What We Learned Analyzing 1M Shopify Orders Across CPG Brands

Introduction

When you spend your days helping CPG brands make sense of their data, you start seeing patterns. Not just within individual stores, but across them. The same mistakes show up again and again. So do the same signals that predict success.

Over the past year at Menza, we’ve analyzed more than one million orders across dozens of CPG brands selling consumables through Shopify. Food, beverage, supplements, personal care, pet products. Different categories, different price points, different customer bases. But underneath the surface, the data tells remarkably consistent stories.

Here’s what we learned.

Most Brands Overestimate Their Repeat Purchase Rate

Ask a founder what percentage of their customers come back for a second purchase, and they’ll usually guess somewhere between 40% and 60%. The actual number across our data set? Closer to 28%.

That’s not a typo. Across CPG brands selling consumable products (the kind you’d expect people to reorder), fewer than three in ten first-time buyers ever make a second purchase.

Some of this is unavoidable. Not every customer will love every product. Some people buy once as a gift. Some are deal-seekers who never intended to become regulars. But 28% is lower than it should be, and it points to a widespread problem: most brands focus relentlessly on acquisition while neglecting the post-purchase experience.

The brands in our data set with repeat rates above 40% shared a few common traits. They had robust email flows that stayed in touch after the first purchase. They sold products with natural replenishment cycles and timed their outreach accordingly. And they didn’t rely solely on discounts to drive the second order; they focused on reminding customers why they bought in the first place.

The Second Purchase Is the Hardest

We looked at cohort behavior across purchase milestones, and the data confirmed something intuitive: getting a customer from one purchase to two is the steepest hill to climb.

Among customers who made a second purchase, 58% went on to make a third. Among those who made a third, 67% made a fourth. The pattern continued: each subsequent purchase became more likely than the last.

This has major implications for where to focus retention efforts. If you’re treating all customers the same after their first order, you’re missing the most critical window. The period between purchase one and purchase two is when the relationship is most fragile. Customers haven’t formed a habit yet. They’re not loyal. They’re just trying you out.

The brands that understood this invested disproportionately in that window. More touchpoints, more education, more reasons to come back. Not aggressive discounting, but genuine engagement. Once a customer crossed the threshold into repeat buyer territory, the momentum often took care of itself.

Subscription Isn’t a Magic Fix

The conventional wisdom in DTC is that subscriptions solve retention. Get customers on a recurring order, and you’ve locked in lifetime value. The data tells a more complicated story.

Across our data set, subscription adoption rates varied widely, from under 5% to over 40% depending on the brand and category. But here’s what surprised us: subscription customers weren’t always the most valuable customers.

In some cases, subscribers had higher churn rates than we expected. They’d sign up for the discount, receive one or two shipments, and cancel. The upfront incentive attracted the wrong customers, people motivated by the deal rather than the product.

Meanwhile, some of the highest-LTV customers were non-subscribers who simply reordered manually when they ran out. They didn’t want a commitment. They just liked the product enough to come back.

The takeaway isn’t that subscriptions are bad. They work well for certain products and customer segments. But they’re not a substitute for building a product people actually want to repurchase. And the customers who choose to subscribe without a discount are often worth more than those who need one to commit.

Discounts Attract Different Customers

We segmented customers by how they were acquired: full price versus discounted first order. The behavioral differences were significant.

Customers acquired through discounts (welcome offers, sale campaigns, influencer codes) had an average repeat purchase rate 35% lower than customers who paid full price on their first order. Their average order value on subsequent purchases was also lower. And they were more likely to wait for another discount before ordering again.

None of this means you should never discount. Promotions have their place, especially for driving trial of new products or clearing inventory. But the data suggests that heavy discounting as a growth strategy has real costs that don’t show up in your acquisition metrics.

Some brands in our data set had started separating their analysis by acquisition type. They’d calculate LTV for full-price customers separately from discount-acquired customers and use those numbers to set different CAC targets. A customer acquired at full price might be worth $150 over their lifetime; a customer acquired through a 30% off promo might be worth $65. Those numbers should inform how much you’re willing to pay to acquire each type.

Product Breadth Matters Less Than Product Depth

We expected to find that brands with larger catalogs had higher average order values and better retention. They have more to offer, more reasons for customers to come back, more opportunities to cross-sell. Logical, right?

The data didn’t support it. Catalog size had almost no correlation with retention rate. Some of the highest-performing brands in our data set had fewer than ten SKUs. Some of the lowest performers had over a hundred.

What did correlate with retention was product depth within a customer’s chosen category. Brands that offered variations, sizes, flavors, and bundles within a focused product line saw better repeat behavior than brands that spread themselves across unrelated categories.

The pattern makes sense when you think about it from the customer’s perspective. If you love a brand’s coffee, you might want more coffee options: different roasts, different sizes, a subscription bundle. You probably don’t want protein bars or candles from the same brand. Depth signals expertise. Breadth can signal confusion!!

Shipping Thresholds Change Behavior

This one seems obvious, but the magnitude surprised us. Brands with free shipping thresholds saw measurably higher average order values than brands with flat-rate or fully free shipping.

The key was setting the threshold just above the natural AOV. If customers typically spend $40, a $50 free shipping threshold nudges them to add one more item. Too high (say, $75) and customers abandon the effort. Too low and you’re giving away shipping without getting anything in return.

We also saw that shipping threshold messaging mattered. Brands that surfaced the gap (“You’re $12 away from free shipping”) in the cart saw higher conversion rates than brands that only mentioned free shipping on the homepage or product pages.

Small optimizations, big impact. This is the kind of thing that shows up clearly when you’re looking at a million orders but might get lost in the noise of a single store’s data.

Returns Erode More Than Margin

Return rates across our CPG data set averaged around 6%, which is lower than apparel or electronics but higher than many brands assume. And the damage extends beyond the direct cost of refunds and reshipping.

Customers who return a product have a dramatically lower chance of repurchasing: around 12% versus 35% for customers whose first order went smoothly. Even if you refund them gracefully and offer a replacement, the relationship is often already broken.

The brands with the lowest return rates had invested in expectations management. Detailed product descriptions. Clear sizing or quantity guidance. Realistic photos. Reviews that mentioned potential downsides. They’d rather lose a borderline sale upfront than acquire a customer who’d be disappointed.

One brand in our data set cut their return rate in half by adding a simple FAQ to their product pages answering the three most common reasons for returns. The FAQ cost nothing to implement. The impact on profitability was significant.

Email Revenue Concentration Is a Risk

Across the brands we analyzed, email typically drove between 20% and 35% of total revenue. That’s healthy. What’s less healthy is how concentrated that revenue often is.

In many cases, a small number of campaigns drove the majority of email revenue. A Black Friday sale, a product launch, a big promotion. The flows (automated sequences) were either underdeveloped or underperforming.

This concentration creates volatility. If one big campaign underperforms, the month’s numbers suffer. It also means brands are leaving money on the table. Flows work in the background, capturing value consistently without requiring manual effort.

The brands with the most stable email revenue had the opposite pattern: flows drove 40% or more of total email revenue, with campaigns providing a lift on top. These brands weren’t sending more emails overall. They’d just built the infrastructure to capture revenue automatically at key moments in the customer journey.

What Separates the Top Performers

When we ranked brands by profitability and growth trajectory, a few factors kept showing up among the top performers.

They knew their numbers at a granular level. Not just total revenue and CAC, but profit margin by SKU, LTV by acquisition source, and repeat purchase rate by cohort. They’d done the work to understand what was really driving results.

They focused on retention before they scaled acquisition. Getting the post-purchase experience right meant every new customer was worth more. That gave them room to spend more on acquisition or pocket the margin.

They treated discounts as a tool, not a strategy. Promotions had a purpose: clear inventory, drive trial, reward loyal customers. They weren’t the default way to get anyone to buy anything.

They made decisions quickly based on data. Spotted a product with a high return rate? Fixed the issue within weeks, not months. Found a campaign acquiring low-quality customers? Cut it and reallocated the budget. Speed compounded into advantage.

A million orders taught us that the fundamentals matter more than the tactics. Get the product right. Acquire customers who actually want what you sell. Stay in touch after the first purchase. Measure what matters, not what’s easy. None of this is revolutionary. But the gap between knowing it and doing it is where most brands fall short.

The data doesn’t lie. It just waits for someone to ask the right questions.