"Start testing, stop guessing" is Relevant Digital's motto, as our experts continue to encourage multivariate testing in ad monetisation among publishers and programmatic networks. Although it's not a new concept, it doesn't seem to receive as much attention as it should.

Understanding Multivariate Testing

By definition, multivariate testing is a technique for testing a hypothesis in which multiple variables are modified. The goal of multivariate testing is to determine which combination of variations performs the best out of all of the possible combinations (Optimizely).

Multivariate testing is a critical component of advertising operations that helps publishers make data-driven decisions on investment and strategy. In whatever economic climate, testing is used not only for optimisation but also for cost savings. 

The Cost of Not Testing

The lack of testing can have significant consequences for businesses, including missed opportunities for growth, ineffective campaigns, waste of resources, low-quality user experiences, and an inability to adapt. Programmatic is a fast-paced market with constant changes, publishers need a proactive approach to testing in order to not fall behind.

Benefits of Multivariate Testing

The possibility of multivariate testing is limitless. Besides growing ad revenue sustainably, it also minimises loss for publishers by providing accurate data. Below are some key aspects where publishers will see improvement by conducting proper testing.

• Ad revenue: by testing various metrics like geo, formats, floor prices, and different ad placements, etc, publishers can determine the optimal configurations for their inventory to maximise CTR and obtain high CPMs.
• User engagement & experience: testing can help publishers optimise the layout, content, and design of their website to ensure user satisfaction and engagement. This results in increased page views, higher viewability, and reduced bounce rates, which drives more ad revenue and reduces the cost of acquisition.
• Data-driven decision-making: testing provides publishers with data-driven insights into what works and what doesn't, allowing them to make informed decisions with calculated risks.
• Competitiveness: by continuously improving their website with data from tests, publishers can stay ahead of the competition and maintain their position as a leader in their industry.

Effective Practices in Multivariate Testing

To make the most out of multivariate testing and avoid wasting resources, these practices should be followed:

• Define clear goals: define the goals and objectives to determine what elements to test and what metrics to track. 
• Choose the right sample size: select an appropriate sample size for the tests, taking into account the website traffic and target audience.
• Monitor and organise the data: to avoid confusion and accurately interpret results, publishers should have the performance analytics in one place but with different segments/categories.
• Analyse data and make decisions based on it: analyse the data based on the dimensions and metrics that have been set out to make decisions.
• Continuously test and optimise: more tests equal more data to securely better the stack's profitability and optimise operations.

Challenges and Solutions in Multivariate Testing

Many publishers and programmatic networks face obstacles that prevent them from experimenting. For some, limited resources, technical barriers, lack of knowledge, and data privacy concerns are hard to overcome. To tackle these challenges, publishers need a straightforward testing process and to use the right tool. A combination of these two will result in high ROI.

Right now, AI seems to be a great help! It significantly reduces the complexity of data analysis and decision-making. Imagine this: once your test variations are set up and live, all performance analytics are logged in real-time for your monitoring. Then, there’s an AI assistant swiftly analysing all the data and suggesting optimisation tweaks. How much time and headache would that save you? 

That’s why Relevant Yield integrates AI and offers a user-friendly management UI to help publishers accelerate the testing process and reduce reliance on technical staff. This integration of AI removes the burden of complex data analysis, allowing programmatic experts to focus on strategic decision-making rather than technical intricacies. With its user-friendly management UI, Relevant Yield empowers your team to conduct sophisticated tests with ease, significantly reducing the dependency on specialised technical staff and making advanced testing accessible to all team members. This shift not only accelerates the testing cycle but also places the control directly in the hands of those with the expertise to use it most effectively.

Conclusion

While challenges like resource limitations and technical constraints exist, the advantages of multivariate testing are undeniable. It plays a pivotal role in informed decision-making, enhancing user experience, boosting ad revenue, and maintaining a competitive edge. Publishers equipped with efficient tools like Relevant Yield and its AI capabilities are well-positioned for success, turning potential setbacks into opportunities for growth and innovation.

Streamline your testing process for higher yield today!