Marketing experimentation is the practice of making changes to organizations’ products, prices, and, promotions to overview the changes in the customer experience. Organizations get value from their ability of microtargeting, personalizing and automating with the marketing technologies. Technology solutions and services facilitate customer discovery with the help of social media marketing, web analytics, and optimizations. Measuring the effects of changes is followed by great experimentations that come with some challenges for the organizations. Following are some of the hurdles organizations face during their marketing experimentation with the ways of overcoming them:
Organizations should get out of the rut: Organizations sometimes fall into a checklist mentality with their testing technologies. The function of testing technologies is to split traffic to a brand and measure visitor behavior. Advanced technologies test multiple combinations to change many similar variables as button colors, headlines, and images. If organizations do not test the right things experimenting will not affect that much or if they test anything about which they have knowledge already the tests will not discover anything new. Organizations have to decide accurately before doing any experimenting. Marketing departments and advertising agencies that are hired by the organizations should concise the assumptions and avoid confusion. They should increase clarity of the value proposition.
Having too many answers: To have effective experimenting results organizations should change the opinions about the ways of working along with incorporating new ideas. Marketers should change the ways of their thinking, which followed by asking more questions and guesswork and surety about their answers to the marketing problems.
A/B testing is one of the popular types of hypothesis testing in marketing experimentation. This type of testing has turned the statistically rigorous mathematical process into an easy method of improving conversion rates. A/B testing randomizes web visitors into groups and shows each group a different set of content. When the test has enough visitors in each variation it analyzes which version has the better performance during the test over time and applies the winning version.
Organizations should resolve problems: Organizations should ensure the accuracy of their evidence. Validity threats can alter the data gathered in the experiments that lead to making the wrong decisions for the marketers. Also, validity threats sometimes followed by instrumentation effect, which might be a page that takes longer to render because of something erroneously loading in the background or problems with the testing and analytics software emails that don’t get delivered due to a server malfunction.
Experimentation is one of the keys of innovation and success of the organizations. And to spread the culture of experimenting organizations should demonstrate how experimentation can answer questions, evolve and adapt to new ideas and challenges.