How to Create an Income and Expense Report in Google Analytics with AI

Tracking your website’s income in Google Analytics is straightforward, but seeing the full picture - profitability - requires you to also pull in your expenses. That’s when things get complicated. This article will show you how to accurately create an income and expense report by combining your GA4 data with your advertising spend and how to use AI to build it instantly.

Why Your Google Analytics Data is Only Half the Story

Google Analytics 4 is a phenomenal tool for understanding what happens on your website. It can show you which traffic sources drive the most users, which pages are most engaging, and, if you have e-commerce tracking set up, exactly how much revenue each channel or campaign generates.

But here’s the problem: GA4 doesn’t know what you spent to get that traffic. It tracks revenue perfectly, but it has no native visibility into your ad costs from platforms like Facebook, Instagram, LinkedIn, TikTok, or even its own sibling, Google Ads.

This leaves a massive gap in your analysis. You might see a Facebook campaign generated $10,000 in revenue and assume it’s a roaring success. But if you spent $12,000 to run that campaign, you’re actually losing money. Without merging your income data with your expense data, you're flying blind, making budget decisions based on incomplete information.

The Manual Grind Most Marketers Endure

To get around this, most marketers fall into a painful, manual routine that looks something like this:

Monday morning: Log into Facebook Ads Manager. Set the date range for last week, export a CSV of campaign performance, focusing on the "Amount Spent" column.
Log into Google Ads. Repeat the process.
Log into LinkedIn Ads. Repeat the process.
Log into GA4. Navigate to the reports, filter for the same date range, and export a CSV of campaign revenue.
Open a new spreadsheet and start copying and pasting data from all those different CSV files, trying to line up campaign names and dates.
Spend the next hour wrestling with VLOOKUPs or SUMIFS formulas to stitch everything together into a single "income and expense" report.

By the time you’re done, half your morning is gone, and your report is already stale. This process is not only tedious but also incredibly vulnerable to human error. A simple copy-paste mistake can throw off your entire analysis.

How to Manually Create an Income & Expense Report: Step-by-Step

Before diving into a smarter solution, let’s quickly walk through the manual process. Understanding the old way helps clarify why the new way is so much better. At its core, the process involves two main data collection steps followed by a data-wrangling step.

Step 1: Get Your Income Data from Google Analytics 4

First, you need to pull your revenue numbers from GA4. Assuming you have e-commerce tracking correctly installed, this part is fairly easy.

Log in to your Google Analytics 4 property.
In the left-hand navigation menu, go to Reports → Monetization → E-commerce purchases.
Set the date range for the period you want to analyze (e.g., "Last 30 days").
The default view shows revenue by "Item name." To see revenue by traffic source or campaign, click the dropdown menu above the table (it says "Item name") and change the dimension to Session campaign or Session source / medium.
Click the "Share" icon (top right) and select Download File → Download CSV.

You now have a spreadsheet with your revenue broken down by campaign.

Step 2: Collect Expense Data from Your Ad Platforms

Now for the repetitive part. You need to pull your spending data from every advertising platform you use. Let's use Facebook Ads as an example, but the process is similar for others.

Log in to Meta Ads Manager.
Navigate to the "Campaigns" tab.
Make sure your columns are customized to show the key metrics you need. Ensure you have columns for Campaign Name and Amount Spent.
Set the date selector in the top-right corner to match the exact same date range you used in Google Analytics. This is crucial for an accurate comparison.
Click the Reports → Export Table Data… button and export the data as a .csv file.

Repeat this exact process for Google Ads, TikTok Ads, LinkedIn Ads, and any other platform where you spend money.

Step 3: Combine Everything in a Spreadsheet

With a folder full of CSVs, it’s time to bring it all together in Google Sheets or Excel.

Create a new spreadsheet and set up columns like: Campaign Name, Source, Ad Spend, Revenue, Sessions, and ROAS (Return on Ad Spend).
Open your exported ad platform CSVs one by one. Copy the Campaign Name and Amount Spent data and paste it into your master spreadsheet.
Open your exported GA4 revenue CSV. Copy the relevant columns (Session campaign, Total revenue, Sessions) and paste them into the master spreadsheet.
Now, you have to merge them. If your campaign names match exactly across platforms (a big "if" for many), you can use a formula like VLOOKUP to pull revenue numbers onto the same row as their corresponding ad spend.
Finally, add a formula for Return on Ad Spend in the ROAS column: (Revenue / Ad Spend).

You did it! You have a report. But it took 45 minutes, it’s already out of date, and if your boss asks a follow-up question like, "That's great, but can you show me this broken down by country?" you have to start the whole painful process from scratch.

The AI-Powered Way: Ditch the Spreadsheets for Natural Language

Instead of manually downloading and merging CSVs, modern AI-powered analytics tools can completely automate this process. They use direct API connections to pull data from all your sources - GA4, Facebook Ads, Google Ads, Shopify, etc. - and store it in one centralized place.

The real breakthrough is how you interact with that data. Instead of building reports by clicking and dragging in a complicated interface or writing spreadsheet formulas, you simply ask for what you want in plain English. The AI acts as your personal data analyst, building the report for you in seconds.

How it Works: A 3-Step Process

Putting AI to work on your income and expense report is monumentally easier than the manual alternative.

1. Connect Your Data Sources (Once)

The first and only setup step is connecting your accounts. You simply authenticate with Google Analytics, Google Ads, Meta, and other platforms you use. This takes a few clicks - no code or technical expertise required. The tool then syncs all your historical and ongoing data automatically, keeping it constantly up to date.

2. Ask for the Report You Want

With your data connected, you can now make requests. Your prompts don't need to be technical or perfectly worded. The AI is designed to understand human language, even if it's casual.

You could ask:

"Show me my ad spend versus revenue for the last 30 days"
"Build a chart that compares Facebook Ad costs to GA4 revenue by day"
"What was my total ROAS for all Google Ads campaigns last month?"
"Make a table showing cost, revenue, and profit for my Q2 campaigns"

The AI understands these requests, grabs the correct metrics from the right data sources (cost from your ad platforms, revenue from GA4), and instantly generates a professional, accurate visualization.

3. Dig Deeper with Follow-Up Questions

This is where the true power lies. An AI analytics tool enables a conversation with your data. Your initial visualization will likely spark new questions, and you can simply ask them.

Once you have your initial income vs. expense chart, you could ask:

"Which campaign had the highest profit?"
"Okay, now filter this for US traffic only."
"Why did spend spike last Tuesday?"
"Change this into a bar chart and organize it from high ROAS to low ROAS"

Each question allows you to drill down deeper, uncovering insights that would have taken hours of re-doing spreadsheets to find. Instead of stopping your analysis to wrangle more data, you can stay in the flow and follow your curiosity to its conclusion.

The Benefits of the AI Approach

Speed: Get answers in seconds, not hours. Free up your week for more strategic work instead of getting bogged down in manual reporting.
Accuracy: By eliminating manual data entry, you remove the risk of human error. Your reports are built on live, direct data from the source.
Real-Time Data: Your dashboards aren't static. They automatically update as new data comes in, so you're always making decisions based on the most current information available.
Accessibility: You don’t need to be a data expert to get mission-critical insights. Anyone on your team can ask questions and understand business performance, fostering a more data-driven culture.

Final Thoughts

Manually creating income and expense reports is an outdated-but-necessary evil for businesses trying to understand their marketing profitability. The process is slow, inefficient, and prone to costly mistakes. It consumes valuable time that could be better spent on strategy and execution rather than on spreadsheet gymnastics.

We built Graphed because we were tired of wrestling with that exact problem. Our platform connects all your disparate data sources like Google Analytics, Shopify, Facebook Ads, and Salesforce, and layers a conversational AI on top of it. This lets you ask simple, plain-English questions and get instant, live dashboards in return - no more exporting CSVs, no more tedious spreadsheet work. You just connect your data and start asking.