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How to Create a Monthly Report in Google Analytics with AI

Cody Schneider•

Building a monthly report in Google Analytics can feel like a necessary chore - you know the insights are in there, but digging them out involves endless clicks, multiple report exports, and a whole lot of spreadsheet wrangling. This article walks you through a smarter, faster way to get the answers you need from your GA data. We'll cover how you can leverage AI to turn hours of manual reporting into a simple conversation.

Why Your Monthly Google Analytics Report Matters

While dashboards give you a real-time pulse, a monthly report forces you to step back and look at the bigger picture. It's your opportunity to spot trends, understand performance against goals, and make informed decisions for the month ahead. A good monthly report answers critical business questions:

  • Are we growing? Where is that growth (or decline) coming from?

  • Which marketing channels are delivering the best ROI?

  • Is our new content resonating with our audience?

  • How are changes to the website impacting user behavior and conversions?

But creating this report traditionally comes with a cost - your time and sanity. Manually navigating GA4, pulling data from five different reports, and stitching it all together into a coherent summary is tedious. By the time you’ve built the report and answered follow-up questions from the team, half your week is gone, and the data is already stale.

The Old Way of GA Reporting: A Manual Grind

For years, the standard process for creating a monthly GA report looked something like this. If it feels painfully familiar, you're not alone.

Step 1: Go Data Mining Across Multiple Reports

You start by logging into Google Analytics and opening up several different tabs. You go to Reports > Acquisition > Traffic acquisition to see channel performance. Then you open Reports > Engagement > Pages and screens to find your top-performing content. Next, it's over to Reports > Monetization for revenue data or Reports > Engagement > Conversions for goal completions.

Step 2: Set Your Date Ranges (Again and Again)

In each of these reports, you have to manually set the date range to "Last month." To add context, you'll also use the "Compare" function to see how the data stacks up against the previous month or the same month last year. This simple step has to be repeated for every single report you look at.

Step 3: Export Everything to Spreadsheets

Once you have a view you need, you click "Share this report" > "Download File" and export it as a CSV or Google Sheet. You do this for your traffic acquisition report, your top pages report, your conversions report, and any other data you need. You now have a folder full of disconnected spreadsheets.

Step 4: The Spreadsheet Struggle

Now the "fun" begins. You consolidate all of these separate CSVs into one master spreadsheet. You copy and paste data, create summary tables, and build charts to visualize the performance of key metrics like sessions, engaged users, conversion rates, and revenue. If you want to show which channels drove traffic to your top pages, you have to perform VLOOKUPs or build pivot tables to merge the different datasets.

Step 5: Present Your Findings

Finally, you take screenshots of your charts and paste them into a slide deck or monthly email, adding your own written analysis to explain what the numbers actually mean. The report is finally done... until your manager asks a follow-up question like, "This is great, but can you drill down into organic search traffic from mobile devices?" and you have to dive back into GA and start the whole process over.

This entire process is slow, prone to error, and keeps you stuck reporting on the past instead of strategizing for the future. Fortunately, there's a much better way.

Using AI for Your Monthly Google Analytics Report

AI tools designed for data analysis completely change this workflow. Instead of acting as a manual "data puller," you become a "question asker." These tools connect directly to your Google Analytics account, giving them a deep understanding of your data structure without you ever having to look at an API schema.

Instead of clicking through menus and reports, you use plain-English prompts to ask for the data and visualizations you want to see. The AI handles all the work of querying the data, building the charts, and putting them into a unified, interactive dashboard for you.

A Step-by-Step Guide to Creating a GA Report with AI

Let's walk through how to build your comprehensive monthly report from scratch in minutes, not hours, just by asking questions.

Step 1: Connect Your Google Analytics Account

The first step is always to grant the AI reporting tool secure, read-only access to your Google Analytics data. This is typically done through a simple and secure OAuth process (the "Sign in with Google" flow you've seen countless times). There are no spreadsheets to upload or API keys to wrangle. You connect once, and the tool keeps your data synced in the background.

Step 2: Build Your High-Level Overview with Natural Language

Instead of manually hunting for metrics, start by asking for a broad overview of last month's performance. Focus your prompts on comparisons, which is where the best insights come from.

Try prompts like:

Create a dashboard showing my most important Google Analytics KPIs for last month. For each metric, compare it to the previous month and the same month last year.

This single prompt can instantly generate scorecards for key metrics like:

  • Total Users

  • Total Sessions

  • Engagement Rate

  • Total Conversions

  • Total Revenue

Each scorecard will automatically show the percentage change month-over-month (MoM) and year-over-year (YoY), giving you immediate context on performance.

Step 3: Dive Into Your Marketing Channels

Now, let's understand where your traffic and conversions are coming from. You don't need to find the Traffic Acquisition report, just tell the AI what you want to see.

Ask a question like:

Show me a breakdown of sessions by channel grouping for last month, and compare it to the previous month.

The AI will likely generate a bar chart or table showing your channels (Organic Search, Paid Search, Direct, Social, etc.) and their performance. Want to see conversion rates instead? Just ask.

Change that to show the user conversion rate by channel.

This conversational approach lets you refine your analysis on the fly, without needing to create a new report from scratch for every question.

Step 4: Analyze Your Content and Landing Pages

Next on your monthly reporting checklist is content performance. What blog posts, landing pages, or product pages are grabbing your audience's attention and driving results? Just ask.

Try prompts like:

  • What were my top 10 landing pages last month by total sessions?

  • Show me a table of my top blog posts ranked by total conversions.

  • Create a trend line of traffic to our new pricing page since it launched.

Step 5: Drill Down with Follow-Up Questions

This is where AI-driven reporting truly shines. When a chart raises a new question, you don't have to start over. You can simply ask a follow-up question to dig deeper into the data you're already looking at.

Imagine your bar chart from Step 3 showed a huge spike in Direct traffic. You can immediately investigate by asking:

Filter that chart to just show me the trend of Direct traffic over the last 90 days.

Or perhaps you see a blog post in your content report is driving a lot of traffic but few conversions. Your follow-up could be:

For the top blog post, show me the primary traffic sources bringing users to that URL.

This conversational drill-down allows you to follow your curiosity and uncover insights at the speed of thought. You get to the "why" behind the data in seconds, rather than getting stuck on the "how" of building the right report.

Step 6: Share Your Live, Interactive Report

Once you’ve built out charts that answer your core business questions, you can arrange them into a single dashboard. Unlike a static PDF or a slide deck, these dashboards are live. The data is pulled directly from Google Analytics in real-time, so it’s never stale.

You can securely share a link to this dashboard with stakeholders. They can explore the data, hover over charts to see more detail, and see the most up-to-date numbers whenever they open it. When they ask a follow-up question, you can simply add a new chart to the dashboard to answer it, turning your monthly report from a one-time handoff into an evolving source of truth for the entire team.

Final Thoughts

Your monthly Google Analytics report shouldn't be about proving you pulled the right KPIs. It should be about uncovering insights that help you grow your business. By shifting away from manual data exports and toward AI-powered analysis, you can spend less time wrangling data and more time understanding what it means.

With Graphed, we’ve made this process as simple as possible. After connecting your Google Analytics account in a few clicks, you can use natural language to build live, interactive dashboards that answer your most pressing marketing questions. Instead of getting stuck in reports, ask "Which campaigns are driving sales this month?" or "Why did our engagement rate drop last week?" and get immediate answers. This turns monthly reporting from a tedious, backward-looking chore into an ongoing, forward-looking conversation with your data.