How to build a reach calculator in Google Sheets guide

## 1. Manual ways to calculate marketing reachBefore we talk automation, it helps to understand the manual workflow you’re trying to offload.### Method 1: Single‑channel reach in Google Sheets1. Create a new spreadsheet in Google Sheets.2. In row 1, add headers: `Date`, `Campaign`, `Channel`, `Impressions`, `Frequency`, `Reach`.3. Each reporting period, export data from your ad platform (e.g., Meta Ads, Google Ads) and paste rows into the sheet under the right columns.4. In the `Reach` column, use the basic formula: - `=D2/E2` assuming `D` is Impressions and `E` is Frequency.5. Drag the formula down for all rows.6. Use `Insert → Chart` to visualize reach trends.Official docs to help:- Create and edit Sheets: https://support.google.com/docs/answer/6000292- Work with charts: https://support.google.com/docs/answer/190718### Method 2: Multi‑channel reach with cost per reach1. Extend your header row with `Spend`, `Cost_per_Reach`.2. Paste spend for each campaign from your ad platforms into the `Spend` column.3. In `Cost_per_Reach`, use: - `=G2/F2` assuming `G` is Spend and `F` is Reach.4. Add a pivot table (`Insert → Pivot table`) to summarize reach and cost per reach by channel and by campaign.5. Filter the pivot to spot channels with low cost per reach.Docs:- Pivot tables: https://support.google.com/docs/answer/1272900### Method 3: Estimate reach from impressions onlyIf your platform does not give you frequency:1. Decide an estimated average frequency (e.g., 1.8 based on past campaigns).2. Add a `Freq_Assumed` column and fill with that value.3. Compute reach as `=Impressions / Freq_Assumed`.4. Clearly label this tab as "Estimated" so stakeholders don’t confuse it with actual reach.## 2. No‑code automation methodsManual pasting works for a couple of campaigns; it collapses when you manage dozens across channels. No‑code tools can move data into Google Sheets on a schedule.### Method 4: Use Google Ads’ built‑in Sheets export1. In Google Ads, create a custom report with `Impressions`, `Average frequency` (if available), `Cost` and identifiers like campaign and date.2. Schedule the report to export to Google Sheets.3. In your destination Sheet, add calculated columns for `Reach` (`=Impressions / Frequency`) and `Cost_per_Reach`.4. Use filters and charts to analyze.Docs:- Schedule Google Ads reports to Sheets: https://support.google.com/google-ads/answer/2404182### Method 5: Connect platforms via no‑code automation (e.g., Zapier/Make)1. Create a new Sheet and define your schema (headers for impressions, spend, frequency, etc.).2. In your no‑code tool, set up a scenario/"Zap" that: - Triggers on a scheduled time (e.g., daily at 1am). - Calls each ad platform’s API to get yesterday’s performance. - Appends a row to your Google Sheet via the Google Sheets connector.3. In Sheets, use array formulas so new rows are auto‑calculated: - In `Reach`: `=ARRAYFORMULA(IF(D2:D="",,D2:D/E2:E))` - In `Cost_per_Reach`: `=ARRAYFORMULA(IF(F2:F="",,G2:G/F2:F))`4. Protect your formula columns so they can’t be overwritten (`Data → Protect sheets and ranges`).Docs:- ARRAYFORMULA: https://support.google.com/docs/answer/3093275- Protect ranges: https://support.google.com/docs/answer/1218656### Method 6: IMPORT functions from public sourcesIf you’re estimating reach from public stats (e.g., YouTube channel views as a proxy):1. Use `IMPORTXML` or `IMPORTHTML` to fetch stats into Sheets.2. Example: `=IMPORTXML("https://example.com/campaign-report","//table[1]//tr")`.3. Parse the relevant columns and apply your reach formulas.Docs:- IMPORTXML: https://support.google.com/docs/answer/3093342- IMPORTHTML: https://support.google.com/docs/answer/3093339## 3. Scaled, AI‑agent workflows with an AI computer agentAt some point, even no‑code automation hits a wall: complex logins, 2FA, different report layouts per client, or channels that lack good APIs. This is where an AI computer agent that can actually use your desktop and browser shines.### Method 7: Agent as your cross‑channel reporting assistant**What it does**- Opens your browser, logs into Meta, Google Ads, LinkedIn, TikTok, etc.- Navigates to saved reports, sets date ranges, downloads CSVs.- Opens Google Sheets, uploads or pastes fresh data into the right tabs.- Applies or updates formulas for reach and cost per reach.**How to set it up (conceptually):**1. Record or describe the workflow once: which URLs to visit, which reports to download, where to paste in Sheets.2. Let the agent run the sequence while you watch; correct it when column orders or UI elements differ.3. Save this as a reusable "reach refresh" workflow and schedule it via webhook or cron from your data stack.**Pros**- Handles platforms with weak or no APIs.- Survives UI changes better than brittle RPA scripts because it “sees” the screen.- Frees your marketing ops team from late‑night reporting crunches.**Cons**- Initial onboarding time to teach the agent your exact process.- Needs clear guardrails (e.g., which accounts and tabs it’s allowed to touch).### Method 8: Agent as anomaly hunter for reach efficiency**What it does**- Opens your master Google Sheet each morning.- Scans for campaigns where cost per reach jumped beyond a threshold.- Leaves comments in the sheet or posts summaries into Slack/Email.**Setup outline**1. Add a `Status` column and an `Alert` rule in your Sheet (e.g., `=IF(Cost_per_Reach>TARGET,"CHECK","OK")`).2. Give the AI agent a simple instruction: “Each day, find rows where `Alert` = CHECK, summarize them, and notify our sales/marketing channel.”3. The agent reads and writes directly in your Sheet, so there’s no custom code.**Pros**- Tells you where to act, not just what happened.- Easy for non‑technical marketers to tweak thresholds and logic.**Cons**- Still depends on the quality of your underlying formulas.- Needs periodic review so it’s aligned with new campaign goals.