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Making Customer Feedback More Actionable with Artificial Intelligence (AI) - Mopinion

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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.


How Can AI-Based Automation Tools Improve Customer Experience? - Mopinion

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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.


Best Practices for using Mopinion's Machine Learning Technology - Mopinion

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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.


All-in-1 user feedback software for websites and mobile apps

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The voice of the online customer is taking on an increasingly important role when it comes to improving websites and apps. So web analysts and digital marketeers are making more and more use of User Feedback Tools in order to collect feedback from the user. Mopinion takes it one step further and offers a solution to analyse and visualise user feedback results from your websites and apps wherever you need them. The real challenge for companies is not about capturing feedback, it is about how to make sense of the data.


Managing unstructured data is crucial to enterprises' AI goals

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For CenturyLink, customer surveys play an important role in understanding the customer experience. But, in the past, without the ability to analyze the unstructured data in these surveys, customer service teams couldn't drill down to identify the nature and characteristics of issues. "Using unstructured data is really important for us because that's where the real detail -- the meat -- comes in," said Beth Ard, vice president of customer experience at the Louisiana-based network services provider. "When you do scoring, for example, you don't have enough actionable insight to make the changes that you need without it." Most business analytics processes require clean and well-structured data, but enterprises are increasingly managing unstructured data formats -- emails, chat transcripts, audio and video, and social media posts.