In 2021, proper A / B testing is more important than ever, and new and emerging technology solutions are breaking the barriers to a manual and tedious process. And that’s good news – there’s a lot at stake.
All of today’s largest tech companies have websites that are changing right before your eyes. For example, if you go to Amazon within 5 minutes, the user interface will likely change due to the company’s testing and refinement strategy. Similarly, thanks to ongoing testing and refinement, Facebook is constantly making changes to its app.
A / B testing is an age old method. If marketing organizations don’t use it, they’re sure to be left behind in 2021. Lifetime marketers tend to view A / B testing as a cumbersome process that requires designers and developers to work with. Fortunately, these days new technology has streamlined the process. There is simply no reason not to A / B test every important element of your customer experience.
A / B testing should influence decisions big and small alike, from simple and cosmetic elements (CTAs, button colors, etc.) to basic elements like page interactivity. Proper A / B testing can identify conversion barriers and move the needle on the bottom line significantly in the process.
Today, by autonomous testing, marketing organizations can eliminate a lot of manual heavy lifting as well as middlemen in this process. Autonomous testing is the ability to create test cases and execute them without human intervention. AI and machine learning do this by using algorithms, data, and predictive models to analyze web pages and provide a full breakdown of all the powerful elements.
This enables marketers to create a website that combines all of the features with the best performance and optimizes conversion rates. Think of autonomous testing as a spreadsheet for competitive marketing organizations in 2021 and beyond.
Natural language processing
When we talk about AI and machine learning, we are talking about natural language processing (NLP). It’s a concept that was discussed ad nauseum in our industry, but has so far remained on the edge of marketing at the implementation level. That’s going to change.
NLP is a branch of AI that learns from the interactions between computers and people and uses these insights to read, decipher and understand human languages. Brands can use NLP to automate communications in ways that make sense to customers and provide them with a better user experience.
Similar to autonomous testing, the latest iterations of NLP marketing organizations operating with fewer resources these days can enable more efficient efficiency.
By using NLP, the AI can successfully imitate human language, form naturally flowing sentences and give the interactions between humans and machines a personal touch. NLP can help AI unlock unstructured data in databases and documents by mapping key concepts and values so that end users can use this data for analysis and decision-making. In other words, brands can and should use NLP to move forward in the data world and provide a better customer experience.
For many marketers, autonomous tests and NLP in the field of theoretical marketing applications have existed for far too long. Today these technologies have reached a critical mass in terms of accuracy, ease of use, and ease of implementation. With efficiency and scalability still a priority in the post-COVID era, it is time for marketers to bring these technologies to the fore in their strategic planning and technology roadmaps