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How do you incorporate experimentation and A/B testing into growth marketing strategies?

Nash Haywood
Nash Haywood
Cloudflare Head of Digital Marketing | Formerly Gong, Genesys, Docebo, ESETSeptember 20

Incorporating experimentation and A/B testing into growth marketing strategies is key for driving sustained growth. Without it, marketing results often plateau quickly. Here’s a 6-step process I’ve used in the past to structure a conversion rate optimization program around.

Step 1 - Hypothesis Formation

In this initial step, pinpoint crucial variables that influence user engagement and construct hypotheses regarding potential changes and their outcomes.

  • Identify Key Variables: Recognize the key variables (like webpage layout, email subject lines, ad creatives) that you think have a significant impact on user engagement or conversion.

  • Develop Hypotheses: Formulate hypotheses based on your observations, analytics data, or customer feedback, predicting how changes in these variables might affect the outcomes.

Step 2 - Designing Experiments

Here, the focus is on developing different variants based on the formed hypotheses, establishing a control group, and setting up appropriate analytics tools to track the performance metrics accurately.

  • Creating & Develop Variants: Create different variants of the webpage, email, or ad, incorporating the changes as per your hypotheses.

  • Control Group: Maintain a control group where no changes are made, to compare the results with the variants.

  • Define Key Metrics: Set up key metrics (like click-through rate, conversion rate, etc.) that will help you evaluate the performance of each variant.

  • Setting Up Analytics: Ensure that analytics tools are set up correctly to accurately track the performance metrics.

Step 3 - Conducting Experiments

During this phase, conduct the experiments by segregating the audience into different groups and launching all variants simultaneously to avoid time-based biases, ensuring a fair test.

  • Randomized Split Testing: Divide the audience randomly into different groups, each group being exposed to one variant.

  • Simultaneous Launch: Launch all the variants simultaneously to prevent any time-based biases from affecting the results.

Step 4 - Data Collection and Analysis

This step entails meticulous data collection and analysis to discern the most effective variant, followed by deriving insights to comprehend customer preferences and documenting the findings for future reference.

  • Collect Data: Gather data on how each variant performed based on the defined metrics.

  • Analyze Results: Analyze the data to find out which variant performed the best and if the differences are statistically significant.

  • Draw Insights: Draw insights from the experiment results, understanding customer preferences and behaviors.

  • Document Learnings: Document the learnings from each experiment to build a knowledge base for future reference.

Step 5 - Implementation and Optimization

At this point, your focus is implement any successful test, engage in continuous optimization based on the learnings, and accelerate growth by repeating the testing process with new hypotheses.

  • Implement Changes: Implement the changes based on the winning variant to optimize your marketing strategies.

  • Continuous Optimization: Use the learnings to continuously optimize and improve your marketing strategies.

  • Scale Successful Experiments: Scale up the successful experiments to a larger audience to maximize the benefits.

  • Iterative Process: Make experimentation an iterative process, continuously testing new hypotheses to foster growth.

Step 6 - Knowledge Sharing

Lastly, foster a data-driven culture within the organization by sharing the learnings with the team, encouraging collaboration, innovation, and developing a flexible marketing strategy adaptable based on the insights gathered from the experiments.

  • Share Learnings: Share the learnings with your team to foster a culture of data-driven decision-making.

  • Collaborative Approach: Encourage a collaborative approach where team members can propose new hypotheses for testing.

  • Fostering Innovation: Foster a culture of experimentation within the organization, encouraging innovation and agility.

  • Adaptability: Develop an adaptable marketing strategy that can pivot based on the insights from the experiments.

By following this structured approach to experimentation and A/B testing, you can effectively incorporate them into your growth marketing strategies, driving improved results and fostering sustainable growth.

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Joann Guo
Joann Guo
Spotify Associate Director, Growth MarketingFebruary 29

We implement a quarterly planning cycle to structure our experimentation process effectively. This timeline allows us to conduct experiments that typically span over four weeks or more to ensure statistically significant results.

During the planning phase, we prioritize experiments based on their potential impact on our KPI. Simultaneously, we maintain a backlog of additional experiments to revisit when time and resources permit, ensuring a steady stream of optimization opportunities.

It's worth noting involving cross-functional teams early in this planning process is essential. This early involvement fosters a culture of experimentation and innovation across the organization, encouraging ownership and participation from all stakeholders.

However, not all experiments yield positive results, and that's okay. Don't be discouraged by setbacks but rather to view them as opportunities for learning. When experiments fail to produce the desired outcomes, try to understand the reasons why they failed and whether it's worth iterating. You can apply the three level of analysis when it comes to evaluating your experiment:

  1. Ask 'why' the experiment was a success/failure? What are the potential reasons.

  2. How 'accurate' were the results to your hypothesis? Close or really far off?

  3. Was the experiment a success or failure? Did it improve the metric in the hypothesis?

Sometimes, you may be surprised that there are more valuable insights gained from failed experiments than from successful ones because an experiment is only a failure if we fail to learn.

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Erika Barbosa
Erika Barbosa
Counterpart Marketing Lead | Formerly Issuu, OpenText, WebrootMay 25

The way I recommend incorporating experimentation and A/B testing into growth marketing is by making it an ingrained part of the strategy. One of the foundations of growth marketing is experimentation. Regardless of your go-to-market motion, industry, or goals, there is an opportunity for experimentation.

First and foremost, start with your goals and desired business outcomes. Then, think through the various opportunities for experiments throughout your strategies. You may find that this requires a bit of a mindset shift. In other words, just like reporting is a part of all strategies, experimentation should be too.

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