Small and large companies are adopting it, and both users as well as customers recognize this technology's potential. According to one forecast 90% of interactions with customers will occur via channels supported by artificial intelligence (AI).
A lot of people think of it as virtual assistants and chatbots, however, it's much more than that: AI transforms the engine of the whole business. The majority of business executives expect AI to revolutionize their business. Studies show that "in a couple of years, 89% of businesses will compete primarily on their customer experience".
In this blog, we'll talk about the potential of AI technology in the field of Customer Experience. Find out how you can be an innovator in your field. You will also see some examples of brands across the world using Wonderflow's technology to keep their customer-centricity in check. Once you really want a useful content on AI Enabled CX, look at this website.
Artificial Intelligence The reason? Every CX professionals know that dealing with consumers generates lots of information. Navigating multiple platforms to comprehend the unstructured and structured inputs is an arduous task. CX data is often messy and customer behavior can be unpredictable. It was once a nightmare scenario for data scientists.
This is where AI comes in. AI systems understand unstructured information in a way similar to humans. But they not only consume huge quantities of data at a greater speed, but they also learn through interactions. This intelligence allows them to join data and fill in the gaps to come up with an actionable, meaningful analysis. In conjunction with human expertise in establishing the business context, AI in CX allows for smarter, faster decision-making using real data.
What exactly is AI do? The computing power that powers AI in CX is not something new. What's changed is the ability to apply it in a bigger size and speedily. AI as well as Natural Language Processing (NLP) can analyze customer datasets to break them into individual components and discover the individual's intentions. Based on the interactions the AI program can make predictions.
The three main components of AI systems that are used in CX are as follows. The first one is to make sure that the researcher has an accurate image of the customer. Following this, information is delivered in real-time. The insights can then be utilized to improve the company's overall business strategy. Let's look at these details. Data unification: Data unification is a way for the creation of a single customer view that is both quick and affordable. It's the process of joining together diverse data sets from various sources and prepare them for analysis through matching, deduplicating and cleansing the data. This process consumes more than 60% of all data scientists time and is essential. The aim is to gather all the information from CRM and call center systems, as well as websites and retail systems to build a single view of the customer.
Take the example of deduplicating data. You've probably performed this task yourself in Excel and be aware of the tedious but essential task it can be. In deduplication, we're looking for an accurate and scalable method to cluster records (usually from different data sources) that are related to the same entity. At its core is the ability to connect records, such as to determine if two data records are related to the same company or if they might be errors.
What are the options of AI-enabled CX? AI has revolutionized the CX environment. We are just starting to see the potential of AI. Early indications suggest that customers are thrilled by the change, and that it can also have a profound effect on internal processes for businesses. This article will explore how AI-enabled CX can transform your business.
Chatbots, virtual assistants and personalization
The most obvious method AI can support CX is via the deployment of Chatbots or Virtual Assistants. When people think of chatbots they often imagine text-based interactions. However, advances in AI speech-to-text recognition as well as NLP have opened the way to chatbots with voice-activated functionality. Chatbots can be launched online, on mobile platforms, or in contact centers. The goal is to serve as a gatekeeper and deal with more straightforward queries using simple keyword recognition to address the customer to content to help them, like FAQs and other specific forms and sources.