You've finally migrated to GA4. Congratulations—you've traded Universal Analytics' familiar interface for something that looks like it was designed by engineers who've never actually had to explain conversion drops to a CEO on a Monday morning.
Here's the thing: GA4's standard reports are built for every business type imaginable, which means they're perfectly optimized for exactly nobody. E-commerce marketers end up clicking through seventeen screens to answer one simple question: "Why did revenue drop 15% last week?"
I've spent the better part of 2025 building custom dashboards for e-commerce clients who were ready to throw their laptops out the window. The good news? Once you set up the right custom reports, GA4 actually becomes useful. The bad news? You have to set them up first.
Let's fix your reporting situation.
Why GA4's Default E-commerce Reports Miss the Mark
GA4's standard e-commerce reports show you what happened. They're terrible at showing you why it happened or what to do about it.
You can see total revenue. Great. You can see transactions. Wonderful. But when your boss asks why the conversion rate dropped on mobile last Tuesday, you're stuck manually creating explorations and filtering six different dimensions while your coffee gets cold.
The default reports also lump together metrics that shouldn't live together. New customer revenue sits next to returning customer revenue like they're interchangeable. (They're not. A business that's 90% repeat customers has very different problems than one that's 90% new customers.)
Custom dashboards solve this by surfacing the specific metric combinations that actually inform decisions. Not every metric. The ones that matter.
Dashboard 1: Revenue Attribution Deep-Dive
This dashboard answers one critical question: Which channels are actually driving profitable customers?
Set this up with these components:
Primary Chart: Revenue by source/medium over the last 30 days, with comparison to previous period. Use a line graph so you can spot trends, not just totals.
Secondary Table: Break down by source/medium with these columns:
- Sessions
- Transactions
- Revenue
- Average order value
- Customer acquisition cost (if you're feeding ad spend data into GA4)
- Revenue per session
Here's what most marketers miss: Sort this table by revenue per session, not total revenue. That $50,000 from Google Ads looks impressive until you realize it took 100,000 sessions to generate it. Meanwhile, that email campaign generated $8,000 from 500 sessions.
The Filter That Changes Everything: Add a segment for "first-time purchasers" versus "returning purchasers." Your attribution picture probably just flipped upside down. Paid social might look mediocre for total revenue but exceptional for new customer acquisition. That's actionable intelligence.
I built this for an apparel client in October, and they immediately shifted 30% of their budget from channels that looked good on paper to channels that actually acquired profitable customers. Revenue per session became their north star metric instead of vanity traffic numbers.
Dashboard 2: Product Performance Intelligence
GA4's default product report shows you a list of products and revenue. Riveting stuff. About as useful as a weather report from last week.
Your custom product dashboard needs context:
Top Section: Your top 20 products by revenue with these metrics:
- Item revenue
- Items purchased
- Average price
- Cart-to-view rate (how many people who viewed it added it to cart)
- Purchase rate (how many viewers actually bought it)
Bottom Section: Your bottom 20 products by the same metrics.
Why look at your worst performers? Because sometimes a product with terrible revenue has an amazing cart-to-view rate but a pricing problem. Or a product getting tons of views but zero adds to cart has a presentation problem, not a demand problem.
The Unexpected Insight: Add a calculated metric for "revenue per product view." This tells you which products are efficient converters. A product with 1,000 views and $5,000 in revenue ($5 per view) is a better bet for promotion than one with 10,000 views and $8,000 in revenue ($0.80 per view).
Shopify merchants especially need this dashboard because their product catalog changes constantly. You need to know what's working right now, not last quarter.
Dashboard 3: Customer Journey Breakdown
Most e-commerce marketers are flying blind on the actual path customers take from first visit to purchase. GA4's default funnel exploration is fine if you want to spend 10 minutes setting it up every single time you need to check something.
Build a persistent dashboard instead:
Funnel Visualization: Set up a standard funnel with these steps:
- First visit (session_start event)
- Product view (view_item event)
- Add to cart (add_to_cart event)
- Begin checkout (begin_checkout event)
- Purchase (purchase event)
The Critical Addition: Create separate funnels for:
- Mobile vs. desktop vs. tablet
- New users vs. returning users
- Each major traffic source
You'll immediately spot where the bleeding happens. I guarantee your mobile checkout abandonment rate is worse than you think it is. (It always is.)
Bonus Metric: Calculate the time between first session and purchase for converting users. If your average is 8 days but your retargeting campaigns stop after 3 days, you're leaving money on the table.
One furniture retailer I worked with discovered their mobile funnel was fine until checkout, where they lost 68% of users. Desktop lost 42% at the same step. Same products, same prices, different experience. They fixed their mobile checkout flow and saw a 23% revenue increase in six weeks.
Dashboard 4: Real-Time Revenue Pulse
You're running a flash sale. Or it's Black Friday. Or you just sent an email to 100,000 people. You need to know what's happening right now, not after GA4's processing delay.
Your real-time dashboard should show:
Current Hour Metrics:
- Revenue (obviously)
- Transactions
- Active users
- Average order value
- Top 5 products being purchased
Comparison Metrics:
- Same hour yesterday
- Same hour last week
- Average for this hour over the last 30 days
Context matters. If you're seeing $5,000 in revenue and freaking out that it's low, but last Tuesday at 2pm you averaged $4,200, you're actually doing fine.
The Alert Setup: Configure GA4 to send you a Slack notification (yes, you can do this) when revenue in any 15-minute period drops below 50% of the average for that time period. Something's broken—your payment processor, your site, your checkout flow—and you need to know immediately.
Nothing says "fun Monday morning" like discovering your site was down for six hours over the weekend and nobody noticed. Ask me how I know.
Dashboard 5: Marketing Campaign Performance Grid
If you're running campaigns with UTM parameters (and you better be), you need a dashboard that shows you what's actually working without making you build custom reports every time.
Primary View: A table showing all campaigns from the last 30 days with:
- Campaign name
- Sessions
- New users
- Transactions
- Revenue
- Cost per acquisition (if you're importing cost data)
- Return on ad spend
The Filter Setup: Create dropdown filters for:
- Campaign source (Google, Facebook, email, etc.)
- Campaign medium (cpc, email, social, etc.)
- Date range (last 7 days, 30 days, 90 days, custom)
What Makes This Powerful: Add a calculated field for "revenue per new user acquired." This tells you the long-term value of each campaign's traffic, not just immediate returns. That awareness campaign that generated zero immediate sales but brought in 5,000 new users? Track those users' behavior over the next 90 days and you might discover it was your best campaign of the quarter.
BigCommerce and WooCommerce users often struggle with campaign attribution because their UTM parameters get stripped during checkout redirects. Make sure you're preserving those parameters through your entire funnel, or this dashboard will be useless.
Dashboard 6: Customer Retention & Repeat Purchase Analysis
Acquiring new customers is expensive. Getting existing customers to buy again is cheap. Yet most e-commerce dashboards obsess over acquisition metrics and ignore retention.
Your retention dashboard needs:
Cohort Analysis: Show revenue by customer cohort (month of first purchase) over time. You want to see if customers who first bought in January are still buying in June, July, August.
Repeat Purchase Metrics:
- Percentage of customers making 2+ purchases
- Percentage making 3+ purchases
- Average time between first and second purchase
- Average time between second and third purchase
- Customer lifetime value by cohort
The Insight Most Marketers Miss: Calculate your "repeat purchase rate" by month. If it's declining, your retention strategies aren't working. If it's increasing, double down on whatever you're doing.
I built this for a supplement brand that discovered their repeat purchase rate dropped from 34% to 19% over six months. They'd been so focused on acquiring new customers through paid ads that they'd stopped emailing existing customers. They rebuilt their email program and got repeat purchases back to 31% in three months. Much cheaper than buying more Facebook ads.
Dashboard 7: Site Search & Navigation Intelligence
If you're not tracking site search, you're ignoring your customers literally telling you what they want.
Your site search dashboard should include:
Search Terms Table:
- Search term
- Number of searches
- Percentage of searches that led to a product view
- Percentage that led to add-to-cart
- Percentage that led to purchase
- Revenue generated from each search term
The Gold Mine: Sort by "searches with zero results." These are people looking for products you don't carry (opportunity to expand) or products you DO carry but they can't find (your site search or navigation is broken).
Navigation Analysis: Track clicks on your main navigation menu items. Which categories get the most clicks? Which get ignored? Your navigation should reflect actual user behavior, not what you think makes sense.
One home goods retailer discovered that 847 people per month were searching for "outdoor pillows" with zero results. They carried outdoor pillows. They were just categorized under "outdoor furniture" instead of "pillows." They created a dedicated outdoor pillows category and saw $23,000 in additional monthly revenue from a change that took 20 minutes.
Actually Building These Dashboards (The Technical Bits)
GA4's interface for building custom reports is... let's say "non-intuitive." Here's the fastest path:
- Go to Explore in GA4 (not Reports)
- Start with a Blank exploration
- Add your dimensions and metrics in the Variables panel
- Drag them into your visualization
- Apply filters and segments
- Save it
- Go back to Reports → Library → Create new report
- Add your saved exploration to a custom dashboard
You can also use Looker Studio (formerly Data Studio) to build prettier dashboards with GA4 as the data source. The visualizations are better, but the setup takes longer. Your call.
The Automation Piece: Set up scheduled email delivery for your most important dashboards. Every Monday morning, your revenue attribution dashboard shows up in your inbox. You don't have to remember to check it. (You won't remember to check it.)
What These Dashboards Won't Fix
Look, custom dashboards make data accessible. They don't make bad strategy good.
If your site converts at 0.8% and your average order value is $23, no dashboard configuration will fix that. You have fundamental business problems that require actual solutions, not better reporting.
Dashboards also won't fix dirty data. If you're not tracking events properly, if your e-commerce integration is broken, if your UTM parameters are inconsistent, your dashboards will just surface garbage more efficiently.
And here's the thing nobody wants to hear: You still have to actually look at these dashboards and do something with the insights. I've seen companies spend weeks building beautiful dashboards that nobody opens after the first month. Set calendar reminders. Make dashboard review part of your Monday routine. Build it into your actual workflow.
Getting Started This Week
Don't try to build all seven dashboards at once. You'll get overwhelmed and quit.
Start with Dashboard 1 (Revenue Attribution). It's the most immediately useful and the easiest to build. Spend an hour on it this week.
Next week, add Dashboard 2 (Product Performance). Week after that, add Dashboard 3 (Customer Journey).
In a month, you'll have a reporting setup that actually helps you make decisions instead of just generating numbers that you nod at during meetings.
The goal isn't perfect dashboards. The goal is useful information that leads to better decisions. Start messy. Refine as you go.
Your future self—the one who can actually answer "Why did revenue drop last week?" in under 30 seconds—will thank you.
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