What We Learned Analyzing Squarespace Stores with SKU-Level Performance Analysis

Category: Squarespace Analytics | Published: January 15, 2025

The Challenge

We recently helped a customer who was struggling with which specific SKUs were driving sales and which should be discontinued. She ran a boutique home goods store on Squarespace—beautiful products, strong brand, loyal following. But when I asked her which products were actually making money, she paused.

"Well, the candles seem popular," she said. "And I think the ceramic mugs do well too?"

That "I think" is what got me. Here was someone who'd built a thriving business, but she was making critical inventory and purchasing decisions based on gut feeling rather than data. She couldn't tell me which SKUs were her top performers, which ones had the best margins, or which products were sitting in her storage unit collecting dust.

Sound familiar? I've talked to dozens of Squarespace merchants facing this exact problem. They know their overall sales numbers, but when it comes to product-level performance, they're flying blind.

What the Data Revealed

When we first ran our SKU performance analysis on her store, the results were eye-opening. We pulled every transaction from the past year and broke it down by individual SKU—total revenue, units sold, average order value, return rate, everything.

Within minutes, we had a complete picture of her product catalog's performance. And what we found surprised both of us.

Her "star performers" weren't what she thought. Those candles she mentioned? They accounted for about 15% of total revenue. Respectable, but nowhere near the top. The real winners were a set of hand-painted serving bowls that she'd almost discontinued because "they didn't seem to move."

Turns out, the serving bowls sold less frequently, but when they did, customers bought multiple sets. The average order value for those SKUs was 3x higher than her store average. They were quietly driving a massive chunk of her profit.

On the flip side, we discovered something even more valuable: the products that were actively hurting her business.

The Surprising Insight

Here's what nobody tells you about ecommerce: some products cost you money. Not because they don't sell, but because they sell just enough to keep you ordering inventory while barely covering their costs.

In her catalog, we found seven SKUs that fell into this category. They generated regular sales—enough to feel "successful"—but when we factored in storage costs, Squarespace transaction fees, and her time spent managing them, they were net negative.

The worst offender was a set of decorative coasters. Popular on Instagram, decent sales volume, but the margins were razor-thin. She was ordering new inventory every two months, paying for storage, and spending hours on customer service questions about them. When we calculated the true cost, she was losing about $300 per quarter on a product she thought was a "solid seller."

This is where automation opportunities become critical. Without automated SKU-level tracking, these profit drains are invisible. You see sales happening and assume you're winning. But the data tells a different story.

Taking Action

Once we had the full picture, the path forward became clear. We didn't just hand her a spreadsheet and wish her luck—we built an automated monitoring system that would keep her informed without requiring constant manual analysis.

First, we set up automated weekly reports that tracked her top 20 SKUs by revenue, units sold, and profit margin. No more guesswork about what was working. Every Monday morning, she'd get a snapshot of her product performance.

Second, we created alert triggers for underperforming SKUs. If a product hadn't sold in 60 days or if its return rate spiked above 10%, she'd get a notification. This turned reactive decision-making into proactive management.

Third—and this is where it gets really powerful—we integrated the SKU data with her cash flow analysis. She could see not just which products sold well, but when those sales converted to actual cash in her bank account. We used our Stripe payout timing analysis to map product sales to deposit dates, giving her a complete financial picture.

The immediate actions she took:

But here's what really changed: she stopped spending mental energy worrying about whether she was making the right inventory decisions. The data was there, updated automatically, telling her exactly what she needed to know.

Results and Lessons Learned

Three months after implementing SKU-level performance tracking, her metrics looked completely different:

But the biggest win wasn't the numbers—it was the confidence. She could now make decisions quickly because she trusted her data. When a supplier offered her a "great deal" on bulk inventory for a low-performing SKU, she declined in 30 seconds. Old her would have agonized over it for days.

When planning for the holiday season, she knew exactly which products to stock up on and which to keep minimal inventory for. No more over-ordering products that would sit around until January, no more running out of bestsellers mid-December.

What We Learned

After analyzing hundreds of Squarespace stores, I've seen this pattern repeat itself: merchants know they need better product-level insights, but they don't realize how transformative it can be until they actually have it.

The key lessons we keep coming back to:

1. Your intuition about product performance is probably wrong. I don't mean that as an insult—it's just human nature. We remember the recent wins, the products customers compliment, the items that look good on Instagram. But data doesn't have recency bias or aesthetic preferences. It tells you what's actually moving.

2. Automation isn't about replacing your judgment—it's about supporting it. Our customer didn't stop being involved in product decisions. She just stopped wasting time gathering data and started spending time acting on insights. The automation handled the tedious stuff so she could focus on strategy.

3. SKU-level analysis creates compound benefits. Better inventory decisions lead to better cash flow. Better cash flow leads to smarter purchasing. Smarter purchasing leads to higher margins. Higher margins give you room to experiment with new products. It's a virtuous cycle, but it starts with knowing your numbers.

4. The cost of bad data is invisible until you fix it. You don't know how much money you're leaving on the table until you stop leaving it there. Those seven money-losing SKUs? She'd been carrying them for over a year. Multiply small inefficiencies across time and they become significant drains.

Your Turn

If you're running a Squarespace store and you can't immediately answer these questions, you need SKU-level analysis:

We built our Squarespace SKU Performance Analysis tool specifically to answer these questions. It connects directly to your Squarespace store, pulls your transaction data, and breaks it down by individual SKU. You get the same insights we provided to the merchant in this story—except you can run it yourself, anytime, with fresh data.

The analysis takes about 30 seconds to run and gives you a complete breakdown of your product catalog's performance. No spreadsheets to build, no manual data entry, no SQL queries to write. Just connect your store and get answers.

Want to see what your top performers really are? Try the SKU Performance Analysis tool now. If you're curious about connecting your broader analytics infrastructure, check out our analytics services or watch a quick demo of the platform.

And if you're already using the analysis and find interesting insights in your data, I'd love to hear about them. Seriously—email me. These stories are how we learn what's actually working in the real world of ecommerce, and I'm always looking for the next surprising pattern hiding in the numbers.

Because at the end of the day, that's what this is all about: turning data into decisions, and decisions into growth. One SKU at a time.