Experimentation & Testing

With today’s sophisticated marketing technology, informed decision-making has never been as achievable. We specialise in assisting with technical marketing experimentation and data analysis to optimise marketing operations and drive growth.

Whether you’re refining product features, enhancing user experiences, or improving campaign performance, we have the expertise to run experiments that yield actionable insights.

Types of Experiments

Our team designs and conducts a variety of experiment types based on your business goals. These include:

  • A/B Testing
    Compare two or more variations to identify the most effective approach.

  • Multivariate Testing
    Test multiple variables simultaneously to understand their combined impact.

  • Holdout Testing
    Establish control groups to measure the true incremental impact of your marketing efforts.

  • Sequential Testing
    Analyse performance over time for ongoing campaigns to ensure long-term effectiveness.

Hypothesis Development

A well-formulated hypothesis is the foundation of any successful experiment. We help you move from intuition to measurable assumptions. Our approach involves:

  • Identifying Business Objectives
    We start by understanding your strategic goals.

  • Formulating Clear, Testable Hypotheses
    Whether you’re looking to increase conversion rates or improve retention, we craft precise hypotheses that can be validated through data.

  • Defining Success Metrics
    We establish key performance indicators (KPIs) to measure the outcome of each hypothesis.

By focusing on hypotheses that matter to your business, we ensure that every experiment leads to meaningful insights.

Statistical Test Selection

Selecting the right statistical test is essential for valid results. Our team ensures rigorous statistical methods are applied, whether your data requires:

  • T-tests
    For comparing two independent groups.

  • ANOVA
    To evaluate the impact of multiple variables.

  • Chi-Square Tests
    When assessing categorical data relationships.

By aligning the statistical test with your business question, we deliver results you can trust.

Experiment Design

Designing a robust experiment is both an art and a science. We employ best practices in experimental design, ensuring that your tests are structured to produce clear, unbiased results. This includes:

  • Randomisation
    Ensuring that participant assignment or exposure is randomised to avoid selection bias.

  • Sample Size Determination
    Calculating the optimal sample size to ensure the results are statistically reliable.

  • Minimising Confounding Variables
    We help you control for variables that could distort the outcome.

Our goal is to create a controlled environment where you can confidently assess the effects of your interventions.

Experiment Execution

Once the experiment is designed, flawless execution is key. Our process includes:

  • Pre-launch Checks
    Rigorous testing of experiment infrastructure before launch.

  • Monitoring
    Continuous tracking of test progress to ensure no technical issues or unexpected anomalies affect the outcome.

  • Adjustment
    Based on real-time data, we make necessary adjustments to ensure validity and reliability.

We manage the full lifecycle of the experiment, allowing you to focus on strategy while we handle the details.

Experiment Interpretation

After the experiment concludes, we provide in-depth analysis and interpretation of the results. This involves:

  • Data Cleaning
    Ensuring data is free from errors or inconsistencies.

  • In-Depth Reporting
    Presenting clear, actionable insights with visualisations to support data-driven decisions.

  • Actionable Recommendations
    Providing practical guidance on how to implement findings into your marketing strategy.

We translate complex statistical outcomes into actionable business insights.

Get in touch with us to find out how we can help you reach the next level of optimisation.