Small and large companies are utilizing the technology. Customers and users alike recognize the benefits of this technology. One reliable forecast estimates that as high as 95% of all interactions with customers will occur via channels that are powered by artificial intelligence (AI) in 2025.
A lot of people think of it as chatbots and virtual assistants, however, it's much more than that: AI changes the power of the entire company. The majority of executives believe that AI will revolutionize their industry. According to research, 89% will be focusing their efforts on customer service within the next few years.
This blog will explore the possibilities of AI technology to improve customer Experience. Find out how you can become a disruptor in your industry. We will also give examples of the ways that Wonderflow's technology is used by global brands to stay ahead of their customer-centricity strategies. If you really want a knockout post about AI Enabled CX,
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Why Artificial Intelligence?
CX professionals are aware that working with consumers can generate a lot of information. Navigating multiple platforms to make sense of the unstructured and structured inputs is not an easy task. CX data is messy, and the behavior of customers can appear unpredictable. This was once a terrifying scenario for data scientists.
That's where AI can help. AI systems understand unstructured information in a manner that is similar to humans. However, they do not just consume vast quantities of data but also at faster speed, they also learn through interactions. This helps them join data and fill in the gaps to come up with an actionable, meaningful analysis. AI in CX, which is a mix of human expertise to create the business context, allows for faster and more intelligent decision-making based on real data.
What is the process by which AI accomplish this?
The computing power that powers AI in CX is not something new. What has been changed is the capacity to perform it on a larger scale and at a much faster speed. AI as well as Natural Language Processing (NLP) can analyze customer datasets and break them down into individual components, and divine the individual's intention. The AI software can then provide recommendations based on interactions.
AI systems in CX contain three key components that are essential to the whole process. They begin by making sure that the researcher has an complete view of the customer. Then, the insights are provided in real-time. In the end, the insights can be applied to the company's business strategy. Let's look at these in greater detail.Data unification: data unification makes the development of one customer view affordable and fast. It's the process by which several data sets are combined from multiple sources. The records are made available for analysis through matching, deduplicating and cleaning them. It's the activity that consumes more than 60% of time of data scientists and is vital. To create one view of the customer, you will need to collect all the data from CRM, web, and call center systems.
Consider the example of deduplicating data. You've probably done this yourself in Excel and be aware of the tedious but critical task it can be. We're searching for an effective and efficient method of aggregating records (often from multiple data sources) that belong to the same entity. It's the capability to link records to determine if records are related to the same person , or in the event of errors.
What can we do with AI-enabled CX?
AI is transforming the CX landscape of CX. We're only beginning to realize the potential of AI. Early signs suggest that customers appreciate the benefits, and that it can also have a profound effect on internal processes for businesses. In this article we'll discuss how AI-powered CX can transform your business.
Chatbots, virtual assistants, and personalization
Perhaps, the easiest method AI supports CX is via the rollout of Chatbots and Virtual Assistants. Many people associate chatbots with text-based interaction when they think of chatbots. Still, developments in AI speech-to-text recognition as well as NLP have opened the way to chatbots with voice-activated functionality. These chatbots can be launched online, via mobile platforms, as well as in contact centers. The purpose of this is to act as a gatekeeper to take care of more basic queries. Simple keyword recognition could be used to identify the client and direct them to pertinent informational content such FAQs and other forms.
