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PureleiJewelry & Accessories DTC

How Purelei added €3.7M by scaling experimentation beyond internal capacity

Scaled experimentation beyond internal capacity. 32 experiments, 22 winners, and a 69% win rate for a €60M+ jewelry brand.

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Purelei
€3.7M€3.7M€3.7MAdditional revenue
Experiments
323232
Winning tests
222222
Win rate
69%69%69%
Annual brand revenue
€60M+€60M+€60M+

The short version

Purelei was already a €60M+ jewelry and accessories brand with strong aesthetic demand, frequent product drops, and a lean ecommerce team. The bottleneck was not brand desire. It was the lack of a structured research and testing engine that could separate high-value ideas from opinions. DRIP built that capability: research on why people bought, tests running in parallel, and a roadmap that re-ranked ideas after every result. Across 32 experiments, 22 became winners, creating a 69% win rate and €3.7M in additional revenue.

From research to the buying experience

Scaled experimentation proof

The testing engine produced €3.7M in additional revenue from 32 experiments and 22 winners.

Purelei experimentation impact chart

The starting point of Purelei

Purelei is a fast-growing German jewelry and accessories brand with a strong community, frequent collection launches, and a distinctive lifestyle identity inspired by Hawaii.

The brand had the kind of visual demand many ecommerce teams try to manufacture: shoppers were drawn to new drops, curated sets, gifts, advent calendars, and waterproof everyday jewelry. Style, novelty, progress and belonging came up again and again in the research.

That made the commercial question more specific: how much more revenue could Purelei capture if the buying experience matched the strength of the brand desire?

The challenge

Purelei had a lean internal team focused on trading, campaigns, products, and brand. CRO was valuable, but the team did not have enough bandwidth to run a high-quality research-to-test pipeline in-house.

The research showed a clear tension: aesthetic appeal and waterproof durability were strong buying motivations, but operational friction around delivery, returns, support, and decision overload could suppress conversion.

The page experience also carried a subtle risk. Premium jewelry shopping depends on focus, desire, trust, and gift confidence. Extra overlays, unclear checkout progress, or too many product-selection paths can reduce the very emotion that made visitors interested.

Our process

The work became a research-backed testing system that compounds.

DRIP's method in three steps, and what each step looked like at Purelei.

  1. Purelei driver profile visualization

    Step 1

    Research

    We studied why shoppers wanted Purelei before deciding what to test.

  2. Purelei protocol board

    Step 2

    Prediction & prioritization

    Each result sharpened the next roadmap decision.

  3. Purelei PLP simplification experiment visual

    Step 3

    Parallel testing

    Tests shipped where a lean team could get measurable leverage quickly.

Step 1

Research

We studied why shoppers wanted Purelei before deciding what to test.

DRIP's research combined driver scoring, feature extraction, buying motivations, and emotional journey analysis. The consistent pattern was clear: shoppers were pulled in by beauty, novelty, waterproof everyday use, and gifting, but they needed a calmer, more reliable path to purchase.

The best test ideas were not cosmetic. They protected aesthetic desire while reducing the operational doubts that made purchase feel risky.

Purelei driver profile visualization
Purelei feature ranking visualization

01

Mine customer language

Separate product desire from buying anxiety.

02

Score the drivers

Quantify which motives should shape hypotheses.

03

Define test surfaces

Map insights to PLP, bundle, checkout, and subscription tests.

Step 2

Prediction & prioritization

Each result sharpened the next roadmap decision.

Prioritization balanced revenue exposure, confidence from research, ease of implementation, and learnings from previous tests. That made the program practical for a team that could not afford a bloated experimentation process.

The win rate improved because ideas were filtered before they consumed traffic, design, or development time.

Purelei protocol board
Purelei impact chart

01

Score

Rank by evidence, reach, effort, and expected learning.

02

Sequence

Move from obvious friction to deeper behavioral tests.

03

Compound

Use each winner and loser to improve the next sprint.

Step 3

Parallel testing

Tests shipped where a lean team could get measurable leverage quickly.

The program focused on high-traffic surfaces and clear mechanisms: reducing PLP clutter, improving gifting decisions, clarifying checkout progress, and making curated offers easier to understand.

Velocity came from narrow hypotheses and strong design constraints, not from random design churn.

Purelei PLP simplification experiment visual
Purelei Birthday Box experiment visual

01

Brief

Tie every variant to a research-backed mechanism.

02

Ship

Keep implementation scoped enough for continuous testing.

03

Read

Measure ARPU, conversion, and segment behavior.

What the research found

DRIP's research separated what shoppers loved about Purelei from what made them hesitate. The strongest purchase motives were visual identity, waterproof durability, and gifting, while the strongest blockers were service, delivery, and return confidence.

#Purchase driverDriver scoreMentionsSentimentpositiveneutralnegative
1

Durability & Waterproofing

Product quality

Shoppers needed confidence that the jewelry would survive everyday wear and keep its finish.

Driver score95
Sentiment75% positive10% neutral15% negative
2

Aesthetic Appeal & Design

Status

The brand world and collection design created the initial emotional pull.

Driver score90
Sentiment70% positive15% neutral15% negative
3

Reliable Customer Service

Trust

A high-desire purchase still needed confidence that problems would be handled clearly.

Driver score80
Sentiment35% positive10% neutral55% negative
4

Gifting Experience

Economic

Curated gifts lowered choice overload and made the purchase easier to justify.

Driver score70
Sentiment72% positive18% neutral10% negative

What it meant for the roadmap

  1. 1

    Style, novelty and belonging created demand

    The brand had to stay expressive while choosing and checking out got simpler.

  2. 2

    Beauty attracted, everyday reliability justified the purchase

    Quality and gift value belonged closer to the decision points.

  3. 3

    Service, delivery and returns shaped trust

    The buying path had to create confidence without cluttering the aesthetic.

  4. 4

    Different customer groups needed different proof

    Novelty, durability, service and value mattered differently depending on expectations.

Current Purelei homepage screenshot captured from the live shop
Live shop, 2026The current Purelei experience is rich in campaign energy, category entry points, and gifting cues. The CRO opportunity was to preserve that desire while making the purchase path feel more reliable.

What the actual tests looked like

The real control, variant and result screenshots behind each test.

Test 1 of 3

Remove Quick Shop / Quick View Feature

The PLP quick-shop overlay looked convenient, but it competed with browsing and created shallow product decisions. Removing it simplified the grid and moved shoppers toward richer product detail pages.

Cluttered PLP overlay → cleaner product browsing and stronger PDP evaluation+2.5% ARPU
Purelei PLP simplification experiment visualization
Experiment visual

Test 2 of 3

Birthday Box Gift Bundle

A curated Birthday Box reduced gift assembly effort. Instead of asking shoppers to choose multiple separate products, the bundle framed the purchase as a complete, thoughtful gift.

Individual product assembly → curated gift bundle with stronger value perception+3.8% ARPU
Purelei Birthday Box experiment visualization
Experiment visual

Test 3 of 3

Checkout Progress Signaling

Checkout progress cues reduced uncertainty at a high-intent step and helped shoppers understand how close they were to completion.

Unclear checkout state → visible progress and lower completion anxietyHigher checkout completion confidence

Overall impact

Across 32 experiments, 22 produced statistically significant winners. That 69% win rate came from strong pre-test filtering: the team was not simply testing more, but testing ideas with better evidence.

The program generated €3.7M in additional revenue for Purelei while letting the internal team stay focused on brand, product, and trading priorities.

The deeper value was capability. Purelei gained a structured experimentation system without needing to build and manage a full internal CRO department.

The takeaway

Purelei shows that brand strength does not remove the need for CRO. It makes CRO more valuable because every hidden friction point taxes demand that already exists.

For visual, community-led brands, the best tests often protect emotion rather than stripping it away. The goal is not to make the shop feel generic. The goal is to make the next purchase decision feel obvious and safe.

DRIP and Apex

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