Use Customer Experience Analytics to Improve Conversational User Experience

Use Customer Experience Analytics to Improve Conversational User Experience

by Audelia Boker Posted on Apr 10, 2019

With the move to online purchasing in the last decade, the need for customers to be able to quickly engage with products and have any queries answered almost immediately has become paramount. Customers do not want to have to call customer service agent or wait for an emailed response regarding a question. If they have the ability to purchase a product now, they also want any questions they might have answered just as quickly. Due to this, customer experience analytics have become one of the primary tools in a business’s arsenal when it comes to developing strategies to engage with customers and improve their overall experience, which includes the conversational UX. One of the primary ways that the user experience is being improved upon is through the use of artificial intelligence, specifically through chatbots. So how can chatbot data analytics assist in the overall improvement of the customer experience?


The Rise of the Virtual Customer Assistant

Customer experience analytics tell you how your consumer is behaving online, where they are clicking, what they are reading, and ultimately what leads them to make a purchase. If a piece of information is missing from a FAQ section, then the customer will typically want an answer to this prior to purchase. This is where chatbots come in.

If you have technology that allows for deep learning then a chatbot can function as a virtual customer assistant who can answer almost any general question a customer may have, and in any language. This can drastically cut down on the need for live customer agents to field queries regarding basic information such as shipping times, or costs to ship to certain locations.

Essentially, chatbots are a multifaceted tool that can aid in a customer’s conversational experience with your platform without having to contact a live representative who may be needed to address specific issues. As well, a chatbot with embedded deep learning algorithms can sift through information and provide concise answers from previous questions that are of a similar nature. All the questions and conversations that customers have with a chatbot are then recorded and stored within a cloud-based technology for further data analysis. Chatbots can also direct customers to similar products, or promotions that are on to further increase the chances of a sale rather than abandonment.


Big Data Synthesis

Big data solution providers become necessary in this process as the customer experience analytics that are constantly uploaded are impossible for a live analytic team to explore on an in-depth level. Running analysis on this data allows you to look at trends within the chatbot info to see if customers are engaging with them in an effective manner or if there is something that is causing them not to buy the product due to the chatbot engagement or how the customer is interacting with the platform. In essence, the analytics provided show how a customer is interacting and whether or not they are experiencing a positive UX with the platform. So, make the most of all the analytics at your disposal from the chatbot interface, to the big data sift. Customer analytics are designed to increase sales and avoid customer abandonment, and repeat customers are the key to big business.

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