Get scientific with these multivariate testing best practices.

08 October 2017 min Optimisation

While you don’t want to test every possible idea, you also don’t want to ignore ones that could impact conversion rates. So use multiple data sources.

From a testing standpoint, marketers are pretty familiar with A/B testing, where two nearly identical online marketing assets have one variable changed, such as the headline copy, to see which one drives better results. However, marketers can go further using multivariate testing, which tests multiple variables and variable combinations at once. It may seem more complicated, but multivariate testing is very useful, and 53% of marketers use it.

While you don’t want to test every possible idea, you also don’t want to ignore possibilities that could impact conversion rates.

To determine variations worth sampling, why not generate ideas from multiple data sources including:

  • First-party audience data on segment demographics, interests and behaviours
  • Third-party data from data providers for additional audience information such as transactional data, purchase behaviours or industry-specific data
  • Historical performance based on previous campaigns targeting similar audiences

 
Get your testing up to scratch with top tips from our data scientists, analysts and specialists at Annalect.

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