A modified version of a website or app can be as simple as changing headlines and call-to-action buttons, or as complicated as redesigning the entire website or app. Either way, A/B testing tools provide real time data about your users, allow you to continuously experiment and optimise your website or app, and ultimately boost conversion rates. Besides, with A/B testing tools you can lower bounce rates and cart abandonment rates, save time and minimise errors in analysis, and increase sales without having to spend more on advertising. A/B testing, also known as multivariate testing or split testing, is a method of testing and comparing two versions of a webpage or app to find out which one is performing better. It all boils down to this simple concept: whichever version or variant of a webpage or app is better at capturing and converting visitors into customers wins.

In order to keep pace and be a disruptor in this digital customer experience battlefield, you should consider tapping into artificial intelligence. Machines and algorithms have become increasingly smart, to an extent that they can pick up the slack and speed up different business processes. In this guest post, Qeedle's Michael Deane shares some of the most effective ways AI-based automation tools can help you wow your customers. No matter whether there's a potential client who has a couple of questions about your product or an existing one, who needs their issue solved, you need to act quickly. Putting your customers on hold until one of your customer service agents is available can be highly detrimental to your conversion and retention rate.

Below we will explain what this new ML technology can do for you as well as lay out some best practices for getting the best results! The automatic feedback categorisation technology is the first of several new, built-in technologies to be launched by Mopinion, which will demonstrate the latest advancements in artificial intelligence and machine learning. It employs Supervised Machine Learning (ML) techniques that make the analysis of qualitative feedback data – by way of labelling and categorisation – a much more fluid and systematic process. Essentially with Supervised Machine Learning you are training the system to do what you want by providing it with examples to learn from. In other words, the technology takes historical data – which in this case is any labelling or categorisation the user has previously inputted into the software – and predicts how the feedback should be categorised based on that data.

Artificial Intelligence (AI) is essentially a technique used to enable computers to'mimic' human behaviour. Some even see it as synonymous with an exact replica of the human thought process. However, when it is used in marketing we're not necessarily talking about actual artificial intelligence, but rather applications of the sort, including machine learning and natural language processing. AI presents myriad opportunities for businesses that use large sums of data. Applications such as machine learning, for example, enable businesses to uncover particular insights within their datasets and clearly see patterns in that data.