Mapping Momentum: Doubling Conversions Through Data-Driven A/B Testing

Problem

OneApp, a technology platform helping renters navigate housing opportunities, faced the challenge of converting paid advertising traffic into completed Match Alpha experiences. While curiosity-driven creative successfully attracted prospective renters, initial engagement did not consistently translate into meaningful conversions, raising questions about whether the messaging communicated enough value to motivate action.

With customer acquisition costs and conversion efficiency critical to scaling the campaign, OneApp needed to determine whether a more personalized, benefit-driven approach could outperform traditional curiosity-based advertising. The challenge was not simply generating more clicks, but identifying which creative strategy attracted higher-intent users, increased completion rates, and delivered more cost-effective customer acquisition.

Solution

I developed an A/B testing strategy comparing two distinct creative approaches for OneApp's Match Alpha campaign.

Variant A: Curiosity (Control)

The original creative leveraged curiosity-based messaging to generate interest in exploring housing possibilities. Its primary objective was to attract clicks by creating intrigue around what users might discover.

Variant B: Odds on Map (Challenger)

The challenger creative introduced a more personalized, outcome-oriented approach, emphasizing the ability to visualize housing opportunities geographically. Rather than asking users to explore an unfamiliar experience, the messaging highlighted a concrete benefit: understanding their potential housing opportunities through an interactive map.

My hypothesis was that specific, visually compelling messaging focused on personalized outcomes would outperform curiosity-driven messaging by attracting users with stronger intent to complete the Match Alpha experience.

The experiment evaluated performance across three primary metrics:

• Completion Rate: Percentage of visitors who completed the Match Alpha experience.
• Cost per Acquisition (CPA): Advertising investment required to generate each completed experience.
• Conversion Volume: Total completed experiences attributed to each creative variation.

The testing strategy focused on identifying not simply which advertisement generated more clicks, but which message attracted users most likely to take meaningful action.

I analyzed conversion efficiency, acquisition costs, and completion volume to evaluate whether the challenger creative warranted broader adoption. The experiment reinforced the importance of optimizing campaigns for downstream business outcomes rather than superficial engagement metrics.

Skills Used:

• A/B Testing & Experiment Design
• Conversion Rate Optimization (CRO)
• Paid Media Strategy & Optimization
• Behavioral Psychology & Creative Testing
• Customer Acquisition Cost (CPA) Analysis
• Marketing Analytics & Performance Measurement
• Statistical Significance Testing

Results

108% INCREASE

IN CONVERSION RATE

(From 2.93% to 6.10%)

49.5% DECREASE

IN COST PER ACQUISITION

(From $43.60 to $22.00)

$22

COST PER ACQUISITION