CarParts Unlocked $1MM in 90 Days

How strategic experimentation for CarParts.com unlocked nearly $1MM in additional revenue in just 90 days

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CarParts.com came to LXRInsights with a familiar challenge facing many large ecommerce brands: significant scale, substantial media investment, and opportunities hidden within millions of customer interactions, product listings, and campaign signals.

The opportunity was not a lack of demand. The opportunity was identifying where performance could be improved, where budgets could be reallocated, and where experimentation could unlock incremental growth.

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Starting With the Audit

The engagement began with a comprehensive audit of paid media performance, product catalogs, audience behavior, geographic demand, and conversion trends.

The review uncovered several areas for optimization:

• A small percentage of campaigns were driving a disproportionate share of performance.
• More than 70% of Performance Max campaigns were generating traffic below account efficiency benchmarks.
• A meaningful percentage of product catalog spend was concentrated on SKUs producing little or no revenue contribution.
• Revenue was concentrated in a small group of regions despite strong performance indicators across additional markets.
• Conversion rates were declining across major product categories despite increasing investment.

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These findings became the foundation for experimentation.

Building Experiments Around Revenue Opportunities

Rather than making broad account changes, the team developed a series of focused experiments designed to isolate specific opportunities and measure impact.

Product Bundling & Average Order Value

The first opportunity centered on increasing customer value through smarter product combinations.

Using product-level analysis and audience intelligence, the team identified opportunities to bundle complementary products and improve average order value while maintaining conversion efficiency.

High-Intent Audience Acquisition

Audience analysis revealed an opportunity to focus on customers demonstrating stronger purchase intent.

The experiment leveraged LXRInsights audience segmentation and predictive signals to prioritize shoppers with behavioral patterns closely aligned to existing high-value customers.

SKU Optimization

Product catalog analysis surfaced opportunities to improve efficiency by prioritizing higher-performing inventory while reducing investment behind lower-contributing products.

The experiment focused on refining product groupings, audience alignment, and merchandising strategy to improve conversion performance and overall return.

Geographic Expansion

Regional performance data showed that revenue was concentrated within a relatively small percentage of markets, while many additional regions demonstrated strong demand indicators.

Using demographic and behavioral data, the team identified high-potential regions for expanded investment and testing.

Conversion Window Optimization

Customer behavior analysis revealed opportunities to align audience timing more closely with purchase intent.

Experiments focused on refining audience windows, improving relevance, and reaching customers closer to the point of purchase.

The Outcome

The experimentation program transformed insights into action.

Across multiple tests, CarParts.com gained a clearer understanding of:

• Which audiences generated the strongest returns
• Which products deserved additional investment
• Which regions offered untapped growth potential
• How customer timing influenced conversion behavior
• Where budget could be deployed more efficiently

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More importantly, the organization established a repeatable framework for identifying opportunities, launching experiments, measuring outcomes, and scaling what worked.

Why Experimentation Matters

Every large ecommerce brand has growth opportunities hidden within its data.

The challenge is determining which opportunities deserve attention first.

For CarParts.com, experimentation provided a structured approach for validating hypotheses, reducing risk, and making investment decisions with greater confidence.

Instead of relying on assumptions, each decision was backed by measurable outcomes.

The result was a stronger foundation for continuous optimization, smarter budget allocation, and long-term growth driven by data rather than guesswork.

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