or sends by email.

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You get the reliability of production-grade automation and the flexibility of a human analyst — without anyone babysitting spreadsheets at midnight.

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