What We Learned Analyzing Shopify Stores with Product Bundle Affinity Analysis

Shopify Analytics

When we built our Shopify bundle analysis feature, we didn't expect to discover that most store owners were leaving 20-30% of their revenue on the table. But that's exactly what the data showed us.

I remember the first merchant who ran our product bundle affinity analysis on their store. Sarah owned a boutique wellness shop selling essential oils, diffusers, and natural skincare. She'd been manually creating product bundles based on what she thought made sense—lavender oil with sleep masks, citrus oils with energizing tea blends. Logical, right?

Wrong. Or at least, not optimal.

The Challenge: Intuition vs. Reality

Here's what we've learned after analyzing hundreds of Shopify stores: human intuition about product affinity is surprisingly unreliable. We think we know what customers want to buy together, but our assumptions are often based on product categories rather than actual purchasing behavior.

Sarah's data told a completely different story. Her customers who bought lavender essential oil weren't reaching for sleep masks—they were consistently adding eucalyptus oil and a specific carrier oil to their carts. The pattern repeated across dozens of orders, yet she'd never created a bundle for this combination because it didn't fit her mental model of "themed" products.

This is the fundamental problem we see again and again: merchants make bundling decisions based on product relationships that make sense on paper, while their customers are voting with their wallets for entirely different combinations.

What the Data Revealed

When we started digging into the order data from our early beta testers, patterns emerged that nobody expected. We built our analysis tool to calculate affinity scores—essentially, how often products appear together in orders compared to their individual purchase rates. The math is straightforward, but the insights were eye-opening.

One athletic apparel store discovered that their best-selling running shorts had the highest affinity not with running shirts (the obvious pairing), but with their mid-tier sports bras and a specific ankle compression sleeve. The store owner told me, "I would have bet money it was the performance tees. We've been bundling those together for two years."

A home goods merchant found that customers buying their premium coffee maker were also purchasing a specific brand of filters and a kitchen scale—not the coffee beans they'd been recommending. The affinity score for the scale was 0.67, meaning it appeared in 67% of orders containing that coffee maker. That's not a coincidence; that's a business opportunity.

We've seen this pattern across dozens of product categories: the bundles that make thematic sense aren't always the bundles that customers actually want.

The Surprising Insight

Here's where it gets interesting. After analyzing thousands of Shopify orders, we discovered something that changed how we think about product recommendations entirely: the strongest product affinities aren't always within the same category.

I'll give you a real example. A pet supply store was selling dog toys, treats, and grooming supplies. Their bundle strategy was straightforward—group similar items together. Toys with toys, treats with treats. Makes sense, right?

But the data showed something fascinating. Their highest-affinity product pair was a medium-sized rope toy and a specific dental treat. The affinity score was 0.71—massively high. When we dug deeper, we realized these were both items that appealed to owners of medium-sized, high-energy dogs. The connection wasn't about product category; it was about customer need.

This insight fundamentally shifted our approach to bundle analysis. We stopped thinking about "related products" and started thinking about "related customers." The question isn't "what products go together?" but rather "what products do the same customers need?"

Another merchant selling art supplies discovered that customers buying their premium watercolor sets were frequently also purchasing a specific sketchbook and masking fluid—items from completely different sections of their store. The connection? These were all tools that intermediate watercolor artists needed as they progressed in their practice. The merchant had been featuring their watercolor sets with brushes (logical), but the data suggested a "watercolor advancement kit" would resonate better.

Taking Action: From Data to Decisions

Understanding affinity is one thing; acting on it is another. We've worked with enough merchants now to see clear patterns in what works and what doesn't.

The most successful approach we've seen is what I call the "test and validate" cycle. Run the bundle affinity analysis, identify your top 3-5 unexpected pairings, create simple bundles for them, and track the results over 30 days. Don't overthink it—just test.

One merchant in our tutorials program did exactly this. They identified that customers buying their signature face cream had a 0.58 affinity score with a specific serum—higher than any other product pairing in their catalog. They created a "Complete Hydration Duo" bundle, priced it at a 12% discount, and featured it on both product pages.

Within two weeks, the bundle was generating 15% of their total revenue. More importantly, it increased the average order value for customers who had only intended to buy the face cream. The merchant told me, "I had that serum sitting in inventory for months. I thought it was a dud product. Turns out I just wasn't showing it to the right people at the right time."

The key is making it frictionless. When someone adds a high-affinity product to their cart, show them the companion product immediately. Don't bury it three clicks deep or make them hunt for it. Amazon figured this out years ago with "Frequently Bought Together"—the same principle applies to every Shopify store.

Results and Lessons Learned

After months of working with merchants running bundle affinity analysis, we've seen some consistent outcomes. Stores that implement data-driven bundles typically see:

But beyond the numbers, what I've found most valuable is the shift in mindset. Merchants who embrace data-driven bundling stop guessing and start knowing. They stop organizing their stores around categories and start organizing around customer behavior.

Sarah, the wellness shop owner I mentioned earlier, completely restructured her product recommendations based on affinity data. She told me last month that her store revenue is up 34% year-over-year, and she attributes a significant portion of that to smarter bundling. "I thought I knew my customers," she said. "Turns out, my data knew them better."

One lesson we learned the hard way: not all high-affinity pairings make good bundles. Sometimes products are purchased together because they serve complementary needs, but customers still want to buy them separately. We had one merchant who found that a specific phone case and screen protector had a 0.82 affinity score—incredibly high. But when they bundled them together, sales actually dropped. Customers wanted the flexibility to choose their screen protector separately.

The takeaway? Use affinity data to inform your bundling strategy, but always test and validate. Data tells you what's happening; you still need to understand why and decide how to act on it.

The Path Forward

If you're running a Shopify store and you haven't looked at your product affinity data, you're almost certainly leaving money on the table. The question isn't whether bundle opportunities exist in your store—they do. The question is whether you'll find them before your competitors do.

We built our bundle affinity analysis tool because we saw too many merchants making bundling decisions based on hunches rather than evidence. And honestly, we've been blown away by the results. Stores of all sizes—from solo founders to teams of 50+—are using affinity data to make smarter decisions about merchandising, marketing, and product development.

The best part? You don't need a data science degree to do this. The analysis takes minutes to run, and the insights are immediately actionable. Look for products with affinity scores above 0.4, test bundles featuring those pairings, and track what happens. Start small, validate quickly, and scale what works.

I've talked to merchants who thought bundle analysis was "too advanced" for their store, or that they needed thousands of orders before the data would be meaningful. Neither is true. Even stores with a few hundred orders can uncover valuable patterns. The key is looking at the data with fresh eyes and being willing to challenge your assumptions about what customers want.

Your Next Step

If you're curious about which products in your store have the strongest affinity, we've made it easy to find out. Our Product Bundle Affinity Analysis connects directly to your Shopify store and surfaces the highest-potential bundling opportunities in minutes.

You might discover, like Sarah did, that your best-selling product pairs perfectly with something you'd never considered. Or like the athletic apparel store, that your assumptions about "obvious" bundles are costing you sales. The only way to know is to look at the data.

Want to see what your customers are actually buying together? Try the analysis on your store and see which bundle opportunities you've been missing. I'd love to hear what you discover—some of the most surprising insights come from the stores we least expect.

Because at the end of the day, data-driven decisions aren't just about optimizing for revenue. They're about understanding your customers better, serving them more effectively, and building a store that grows sustainably. And that's worth far more than any individual bundle.

If you're just starting your ecommerce journey and want to learn more about turning data into actionable insights, check out our guide on growing from hobby to business—many of the same principles apply whether you're on Etsy or Shopify.