How to Create a Work in Progress Report in Google Analytics with AI
A final report tells you what happened last month, but a work in progress (WIP) report tells you what’s happening right now. Knowing your campaign performance mid-flight is key to making smarter, faster adjustments instead of waiting until the budget is spent. This article will show you how to build a marketing WIP report in Google Analytics 4, first through the standard manual process and then through a much faster AI-powered approach.
What is a Work in Progress (WIP) Report for Marketing?
Think of a marketing WIP report as a live dashboard for your active campaigns and goals. It’s not a detailed, formal summary you present at the end of the quarter. It's a quick, real-time glance at the metrics that matter most to see if you’re on track. It's designed to answer questions that demand immediate attention:
"We launched a new social media campaign on Monday. Is it actually driving traffic and sign-ups today?"
"Are sales this month pacing to hit our target, or are we falling behind?"
"That new set of blog posts went live last week. Are people reading them, and are they converting?"
"I'm seeing a lot of traffic from our email newsletter, but is it leading to actual purchases?"
A good WIP report gives you the agility to react. If a campaign is underperforming, you can adjust your budget or creative before it’s too late. If a new content piece is taking off, you can double down on promoting it. Without a live view, you’re flying blind until you pull together a retroactive report, at which point the opportunity to optimize has already passed.
The Manual Method: Building a WIP Report in Google Analytics 4
Google Analytics 4 contains all the data you need for a WIP report, but finding it and stitching it together is a multi-step, manual process. It requires navigating different reports, applying filters, and mentally connecting the dots. It’s effective, but it pulls you away from deeper analysis. Let’s walk through a common scenario: checking the performance of a new content marketing campaign launched at the beginning of the month.
Step 1: Check High-Level Traffic Trends
First, you need to see if your overall traffic is moving in the right direction. Are more people visiting the site this month than last month at this time?
Navigate to Reports > Acquisition > Traffic acquisition.
Set the date range in the top right to your current WIP period, like "This month to date."
Review the charts for Users and Sessions. Look for any unusual spikes or dips that might correspond with your campaign launch.
Scan the table below the chart. Look at the Session default channel group column to see which channels (Organic Search, Direct, Paid Social, etc.) are driving the most traffic. Does this align with where you're promoting your new content?
This gives you a broad overview but doesn't tell you about your specific campaign's performance.
Step 2: Check for Goal Completions (Conversions)
Traffic is great, but a WIP report needs to track whether that traffic is translating into valuable business actions. In GA4, these are called Conversions.
Go to Reports > Engagement > Conversions.
Again, ensure your date range is set for the current period.
The table lists all your configured conversion events (e.g., 'generate_lead', 'purchase', 'trial_signup').
Look at the Conversions and Total users counts for each. Are the most important goals seeing an uptick since your campaign started? This view tells you what is happening but not why or from what sources.
Step 3: Analyze Specific Content Performance
Now, let's connect the dots and see if the new content pages are the ones driving traffic and conversions.
Navigate to Reports > Engagement > Landing page. The landing page report shows the first page a visitor saw during their session.
Use the search bar above the table to filter for your new content. For example, if all your new blog posts live in a /blog/ directory, you could search for "blog".
Look at the key columns for each of your new pages: Users, Sessions, Engagement rate, and Conversions.
This is where you finally get a direct answer: you can now see which new articles are attracting users and, more importantly, which ones are leading to them taking a desired action on your site.
The clear downside is how many clicks and screens this takes. You had a simple question - "is my new content working?" - and it required navigating three separate parts of the GA4 interface. If you have a follow-up question, you have to start the process all over again.
The AI-Powered Alternative: From Hours to Seconds
The manual process works, but it's slow and fragmented. The modern alternative bypasses menus and reports entirely, letting you interact with your Google Analytics data using plain English. Instead of a difficult-to-navigate software interface made for professional analysts, think of it as a conversational interface built for busy marketers and founders.
This approach solves the biggest challenge of data analysis: data literacy. You shouldn't need to know the specific name of a GA4 report or which dimensions and metrics to combine to get an answer. You just have to know what question to ask.
Asking Better Questions, Getting Faster Answers
Asking a question in natural language turns a multi-step research project into a single query. An AI data analyst understands what you mean, navigates the complexities of the data source on its own, and provides the answer, visualizing that answer so it’s easy to understand.
Let's reconsider the previous tasks, but this time asking an AI tool connected to your GA4 account.
Example 1: Checking Overall Campaign PerformanceInstead of clicking through the Traffic Acquisition report, setting date ranges, and adding filters, you can simply ask:
Show me users and conversions from our 'Summer Sale' campaign this month in GA4.
The AI will parse your request, query Google Analytics for the 'Summer Sale' campaign, pull user and conversion data for the current month, and generate a clear chart and table with the exact information you requested. The entire process takes seconds.
Example 2: Analyzing Content PerformanceRather than digging through the Landing Page report and manually filtering, just state what you want to know:
What are my top 5 blog posts by new users this week and how many sign-ups came from each?
It understands "blog posts" as pages, "new users" and "sign-ups" (a conversion event) as the metrics to pull, and delivers a clean summary table - no clicks required.
Example 3: Drilling Down with Follow-Up QuestionsThis is where an AI-powered process truly shines. Imagine your first query showed that Paid Search is driving a lot of traffic. Instead of starting over in the GA4 interface, you can simply ask a follow-up:
Okay, break that down and show me conversions by campaign for just Paid Search traffic.
The AI maintains the context of your conversation, allowing you to slice and dice the data dynamically until you uncover the key insight.
Turning Questions into a Live Dashboard
One-off questions are great for quick checks, but the ultimate goal of a WIP report is to have a centralized place to monitor performance without repeating yourself every day. With an AI tool, you can turn your series of questions into a live, self-updating dashboard.
The workflow looks completely different from the traditional dashboard-building process:
Connect Your Data: Start by connecting your Google Analytics account one time. No complex setup or API keys needed.
Build One Chart at a Time: Use simple, natural language prompts to create each component of your WIP report.
"Create a line chart of daily website sessions from the US this month."
"Add a bar chart showing conversions by marketing channel last 30 days."
"Add a table with the top 10 landing pages by user engagement."
Arrange Your Live Report: Drag and drop the charts you created into a layout that makes sense for you.
The result is a fully customized Work in Progress report that pulls live data directly from Google Analytics. You never have to manually update it again. Every time you view the dashboard, it shows you the very latest performance data, meaning your weekly check-in goes from a half-day of data wrangling to a five-minute glance.
Final Thoughts
Relying on end-of-month reports makes it impossible to be proactive. By building a simple work in progress report, you can gain immediate clarity on campaign performance and make data-informed decisions while there’s still time to impact the outcome. While you can manually assemble this intel in GA4, a conversational AI approach collapses the discovery process from minutes or hours into seconds.
At Graphed, we created this exact AI data analyst experience because we got tired of spending our days trapped in platform reporting tabs. After a one-click connection to sources like Google Analytics, you can ask for charts, reports, and dashboards in plain English. There’s no complex interface to learn, just a simple chat box that lets you go from a question to a real-time, shareable dashboard in less than a minute. You spend your time thinking about what insights mean for business performance, not battling menus and filters to find the data in the first place.