
Every agency has that one Friday afternoon ritual: exports from Facebook Ads, Google Ads, TikTok, LinkedIn… all landing in a jungle of CSV files. Then comes the copy-paste marathon into a “final” report that looks different every week. Clients get inconsistent views, your team dreads reporting week, and leaders are flying blind between channels.
A solid ads report template in Google Sheets fixes that. You define one source of truth: standard KPIs, consistent date ranges, clear campaign breakdowns, and a repeatable structure you can reuse across clients. Because Sheets is flexible and familiar, you can blend data from paid social, search, and email into one canvas, add calculated fields for ROAS, CAC, or MER, and layer conditional formatting so outliers pop instantly. Instead of reinventing the wheel every month, your team works inside a proven frame that tells a clear performance story in minutes.
Now imagine that template maintained by an AI computer agent. Rather than your team logging into every ad account, downloading reports, and fixing formulas, the agent does the clicking, exporting, and updating for you. The same Google Sheets template stays fresh every morning, campaigns are already summarized, and your humans arrive to insight-ready dashboards instead of raw data. Reporting turns from a chore into a strategic lever you can trust at scale.
If you run ads for multiple brands, you already know: reporting can quietly swallow entire days. The right ads report template in Google Sheets can cut that work dramatically—and when you combine it with no-code tools and an AI computer agent like Simular, you can almost erase the manual grind.
Below are three levels of maturity: from hands-on, to automated, to fully agent-driven.
Raw_FacebookRaw_Google_AdsSummaryClient_NotesSummary, define your core KPIs in the header row: Spend, Impressions, Clicks, CTR, CPC, Conversions, CPA, ROAS.=SUM(Raw_Facebook!C:C) for total spend=SUM(Raw_Facebook!D:D + Raw_Google_Ads!D:D) for blended clicks=IFERROR(Clicks/Impressions,0)=IFERROR(Spend/Clicks,0)=IFERROR(Revenue/Spend,0)You’ve now created the base “canvas” for every future report.
File → Import and bring the data into the matching Raw_* tab (see https://support.google.com/docs/answer/9143382 for import options).Repeat this flow weekly or monthly. It’s tedious but gives you full control.
Summary tab, insert charts via Insert → Chart:Format → Conditional formatting) to:This manual but structured approach is your baseline. Once it works, you’re ready to automate pieces of it.
Several tools (like native connectors or third-party add-ons) can pipe ad data straight into Google Sheets on a schedule.
Typical setup pattern:
Extensions → your connector.Raw_* tabs update without you touching them.Your original formulas and charts in Summary now update automatically as the raw data refreshes.
Even without external tools, Sheets has functions that help reduce copy-paste:
IMPORTRANGE to pull from another Google Sheet that receives exported data: https://support.google.com/docs/answer/3093340IMPORTXML for simple web scrapes (e.g., competitor benchmarks): https://support.google.com/docs/answer/3093342Example:
=IMPORTRANGE("<source-sheet-url>", "Raw_Facebook!A:Z") to auto-pull the latest rows.This keeps the client report clean while another Sheet handles the messy imports.
File → Share in Google Sheets to give clients “Viewer” access.Show history so you can roll back errors if needed.You’ve now moved from “build every report from scratch” to “maintain a living template.” The final step is to stop even maintaining it manually.
This is where an AI agent stops being a toy and starts acting like a real teammate. Simular Pro can operate across your desktop, browser, and Google Sheets the way a human would—only with patience you don’t have.
You define the playbook once; the Simular AI agent runs it on a schedule:
Raw_* tabs.Because Simular Pro logs every action and is fully inspectable, you can see exactly how it pulled and updated numbers—no black-box behavior.
Workflow A: Daily multi-client refresh
Workflow B: Pre-meeting report pack
Pros
Cons
The trajectory is simple: start with a well-designed Google Sheets template, layer in no-code automations, then graduate to an AI computer agent that owns the end-to-end reporting workflow. That’s how agencies and in-house teams move from spreadsheet survival mode to truly scalable, insight-first reporting.
Start by deciding what questions your report must answer every time: How much did we spend? What did we get back? Which channels or campaigns drove results? Open a new Google Sheet and create separate tabs like `Raw_Facebook`, `Raw_Google_Ads`, and `Summary`. In the raw tabs, mirror the column names used by your ad platforms (Campaign, Date, Impressions, Clicks, Cost, Conversions, Revenue). This makes it easier to paste in exports without rework.
In the `Summary` tab, put your KPIs in the top row: Spend, Impressions, Clicks, CTR, CPC, Conversions, CPA, ROAS. Under each, write formulas that aggregate from the raw tabs, e.g. `=SUM(Raw_Facebook!F:F)` for Spend or `=IFERROR(SUM(Conversions)/SUM(Clicks),0)` for CVR. Add a date range filter by pointing formulas to a `Start_Date` and `End_Date` cell using `FILTER` or `SUMIFS`. Finish with charts and conditional formatting to highlight high or low performers. Once this skeleton works for one client, duplicate the file and simply swap the raw data for others.
The key is to normalize your data before you summarize it. In Google Sheets, create a separate raw tab for each platform: `Raw_Facebook`, `Raw_Google_Ads`, `Raw_TikTok`, etc. When you export reports, always include a consistent set of fields: Date, Campaign name, Ad set/Ad group, Impressions, Clicks, Spend, Conversions, Revenue. If a platform doesn’t have Revenue, set that column to 0 so formulas still work.
Then, build a `Combined_Raw` tab with an `={'Raw_Facebook'!A:G; 'Raw_Google_Ads'!A:G; 'Raw_TikTok'!A:G}` array formula (adjust ranges for your columns). This stacks all platforms into a single master table. Your `Summary` tab should reference `Combined_Raw` using `SUMIFS`, `QUERY`, or `PIVOT TABLE` to calculate KPIs by Channel, Campaign, or Country. For example, `=SUMIFS(Combined_Raw!F:F, Combined_Raw!B:B, "Facebook")` for Facebook spend if column B holds the Source. This way, you maintain platform-specific detail while unlocking a unified, blended view for leadership or clients.
Most templates break because column orders change, naming conventions drift, or people overwrite formulas. Start by locking the structure: use one header row in every raw tab and avoid inserting random rows above it. Protect formula ranges with `Data → Protect sheets and ranges`, giving edit access only to the people who truly need it. Put all manual inputs (like targets, budgets, or date overrides) in a dedicated `Config` tab so they don’t interfere with calculations.
When pasting exports, always paste values only (`Ctrl+Shift+V` or `Edit → Paste special → Values only`) into clearly defined data ranges under the headers. If your sources frequently change their export layout, consider using named ranges or `INDEX(MATCH())` to locate columns by header name rather than fixed positions. Finally, version your template: keep a clean “master” file that you never overwrite with live data. When in doubt, copy the master, plug in fresh raw data, and only then share the working file with your team or client.
You have several options, from light to heavyweight. The lightest is using `IMPORTRANGE` to pull from a separate “data warehouse” Sheet where someone pastes exports; your client-facing template updates automatically whenever that source changes. For more automation, install a Google Sheets connector add-on from the Workspace Marketplace that can log into ad platforms and schedule data pulls directly into your `Raw_*` tabs.
Configure each connector to target a specific tab, time window, and set of metrics, and set refreshes to daily before your team starts work. Preserve your formulas and charts in the `Summary` tab so they recalculate on every refresh. If you need cross-tool automation, you can orchestrate this with no-code tools (like Zapier or Make) to trigger flows when new data appears. At the highest level of automation, a Simular AI agent can perform the entire ritual—opening ad accounts, exporting data, inserting it into Sheets, and even sending out updated report links—without requiring APIs, because it interacts with your tools like a human operator.
Treat the AI agent like a junior analyst who lives inside your computer. First, finalize your Google Sheets ads report template so the structure is stable: tabs, headers, formulas, and charts. Next, map out the step-by-step process you currently follow: which platforms you open, which filters you apply, how you export data, and exactly where you paste it in Sheets. Use that as the spec for your Simular AI agent.
In Simular Pro, you’d configure the agent to open your browser, navigate to each ad account, apply the date range, export or copy tables, then switch to your Google Sheet and paste data into the correct `Raw_*` tabs. With Simular’s transparent execution, you can watch the agent’s actions like a replay, tweak selectors or timings, and add guardrails (for example, verifying that total spend is within expected bounds). Once the run is reliable, schedule it daily or weekly and wire a webhook or email step so stakeholders get a fresh link and short summary. Over time, you can extend the playbook: multi-client loops, anomaly alerts, or pre-meeting report packs—all handled by the AI agent so your team can focus on strategy instead of spreadsheets.