Optimising any process can be the ultimate can of worms as no campaign response is not dependent one thing it is what is known as a multi-variable problem. This concerns understanding the different aims and background of each analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of analyses in order to understand the relationships between variables and their relevance to the problem being studied.
But to prevent my brain from melting, I came up with these six steps to minimise the “science bit” and make it more user-friendly.
- Ask a very specific question – what do we need to do to improve engagement?
- Create a very specific hypothesis – will a shorter subject line improve open rates?
- Test the hypothesis by sending the emails, tweets or posts.
- Log the results and pop them into Excel to see if your hypothesis holds up to scrutiny. It is key to give the campaign the time to run with potentially some re-mails.
- Learn from the outcomes and results.
- Repeat this simple method for additional hypotheses.