Shopify Analytics: What to Track, What to Ignore, and How to Set It Up

I am going to save you a lot of time with this article.

Most eCommerce founders I talk to are drowning in data and starving for insight. They have Shopify analytics, Google Analytics, Klaviyo analytics, Meta analytics, and maybe a couple of other dashboards — and they still cannot answer the basic question: "Is my business healthy and what should I do next?"

The problem isn't lack of data. It is too much data with no framework for knowing what matters.

Here is my framework. I am going to tell you the exact metrics to track, the ones to ignore, and how to set up your Shopify analytics so that finding answers takes 5 minutes instead of 5 hours.

The Metrics That Actually Matter

I am going to organize these into three tiers: daily checks, weekly reviews, and monthly deep dives.

Daily Checks (2 Minutes)

These are your vital signs. You glance at them every morning to make sure nothing is on fire.

Revenue. Total sales today compared to same day last week. Not compared to yesterday — day-of-week patterns matter. Tuesday revenue compared to last Tuesday gives you a real signal. Tuesday compared to Monday tells you nothing.

Orders. Number of orders today. Combined with revenue, this gives you your average order value without having to calculate it. 50 orders and $5,000 in revenue is a $100 AOV. You should know your baseline AOV by heart.

Conversion rate. Shopify shows this on the main dashboard. If your typical conversion rate is 2.5% and today it is 1.2%, something is wrong. A new bug, a broken checkout, a bad ad driving unqualified traffic. Catch it early.

Traffic. Total sessions today. A sudden drop means an ad got paused, a page broke, or something changed in your traffic sources. A sudden spike means an ad is spending fast, you went viral somewhere, or a press mention hit.

That is it for daily. Four numbers. Takes 90 seconds to check.

Weekly Reviews (15-20 Minutes)

This is where you make decisions. Every Monday, look at these:

Revenue by channel. How much came from organic search, paid social, paid search, email, direct, and referral? Is the mix healthy or are you over-dependent on one channel? If 70% of your revenue comes from Meta ads, you are one algorithm change away from a very bad month.

Customer acquisition cost (CAC). Total ad spend divided by new customer orders. Not total orders — new customer orders only. If you spent $10K on ads and got 200 new customers, your CAC is $50. Is that sustainable given your margins and LTV?

Email revenue percentage. What percentage of total revenue came from email and SMS? For healthy eCommerce brands, this should be 25-40%. Under 20% means your retention marketing is underbuilt. Over 50% means you are over-relying on your existing list and not acquiring enough new customers.

Top products by revenue. Are the same products always at the top? Or is there movement? A product suddenly jumping up means an ad or piece of content is working. A product dropping off might mean you are running low on inventory or the page has an issue.

Cart abandonment rate. Shopify tracks this. If it is above 70%, that is normal-ish for eCommerce but still worth investigating. If it spikes above 75-80%, something specific is causing people to bail at checkout.

Returning customer rate. What percentage of this week's orders came from repeat buyers? A healthy eCommerce business should see 25-40% returning customers. If it is below 20%, your retention marketing needs work. If it is above 50% and total revenue isn't growing, you aren't acquiring enough new customers to grow.

Monthly Deep Dives (60 Minutes)

Once a month, go deeper into the numbers that shape strategy.

Customer lifetime value (LTV). Shopify shows average order value, but you need to calculate LTV manually. Average order value multiplied by average number of orders per customer multiplied by average customer lifespan. Track this monthly and watch the trend. Rising LTV means your retention strategy is working. Declining LTV means customers are buying less or churning faster.

Cohort analysis. Group customers by the month they first purchased. Track each cohort's revenue over subsequent months. Are January customers still buying in April? Are they buying more or less than December customers did at the same point? Cohort analysis tells you if your customer quality is improving or declining over time.

Product page conversion rates. Look at individual product page conversion rates, not just overall store conversion. You will find some products converting at 5% and others at 0.5%. The low converters are either priced wrong, described poorly, or being shown to the wrong audience. Fix those and overall store conversion goes up.

Traffic quality by source. Compare conversion rates by traffic source. If Meta traffic converts at 1% while Google Shopping converts at 3%, you need to either improve your Meta landing pages or reconsider your Meta targeting. If email traffic converts at 8% (which is common), that tells you retention is your highest-quality channel.

Profit margin by product. Revenue is vanity. Profit is sanity. Track which products are actually making you money after COGS, shipping, and returns. Some of your "best sellers" might have the worst margins.

What to Ignore

Here is the part most analytics articles skip: the metrics that actively waste your time.

Sessions by page. Unless a page is broken, knowing that your "About Us" page got 500 visits last month tells you nothing actionable. What are you going to do with that information?

Bounce rate. Google Analytics bounce rate for eCommerce is misleading. Someone can land on a product page, read the description, add to cart, and check out — all in a single-page session that technically "bounced" from the landing page. Focus on conversion rate, not bounce rate.

Social media followers. This is a vanity metric that has nearly zero correlation with revenue. A brand with 5K engaged followers that buy regularly outperforms a brand with 500K followers that never purchase.

Time on site. More time on site is not inherently good. If someone spends 15 minutes on your site because they can't find what they want, that is bad. If someone finds their product in 90 seconds and checks out, that is great. Time on site without conversion context is meaningless.

Total email list size. A list of 100K that generates $10K per campaign is worse than a list of 20K that generates $15K per campaign. Revenue per recipient matters. List size alone does not.

How to Set Up Your Analytics Stack

Here is the technical setup that gives you everything you need without overcomplicating things.

Layer 1: Shopify Built-In Analytics

Shopify's native analytics are better than most people realize. For daily checks and basic weekly reviews, you don't need anything else.

Set up your Shopify dashboard to show: total sales, online store conversion rate, total orders, returning customer rate, and top products. Pin these to your main view.

Enable Shopify's marketing attribution. Go to Settings and then Marketing and make sure attribution is enabled. This gives you basic channel attribution directly in Shopify — no extra tools needed.

Layer 2: Google Analytics 4 (GA4)

GA4 is free and gives you things Shopify analytics can't: multi-touch attribution, user journey mapping, and cross-device tracking.

Set up GA4 properly. This means:

Install the GA4 tag via Google Tag Manager (not the native Shopify integration, which misses events). Set up enhanced eCommerce events: view_item, add_to_cart, begin_checkout, purchase. These events feed GA4's eCommerce reports and give you funnel visualization.

Create a proper conversion setup. Mark the purchase event as a key event (conversion) in GA4.

Set up audiences for retargeting. Create audiences for "added to cart but didn't purchase," "viewed product pages 3+ times," and "purchased in last 30 days." These feed your Google Ads retargeting.

The reports you actually need in GA4:

• Acquisition overview: Where traffic comes from and how each source converts
• User acquisition vs. Traffic acquisition: The difference between new user first touch and session-level source
• eCommerce purchase journey: The funnel from session to purchase, showing where people drop off
• Landing page report: Which pages people enter on and how those sessions convert

Layer 3: Klaviyo Dashboard

For email and SMS analytics, Klaviyo's built-in reporting is better than GA4's email attribution.

Key Klaviyo metrics to set up:

Revenue dashboards by flow and by campaign. Know which automated flows are driving the most revenue and which campaigns perform best.

Revenue per recipient (RPR). This is the metric that rules email marketing. More on this in other posts, but RPR tells you how much revenue you generate per email sent. It accounts for list size, engagement, and conversion in one number.

Deliverability dashboard. Inbox placement, bounce rate, spam complaints. If deliverability drops, nothing else matters because your emails aren't being seen.

Layer 4: A Simple Spreadsheet

This is where it all comes together. Create a Google Sheet with weekly data entry:

| Week | Revenue | Orders | AOV | New Customers | CAC | Email Revenue % | Conversion Rate | Blended ROAS | |---|---|---|---|---|---|---|---|---| | Jan 6 | $45,200 | 520 | $86.92 | 312 | $42 | 32% | 2.4% | 4.2x | | Jan 13 | $48,100 | 540 | $89.07 | 328 | $39 | 35% | 2.6% | 4.5x |

15 minutes every Monday to fill this in. Over time, you build a trend line that tells you exactly how your business is performing, what's improving, and what needs attention.

No fancy dashboard tool. No $500/month analytics platform. A spreadsheet updated weekly is more actionable than a real-time dashboard that nobody looks at.

The Common Setup Mistakes

Duplicate tracking. Running both the Shopify GA4 integration AND a manual GA4 tag through Google Tag Manager. This double-counts everything. Pick one method and stick with it.

Not filtering internal traffic. If your team visits the site regularly (which they do), your analytics are inflated by internal visits. Set up an IP filter in GA4 or use the Chrome extension to exclude internal traffic.

Wrong attribution settings. GA4 defaults to data-driven attribution, which distributes credit across touchpoints. This is better than last-click, but you should understand what model you are using and why. Go to Admin, then Attribution settings, and review.

Not connecting Shopify and GA4 properly. The purchase event in GA4 must match your Shopify revenue. If GA4 shows $40K and Shopify shows $50K for the same week, your tracking is leaking. Audit the connection.

Ignoring Shopify's built-in reports. People install expensive analytics tools and ignore the free reports Shopify already provides. Shopify's Sales by Channel, Sales by Product, and Customer Over Time reports are genuinely useful and accurate. Start there.

The Five-Minute Daily Routine

Here's exactly what to do every morning:

1. Open Shopify admin. Check today's sales, orders, and conversion rate vs. same day last week. (60 seconds)
2. Open Klaviyo dashboard. Check if any flows are underperforming or if there is a deliverability alert. (60 seconds)
3. Open your ad accounts. Check spend and blended ROAS for the day. (60 seconds)
4. Done. Go run your business.

Once a week, spend 15-20 minutes on the weekly metrics. Once a month, spend an hour going deep. That is all the analytics time you need.

The brands that are the most data-informed are not the ones with the most dashboards. They are the ones who know which 10 numbers matter and check them consistently.

If your analytics are a mess and you are not sure what you should be tracking, we set this up for eCommerce brands all the time.

Book a call and we will help you build an analytics setup that actually makes decisions easier.