As a marketing agency, delivering clear, insightful reports to clients is crucial for demonstrating your value and keeping them informed about their campaigns. While dedicated reporting software like Swydo offer robust features, Google Sheets can be a viable and cost-effective alternative for agencies just starting out or with limited reporting needs.
In this guide, we’ll walk you through creating a comprehensive monthly marketing report in Google Sheets, with sections for website analytics, PPC campaigns, and social media performance. We’ll cover the benefits and limitations of using Sheets for client reporting, and provide step-by-step instructions for importing data, analyzing it with formulas and pivot tables, and visualizing it with charts.
Why Use Google Sheets for Client Reporting?
There are several reasons why your agency might choose Google Sheets for reporting:
- Cost: Google Sheets is free, making it an attractive option for agencies on a tight budget.
- Familiarity: Many people are already comfortable with Google Sheets/Excel, reducing the learning curve.
- Customization: Sheets offers a blank slate that you can customize to match your agency’s branding and reporting style.
- Integration: Google Sheets can pull data directly from platforms like Google Analytics and Ads, making it easy to centralize your data.
- Collaboration: Sheets allows multiple team members to work on a report simultaneously and add comments for feedback.
However, there are also some limitations to consider:
- Manual setup: Building and formatting reports in Sheets can be time-consuming, especially compared to tools like Swydo that offer pre-built marketing templates.
- Lack of dynamic visuals: While you can create charts in Sheets, they aren’t as interactive or visually appealing as dedicated reporting dashboards.
- Limited data connectors: Sheets has built-in integrations with Google platforms, but connecting to other data sources often requires third-party add-ons or manual CSV exports.
- No automated insights: Swydo and other tools can flag significant changes in metrics and provide intelligent explanations. Sheets doesn’t have this extra layer of analysis.
So when does it make sense to use Google Sheets for reporting? It’s a good fit for agencies that:
- Are just starting out and need a low-cost solution
- Have relatively simple reporting needs
- Primarily use Google marketing platforms like Analytics, Ads, and Search Console
- Want more control over the structure and styling of their reports
On the other hand, agencies that work with enterprise clients, pull data from many disparate sources, or need to scale their reporting may outgrow Sheets and benefit from a more robust tool like Swydo.
How to Create Your Report in Google Sheets
Now, let’s dive into building a multi-channel marketing report step-by-step.
You can make copy of my Google Sheet Marketing Template and follow along
Step 1: Set Up Report Structure
Begin by creating a new Google Sheet and adding the following tabs:
- Report Summary
- Website Analytics
- PPC Campaigns
- Social Media
- Raw Data
- GA Raw Data
- Google Ads Raw Data
- Social Raw Data
Step 2: Import Data
Import your marketing data into the respective raw data tabs:
- Google Analytics data goes into the “GA Raw Data” tab
- Google Ads data goes into the “Google Ads Raw Data” tab
- Social media data goes into the “Social Raw Data” tab
Then, in the “Raw Data” tab, use formulas to reference and compile the data from the individual source tabs:
- For Google Analytics data:
='GA Raw Data'!A:G
- For Google Ads data:
='Google Ads Raw Data'!A:Q
- For Social media data:
='Social Raw Data'!A:E
This keeps your original data separate and untouched while still allowing you to centralize it for analysis.
Step 3: Analyze Website Analytics
Go to the “Website Analytics” tab.
Monthly Traffic Summary
Create a table to summarize key traffic metrics month-over-month. This allows you to quickly assess the overall health and growth of the website.
The formulas used are:
Metric | Jun-25 | Jul-25 | MoM % Change | |
---|---|---|---|---|
1 | Sessions | =SUMIF('GA Raw Data'!$A$2:$A, ">=2025-06-01", 'GA Raw Data'!$C$2:$C) | =SUMIF('GA Raw Data'!$A$2:$A, ">=2025-07-01", 'GA Raw Data'!$C$2:$C) | =(C2-B2)/B2 |
2 | Bounce Rate | =AVERAGEIF('GA Raw Data'!$A$2:$A, ">=2025-06-01", 'GA Raw Data'!$D$2:$D) | =AVERAGEIF('GA Raw Data'!$A$2:$A, ">=2025-07-01", 'GA Raw Data'!$D$2:$D) | =(C3-B3)/B3 |
3 | Avg. Session (sec) | =AVERAGEIF('GA Raw Data'!$A$2:$A, ">=2025-06-01", 'GA Raw Data'!$E$2:$E) | =AVERAGEIF('GA Raw Data'!$A$2:$A, ">=2025-07-01", 'GA Raw Data'!$E$2:$E) | =(C4-B4)/B4 |
Sessions by Channel Pie Chart
Create a breakdown of sessions by marketing channel to understand the main drivers of website traffic.
The formulas used are:
Channel | Sessions | |
---|---|---|
1 | Organic Search | =SUMIF('GA Raw Data'!$F$2:$F, "Organic Search", 'GA Raw Data'!$C$2:$C) |
2 | Paid Search | =SUMIF('GA Raw Data'!$F$2:$F, "Paid Search", 'GA Raw Data'!$C$2:$C) |
3 | Social | =SUMIF('GA Raw Data'!$F$2:$F, "Social", 'GA Raw Data'!$C$2:$C) |
4 | =SUMIF('GA Raw Data'!$F$2:$F, "Email", 'GA Raw Data'!$C$2:$C) | |
5 | Direct | =SUMIF('GA Raw Data'!$F$2:$F, "Direct", 'GA Raw Data'!$C$2:$C) |
To create pie chart:
- Select Channel and Sessions columns
- Click Insert -> Chart -> Pie chart
- Title “Sessions by Channel – July 2025”
- Customize design
Step 4: Analyze PPC Campaigns
Go to “PPC Campaigns” tab.
Campaign Performance Summary
Create a table summarizing the key metrics for each PPC campaign. This helps identify which campaigns are driving the most conversions at the lowest cost.
The formulas used are:
Campaign | Impressions | Clicks | CTR | Cost | Conversions | CPA | |
---|---|---|---|---|---|---|---|
1 | Brand | =SUMIF('Google Ads Raw Data'!$A$2:$A, A2, 'Google Ads Raw Data'!$C$2:$C) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A2, 'Google Ads Raw Data'!$D$2:$D) | =C2/B2 | =SUMIF('Google Ads Raw Data'!$A$2:$A, A2, 'Google Ads Raw Data'!$F$2:$F) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A2, 'Google Ads Raw Data'!$G$2:$G) | =E2/F2 |
2 | Non-Brand | =SUMIF('Google Ads Raw Data'!$A$2:$A, A3, 'Google Ads Raw Data'!$C$2:$C) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A3, 'Google Ads Raw Data'!$D$2:$D) | =C3/B3 | =SUMIF('Google Ads Raw Data'!$A$2:$A, A3, 'Google Ads Raw Data'!$F$2:$F) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A3, 'Google Ads Raw Data'!$G$2:$G) | =E3/F3 |
3 | Remarketing | =SUMIF('Google Ads Raw Data'!$A$2:$A, A4, 'Google Ads Raw Data'!$C$2:$C) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A4, 'Google Ads Raw Data'!$D$2:$D) | =C4/B4 | =SUMIF('Google Ads Raw Data'!$A$2:$A, A4, 'Google Ads Raw Data'!$F$2:$F) | =SUMIF('Google Ads Raw Data'!$A$2:$A, A4, 'Google Ads Raw Data'!$G$2:$G) | =E4/F4 |
Cost Per Acquisition Chart
To visualize CPA by campaign:
- Select Campaign and CPA columns
- Click Insert -> Chart -> Column chart
- Title “Cost Per Acquisition by Campaign”
- Customize style
Step 5: Analyze Social Media
Navigate to “Social Media” tab.
Monthly Summary Metrics
Create a table summarizing the key social media metrics month-over-month. This provides a high-level view of follower growth and engagement.
Most metrics, like Followers and Impressions, come directly from the platform. But some, like Engagement Rate, are calculated from the raw data.
The formulas used are:
Metric | Jun 2025 | Jul 2025 | MoM % Change | |
---|---|---|---|---|
1 | Followers | ='Social Raw Data'!C24 | ='Social Raw Data'!C25 | =(C2-B2)/B2 |
2 | Avg. Post Impressions | =AVERAGE('Social Raw Data'!C2:C7) | =AVERAGE('Social Raw Data'!C8:C13) | =(C3-B3)/B3 |
3 | Avg. Engagement Rate | =(SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$C$2:$C$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$C$2:$C$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$C$2:$C$7)) / (SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$E$2:$E$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$E$2:$E$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$E$2:$E$7) | =(SUMIF('Social Raw Data'!$B$8:$B$13, "Video", 'Social Raw Data'!$C$8:$C$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Image", 'Social Raw Data'!$C$8:$C$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Link", 'Social Raw Data'!$C$8:$C$13)) / (SUMIF('Social Raw Data'!$B$8:$B$13, "Video", 'Social Raw Data'!$D$8:$D$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Image", 'Social Raw Data'!$D$8:$D$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Link", 'Social Raw Data'!$D$8:$D$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Video", 'Social Raw Data'!$E$8:$E$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Image", 'Social Raw Data'!$E$8:$E$13) + SUMIF('Social Raw Data'!$B$8:$B$13, "Link", 'Social Raw Data'!$E$8:$E$13) | =(C4-B4)/B4 |
Engagement by Post Type
Use a pivot table to analyze average engagement metrics by post type. This helps identify which content formats resonate most with the audience.
- Create a pivot table with Post Type as Rows and Likes, Comments, Shares as Values
- Rename the values to “Avg. Likes”, “Avg. Comments”, “Avg. Shares”
- Sort the rows by Total Engagements descending
Post Type | Avg. Likes | Avg. Comments | Avg. Shares | Total Engagements | |
---|---|---|---|---|---|
5 | Video | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$C$2:$C$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$D$2:$D$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$E$2:$E$7) | =SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$C$2:$C$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Video", 'Social Raw Data'!$E$2:$E$7) |
6 | Image | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$C$2:$C$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$D$2:$D$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$E$2:$E$7) | =SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$C$2:$C$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Image", 'Social Raw Data'!$E$2:$E$7) |
7 | Link | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$C$2:$C$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$D$2:$D$7) | =AVERAGEIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$E$2:$E$7) | =SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$C$2:$C$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$D$2:$D$7) + SUMIF('Social Raw Data'!$B$2:$B$7, "Link", 'Social Raw Data'!$E$2:$E$7) |
To create chart:
- Select pivot table data
- Insert -> Chart -> Column
- Title “Average Engagements by Post Type”
- Customize design
Step 6: Build Executive Summary
In the “Report Summary” tab, provide a high-level overview of the key insights from each channel:
- Website traffic increased 18.1% MoM, driven by organic search (+20%) and paid search (+15%)
- PPC CPA varied significantly by campaign type, with Brand at $5, Non-Brand at $15, and Remarketing at $3.14
- Social media followers grew 13% MoM, with video posts driving the highest engagement rates
Copy and paste the most important charts from the other tabs into the summary to create a visual dashboard. Add a heading with the reporting month (e.g. “July 2025 Marketing Report”).
Step 7: Automate Data Refresh
To automate data refreshes and streamline your reporting process, you can either use Google Apps Script or explore Google Sheets extensions that allow for easy data export and import.
Option 1: Google Apps Script
Create custom functions with Google Apps Script to pull data from platforms like Google Analytics, Google Ads, and social media. Set up these functions to run on a schedule, such as weekly, to automatically update your report. The script runs on its own, pulling the latest data and saving time on manual updates. Once set up, you no longer need to worry about keeping your data fresh because the script takes care of it automatically.
Option 2: Extensions for Data Export/Import
If you prefer not to write code, Google Sheets extensions offer a quick and easy way to import and export data from various platforms. These extensions connect directly to services like Google Analytics and Google Ads, pulling the data you need without needing to manually download or upload anything.
Popular options include:
- Supermetrics: Connects Google Sheets to multiple marketing platforms, automating data imports with minimal effort.
- Data Connector for Google Analytics: A straightforward extension that brings Google Analytics data directly into Sheets, making it easy to manage your report.
- Zapier or Integromat: Integrates Google Sheets with other apps, automating the process of importing and exporting data across platforms.
Choose the solution that works best for you. Whether you go with Apps Script or use an extension, both options help you automate data refreshes and focus more on the insights and analysis that matter most to your clients.
How to Use Google Sheets Reports into Swydo
After you’ve created your Google Sheets report, you can easily integrate the data and analysis into Swydo. Swydo allows you to link your Google Sheets directly, so any tables or data analysis you’ve prepared in Sheets can be fetched and included in your client reports. The Google Sheet integration makes it easy to manage all your client’s data in one place, saving you time and ensuring the information is automatically updated without needing to duplicate work.
If you’re using Zapier, you can automate data transfers from Google Sheets to Swydo, further streamlining the process. Whether you’re updating website analytics, PPC campaigns, or social media data, Swydo can fetch the latest data from your Sheets and include it in your custom reports, ensuring your clients always have access to the most current insights.
Conclusion
Using Google Sheets, you can build robust multi-channel reports to keep clients informed. Key principles:
- Store raw data in separate tabs, reference in master “Raw Data” tab
- Use SUMIF and pivot tables to slice data
- Visualize KPIs with clear charts
- Provide insights to interpret the numbers
- Automate data imports with Apps Script or Extensions
While Sheets has limitations vs BI and client reporting tools, it’s a solid option for lean agencies. Focus metrics on client goals, spotlight key trends, and translate data into an engaging story. With practice, you’ll build reports that showcase your value and wow clients.
Ready to streamline your client reporting? Swydo offers easy automation and powerful data integrations.
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