Real stores. Real before/after.

Specific numbers from specific stores. No "transformative partnerships," no rounded vanity metrics. Just what we found, what we changed, and how long it took.

Axel Offroad

Off-Road Helmets & Gear Mobile-Heavy (88% mobile) Shopify

The Pattern We Found

The site "worked." Pages loaded. Orders came in. The dev team said everything was fine. But mobile conversion was soft and nobody could explain why.

We were watching Clarity data weekly. Across four straight reporting periods, three signals kept moving together: JavaScript error rate sitting at 5 to 6%, dead clicks on the collection page at 4.6%, and quick backs at 15%. Most teams look at those as separate metrics. They're not. They're the same problem.

The JS errors were null reference failures in the product card initialization code: productelement.getattribute, addEventListener on null elements, "cannot read properties of null." On mobile, those errors were silently breaking interaction on the collection page. Users tapped products. Nothing happened. They tapped again. Nothing. They quick-backed to Instagram or Facebook and the session ended. From the dev team's desktop browser everything looked fine. On mobile, which is 88% of Axel's traffic, it wasn't.

The Fix

Targeted null check fixes on product card initialization. Guard the DOM access. Defer initialization until elements exist. Not a theme rebuild, not a re-platform. One dev cycle, scoped to the actual problem.

Then we deliberately waited a week before reporting. Clarity has a 4 to 5 day data lag, and we wanted to see whether dead clicks would fall in parallel with the JS error rate. If the two metrics moved together, that would confirm the causation we'd hypothesized. They did.

The Result · Technical (Apr 7 to 13 vs Mar 26 to Apr 2)

Metric Before After Change
JavaScript Error Rate 5.19% (peak: 5.77%) 1.74% −66% (−70% from peak)
Dead Clicks 4.63% 2.42% −48%
Quick Backs 14.97% 10.73% −28% (lowest ever recorded)
Performance Score 84/100 86/100 +2 (best ever recorded)
CLS 0.014 0.013 Best ever recorded

The Result · Revenue (Apr 1 to 13 vs Mar 1 to 13)

Metric Before (Mar 1 to 13) After (Apr 1 to 13) Change
Total Sales $68,865 $85,907 +30%
Net Sales $63,732 $80,534 +32%
Online Store Revenue (channel we manage) $35,725 $46,800 +31%
Online Store, Week-over-Week (post-fix) $19,900 $24,300 +22% in one week
Average Order Value $204 $237 +16%
Returns $5,162 $2,270 −56%

Timeline: Four weekly reporting periods of pattern detection → one dev cycle of targeted JS fixes → one week of post-fix data validation. The fix was small. Knowing where to point it took the analysis.

What This Actually Means

The lesson here isn't "JavaScript errors hurt revenue." Most $1M+ Shopify stores have JS errors firing somewhere, and most of them don't materially affect conversion. What mattered at Axel was that the errors were specifically breaking mobile interaction on the collection page, on a store where 88% of traffic is mobile. That's the pattern we look for: not "what's broken," but "what's broken in a way that's actually costing you."

The dev team wasn't bad. They just weren't looking at this layer of data. Most aren't.

TigerFriday

Performance Dancewear $1M to $5M Revenue Shopify

The Pattern We Found

TigerFriday's dancewear catalog was organized by product type instead of use case. Dance parents shopping for competition outfits had to mentally cross-reference leotards, skirts, and accessories across multiple categories. The premium line ($89+) sat next to basics ($29) with no visual or contextual differentiation, training shoppers to default to the lowest price point. Classic premium justification gap.

The Fix

Restructured collections around use cases: Competition, Training, Performance, Basics. Built comparison architecture for premium vs. standard lines showing material quality, durability, and feature differences. Added "Complete the Look" bundles that paired complementary items. Implemented smart upsell sequencing based on cart contents.

The Result

Metric Before After Change
Average Order Value Baseline n/a +35%
Premium Line Share Low Dominant Significant shift
Discount Dependency Heavy Minimal -50%

Timeline: Audit to results in 4 weeks

Sears · Enterprise Retail

Loyalty program architecture contributing to $12M impact. Engagement from a prior role. Details available on request.

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