Product Pricing Test: +54.7% Profit Per Visitor Case Study

You might be underpriced. Most brands are.

We ran a pricing test for an 8-figure adult wellness brand. Two products, both priced at $99. The assumption was that the price was right.

We tested four price combinations. Lowering prices. Raising prices. Asymmetric pricing.

The winner? Raising Product A to $125 and adjusting Product B to $90.

Results: +54.7% profit per visitor. EST. +$40,573/mo.

They were leaving money on the table by not charging enough.

The Problem With Guessing at Price

Most brands set prices based on cost-plus, competitor matching, or gut feel. "This feels like a $99 product" becomes the price forever.

But price is the most powerful lever in ecommerce. A 10% price increase on the same volume is pure profit. A 10% conversion increase requires more traffic, more marketing, more work.

Without testing, you never know if you're priced right. You might be leaving margin on the table. You might be losing sales to price sensitivity. Only data tells you which.

The Hypothesis

Adjusting the prices of two of our products across four different price combinations will help us identify the optimal price pairing that maximizes overall revenue.

By finding a more value-aligned price point we expect to see an improvement in either average order value (AOV), profit per visitor, or both, while maintaining high conversion rates.

The goal wasn't just revenue. It was profit per visitor, the metric that accounts for both conversion and margin.

Test Setup

Component: Product Pricing
Location: Sitewide
Platform: Intelligems
Test Type: A/B/n with 5 variations

Control

Product A: $99
Product B: $99

Profit per Visitor: $0.44

Identical pricing. The baseline.

Variation 1: Lower Both

Product A: $50
Product B: $50

Profit per Visitor: $0.50

50% price cut. Testing if lower prices would drive enough volume to increase profit.

Variation 2: Slight Reduction

Product A: $90
Product B: $75

Profit per Visitor: $0.48

Modest decrease. Testing price sensitivity in the $75-90 range.

Variation 3: Premium Positioning (Winner)

Product A: $125
Product B: $90

Profit per Visitor: $0.68

26% increase on Product A. 9% decrease on Product B. Asymmetric premium strategy.

Variation 4: Full Premium

Product A: $125
Product B: $150

Profit per Visitor: $0.33

Both products at premium prices. Testing if the market would bear full premium positioning.

Results

Winner: Variation 3 (Product A $125, Product B $90)

Metric	Change
Profit per Visitor	+54.7%
Estimated Monthly Profit	+$40,573

Raising prices increased profit. Lowering prices didn't compensate with enough volume.

Why It Worked

1. They were underpriced, not overpriced

The instinct is usually "lower prices = more sales = more profit." Variation 1 tested that theory by cutting prices in half.

Result: profit per visitor only went from $0.44 to $0.50. A 50% price cut didn't double conversions. Not even close.

Meanwhile, Variation 3 raised prices and profit per visitor jumped to $0.68. The brand had pricing power they weren't using.

2. Asymmetric pricing created a strategic anchor

Variation 3 didn't raise both products equally. Product A went to $125. Product B went to $90.

This creates an anchor effect. Product A at $125 makes Product B at $90 look like good value. Customers who balk at $125 have a "reasonable" alternative.

Compare to Variation 4 where both were premium ($125 and $150). No relief valve. Profit per visitor dropped to $0.33, the worst performer.

3. Premium pricing signals premium quality

For intimate wellness products, customers want quality. They want products that work, last, and feel premium.

A $99 price might actually create doubt. "Is this good enough?" A $125 price signals confidence. "This is the best."

Price is a quality signal, especially in categories where customers can't easily compare products.

4. The right price isn't always the lowest price

Variation 1 (both at $50) barely beat the control ($0.50 vs $0.44). Half the price, marginally more profit per visitor.

That means conversion didn't increase enough to offset the margin loss. The demand curve wasn't elastic enough at this price point.

For premium products, there's often a floor below which lower prices don't help.

5. Variation 4 found the ceiling

At $125 and $150, profit per visitor dropped to $0.33. That's the price ceiling. Beyond it, conversion falls faster than margin rises.

The test found both the floor (Variation 1) and the ceiling (Variation 4). The optimal point was in between, but skewed toward premium.

What This Means for Pricing Strategy

You won't know your optimal price without testing. Assumptions aren't data.

Key principles:

• Test higher, not just lower: You might have more pricing power than you think
• Test asymmetric combinations: Different products can have different optimal prices
• Measure profit per visitor: Revenue alone doesn't account for margin
• Find floor and ceiling: Extreme variations tell you the boundaries
• Premium signals quality: In some categories, higher price increases perceived value

FAQ

Won't raising prices hurt conversion rate?

Sometimes. But profit per visitor accounts for that.

If conversion drops 10% but price increases 25%, you can still come out ahead. The test measures the net effect, not just one variable.

How long should pricing tests run?

Long enough to reach statistical significance. Usually 2-4 weeks minimum, depending on traffic.

Pricing tests need more data than UX tests because the effects can be smaller and more variable.

Should we test pricing on all products at once?

Start with your highest-volume products. They have the most impact and the fastest statistical significance.

Once you learn your customers' price sensitivity on key products, you can apply those learnings more broadly.

What about existing customers who remember old prices?

Price tests show new visitors different prices. Existing customers may see the control.

When you implement a price change, you can grandfather existing customers or simply accept that prices change over time. Most customers understand this.

Isn't price testing ethically questionable?

Price testing is standard practice in retail. Prices fluctuate constantly based on demand, competition, and strategy.

What matters is that all customers at any given time see legitimate prices for products they can purchase. Testing helps you find the right price; it doesn't deceive customers.

This test was run using Intelligems as part of a CONVERTIBLES personalization program. Want to see what pricing optimization could do for your store? Book a call to get 3 personalized recommendations for your store.