Arpeely, ML media and UA platform

Arpeely is a leading platform in machine learning and algorithm-driven media and user acquisition. They specialize in optimizing advertising bidding and strategies to drive high-value traffic and engagement. Driven by a commitment to continuous improvement and innovation, Arpeely sought to refine their A/B testing approach, aiming to maximize the impact of their data-driven decisions.

Client

Arpeely

Challenge

Improve A/B testing methodologies for better and faster results

Solution

Comprehensive workshop on theoretical and practical aspects of A/B testing

Result

Improved testing capabilities, and better decision-making

Improve Testing Methodologies

Arpeely aimed to develop their A/B testing capabilities to the maximum. They sought external expertise to strengthen their testing practices, particularly in sequential testing, to enable faster, data-driven decisions.

Theoretical and Practical Workshop for Better A/B Testing

Foundational Principles

Importance of A/B testing, random sampling, hypothesis testing, understanding p-values, and confidence intervals.

Practical Challenges

Ensuring data trustworthiness, dealing with seasonality, and avoiding common pitfalls like peeking and early stopping.

Interactive Sessions

Detailed Q&A to address specific needs and challenges faced by Arpeely's team.

Improved A/B Testing Efficiency and Accuracy

Improved Testing Capabilities

Conducting more accurate and reliable tests.

Better Decision-Making

Enhanced ability to make better and faster data-driven decisions.

"The collaboration with Bell has been very beneficial for Arpeely. Their comprehensive workshop and support empowered our team to build a cutting-edge system, which enabled us to conduct more accurate and reliable tests and make faster data-driven decisions. We saw immediate improvements, which were impactful for our business."

Moran Cohen Koller, Director of Data, Arpeely