AI in Customer Experience and Interaction

Role of AI in Customer Experience

With the increase in computation power and decreasing prices of storage devices leads to a digital transformation to apply AI in Customer Experience for solving business problems. Some specialists are calling it the fourth industrial revolution. Artificial Intelligence is all about making computers think like humans with customer interaction solutions.

"8.9 million new jobs to be created by 2025 which leads to an increase in demand for robot monitoring professionals, data scientists, automation specialists - Forrester"

Using domain expertise of humans, we are feeding the features to the system to create AI to solve problems of domains like healthcare, stocks, Computer Vision (CV), Natural Language Processing (NLP), Retail, Entertainment, etc. Due to these applications, have better solutions for problems like cancer prediction which is a way better than trained medical experts, stock market prediction by analyzing the various traits such as sentiments of people, detecting unusual activities in video, etc.

One significant difference has emerged immediately - UX focuses on the end-user, that is, the person who uses the product or service, while CX focuses on the customer. Taken From Article, Comparing Customer Experience and User Experience

The entire credit goes to the active community of researchers that made solving such problems with greater accuracy. AI can also be used for customer interaction, like humans are interactive and intuitive researchers are making systems that are as interactive and intelligent as humans but are resistant to tiring and boredom. The driving force behind it is electricity and a network connection.

Why AI in Customer Experience and Interaction is Important?

Below listed are the major importance of AI in Customer Experience:

Better Data Crunching - When tackling with the wide variety of data collected from different sources such as feedback, surveys, customer requirements, etc. humans might get into a state of confusion which to And what to deal first. Using the fusion of AI and machine learning it quantifies the insights collected from the data and ultimately leads to Better strategic decisions.
Hungry for Data - Results in better performance when we feed to more (variety) data. Let's take an example of an AI chatbot deployed at some support site. If we keep on asking the short queries, it gives good result but not as efficient as per the expectations. Great questions will improve its performance as the bot tries to find the intent from the query.
No Human Intervention in Services - A piece of software deal with the customer for handling its queries. Whatever you ask it can give you better answers or suggestions without saying pardon
Time Efficient - Can handle queries in no time. Without the need to think like a human before answering.
Cost Efficient - A single AI bot can handle communications of many channels at once. Hence, it leads to saving the cost of hiring.
Improves Routing of Tickets - For a customer-centric organization, it is necessary to improve the ticket's path. Consider the example of Uber there can be issues like refund status, driver not arrived, etc. So the system must route the tickets by understanding the intent of the problem to the respective customer care executive so that customer doesn't need to wait for more.

Some facts and figures related to Artificial Intelligence

Robots and AI will replace 7% of jobs in the US by 2025. But an equivalent of 9% of the posts will be created.
73% of Companies will shift their AI product to the cloud.
58% of consumers want the product can self-diagnose issues and automatically troubleshoot itself.

The secret sauce for a Successful Business

The organization must focus on customer involvement and engagement. With the introduction of AI in customer interaction, people started enjoying the services, increase in time of engaging, gains user trust and improves the brand value.

Helping and supporting a company or organization offers to its clients before, during, and after a transaction or use of a good or service. Taken From Article, Generative AI for Customer Service

Building Blocks for AI in Customer Experience and Interaction

Data Unification
Real-time insights delivery
Business Context

Data Unification - In an organization, data comes from many sources i.e. records, real-time data and curated data from the team. The problem is how to merge and match these sets of data to get the best out of it. Companies like General Electric (GE) have spent several years in data unification. The most important and tedious phase for data engineering teams to prepare ready for modeling.

Real-time insights delivery - It's all about analyzing the interest of the customer. Organizations like Amazon, Flipkart has made their recommendation algorithms that recommend product promptly and moreover can increase the buying capacity of the customer (upsell).

Business Context - When applying AI in the organization, we first need to understand the perspective of the business. What is our target customer and how we handle the ambiguity in the conversation between customer and support?

Fields that make AI in Customer Service Possible

The two of the major feilds were

Natural Language Processing

Analyzing the voice of the user, the system generates words. It's not limited to the word generation but can also find the intent and the speech quality of the user. Now we have bots that can transfer the spoken words to another language (transliteration).

Computer Vision

Deals with images and video. Services like face detection, auto-subtitle generator, beautify, etc are state-of-the-art applications of AI in computer vision. Some insights into the experiments conducted by Oracle on 800 respondents - "41% admitted that they found customer satisfaction data most struggling. The purchasing history and the social activity were the runners up in this experiment, and 38% found them struggling". "The manufacturing industry is very possessive about analyzing the changes in customer interest".

Real-Time Store Monitoring helps to know which customer is essential to any company and increasing customer convenience has remained the topmost priority for retail stores. Taken From Article, Real-Time Store Monitoring

Real-Time Use Cases of AI for customer Experience and interaction

Amazon Alexa, Google Home these devices are state-of-the-art examples of AI. They can understand the natural language, can authenticate the user based on audio and can control the entire home.

Apple Siri one of the advanced speech processing software. A personal assistant, can book a cab, gives better suggestions
Chatbot API provided by Twilio is quite intuitive and segments the user's query based on priority.
McDonald's acquired an AI startup that recommends based on time and weather to save customer's time.
Sephora an online beauty store that recommends the shades of lipsticks based on skin tone and dress. Increasing customer engagement.
Facebook messenger now recommends actions based on your chat, i.e. share location or a photo.
Disney is working on an augmented reality-based book app that automatically segments the black and white drawing image and makes it live on your iPad. The most fun part is the object even reacts when you color them.

The Agile User Experience Approach for building different UI/UX Processes. Click for Product Design and User Experience Solutions

Customer Experience and Interaction Strategy

Customer Interaction solutions help companies to optimize services and processes which further help to serve the clients efficiently. To know more about Customer Interaction Solutions we advise taking the following steps -