In today’s world, Artificial intelligence (AI) has been a huge influence in making telephony smart. The addition of AI in the world of telephony has brought technological advancements in the features and services of phone systems.
As more and more companies are shifting to cloud-based phone systems, they are more likely to feel the presence of AI while handling their business communications than they ever did in traditional phone systems.
Artificial intelligence in telephony has brought potential benefits to the industry which include top customer experience, excellent network support, and more. These benefits are the results of using AI to automate the mechanics of phone systems.
In this article, we will take about some of the common uses of AI in telephony and powerful AI-based features.
AI and telephony together are transforming the way people view phone systems. Most cloud-based phone systems have incorporated the concept of AI so well that companies are utilizing them as a core tool for running businesses. Let’s have a look at 8 uses of AI in telephony.
1. Predictive risk management
Running any business is not an easy task. There is always room for risks that can disturb the flow of services that businesses provide to their clients or customers. Businesses are dedicated to providing better services to their clients or customers. The telephony industry can use Artificial Intelligence to perform predictive analysis, which helps them provide better service.
With the use of machine learning, AI can analyze the organization’s historical data to identify any potential hazards or concerns that may arise in the future. This enables firms to plan for such situations and to totally avoid them. The business process is streamlined and uninterrupted with AI. This also aids companies in developing future-proof strategies to boost their performance.
2. Virtual Assistant
IVR is the abbreviation of Interactive Voice Response. It is regarded as an AI-based cloud telephony solution that allows customers to get assistant via a voice response system. It is also known as a Virtual Assistant.
IVR as a Virtual Assistant assists in routing calls to various departments without manual effort. When the FAQs are pre-recorded into the system, a Virtual Assistant can also resolve small consumer questions on its own. It also sends a welcome message to consumers, which can be changed at any moment.
3. Robotic Process Automation
All the telephony companies must deal with a vast number of data on a regular basis which increases the likelihood of human mistakes. To reduce such mistakes, telephone industries use RPA in their system.
RPA is the abbreviation of Robotic Process Automation. It is an AI-based business process automation technology that makes data processing easier and faster for enterprises.
It not only ensures error-free processing but also frees up more agents to focus on more vital responsibilities, such as dealing with clients and resolving their difficulties rather than wasting time processing error-free tasks.
It’s not possible to handle all the customers one after another. So, businesses are increasingly using conversational AI and chatbots to connect with their customers. AI Chatbots are pre-programmed to automatically respond to certain questions.
It also gathers information about clients that is supplied to the agent before they interact with them in order to provide a better customer experience.
AI chatbots make it easier for both the customer and the company to engage in a quick and effective manner. It also saves consumers’ time because the AI in the chat provides general information. Because many customers prefer talking to calling, AI chatbots are a valuable tool to any company.
5. Machine Learning
Many telephony providers use machine learning to improve the ability to do tasks efficiently over time. In simple words, machine learning is the process of learning the efficient way of doing a task by repeating the task again and again. Essentially, telephony software develops itself by learning from its own previous experiences.
By working with data repetitively, Machine learning helps you to predict data for completing the task quickly and accurately. It allows the software to work faster each time it is utilized. This saves the agents and organizations a lot of time and avoids the possibility of errors.
Also, it makes AI chatbots increase their vocabulary by learning from customers’ queries, details, and answers.
6. Optimized Network
The majority of communication networks are complicated and difficult to administer. AI can help network operators use enhanced automation in network operations which helps them to improve control and administration over their network. It can greatly optimize the network architecture so that the deployment of technologies becomes easy.
Data from networks and devices can be utilized to predict and prevent network-related issues as well as to deploy fixes to improve reliability. Additionally, AI can be used to analyze quantitative and qualitative data from customer interactions, service logs, complaints, requests, and cross-channel portals across demographics, devices, time zones, and regions.
7. Fraud Detection
The cloud telephony industry is one of the world’s fastest-growing industries. With more and more companies shifting to the cloud for telephony services, this industry is susceptible to fraud. Unauthorized access, cloning, data theft, and other frequent fraudulent acts are some of the commonly known frauds.
There are AI methods that can detect and block these illegal activities and prevent data from falling into wrong hands. It can detect irregularities in network traffic and prevent them from obtaining any vital or sensitive information.
8. Physical Database
It is challenging for large telephony companies that use multichannel communication to collect all of the data from various communication platforms in one location. They can use AI to create physical databases for storing customers interaction data to keep them safe in the event of a natural disaster.
The voice-to-text feature enables the company to make transcripts of phone talks and store them alongside the data from text messages or email chats with customers. This ensures that all of a customer’s information is secured in a single format.
Today, virtual cloud phone systems like KrispCall have powerful in-build features that use AI for handling communication channels. These AI-based features allow businesses to enhance the productivity of agents and the quality of customer experience to the next level. The following are some of the most popular AI-based features used in cloud telephony.
1. Predictive Dialer
A predictive dialer is a powerful outbound calling solution for a business. Its main purpose is to automatically dial the phone numbers from the given list. When it detects a connection while making phone calls, it transfers the call to the next available agent. It filters out all the busy signals, no-answers, voicemails, disconnected numbers, and so on.
The algorithm of a predictive dialer allows the system to predict which agent will be free for taking the next call and dials the next listed phone number on the behalf of the agent. This algorithm estimates when an agent will complete a phone call and then call a different phone number. Predictive dialers, when set up correctly, provide agents with a consistent stream of phone calls.
2. Intelligent Call routing
Intelligent call routing (ICR) is a call center feature that captures the incoming phone calls, sorts them into a queue, and routes them to the most appropriate agent. The system establishes routing priorities on the basis of the logic developed by analyzing the agent’s preferred criteria and rules.
Today’s ICR recognizes a caller, allows the caller to choose options from the menu based on the call’s purpose. After that, it routes the call to the agent defined in the routing rules and criteria.
When the intended agent is unavailable or busy, the system transfers the call to the next best alternative for the call and the caller’s specific purpose. It continues to search over the given list of targetable agents until it finds the best-suited one.
3. Voice to text
The Voice to Text feature automatically documents spoken speech into written text using artificial intelligence (AI) and machine learning. This is a great feature to store text messages and voice calls stored together for future references.
It assists you to retrieve important information in a textual format that was unclear in voice recordings. This data is a great addition for data analysis, training purposes, and keyword research.
IVR stands for Interactive Voice Response that provides call routing features through an automated virtual assistant. It enables clients to communicate with a computer prior to speaking with a professional. This technology is used in conjunction with Automatic Call Distribution (ACD) which is commonly used in call centers.
IVR collects information from the customer’s Inbound phone calls before automatically routing the call to the appropriate department. When customers make a phone call, they are greeted with a voice menu.
Usually, they have to navigate the menu manually by pressing the keys on the phone keypad for routing calls to the desired agent.
5. Call analytics
The monitoring, gathering, evaluation, and reporting of phone call data is referred to as call analytics. Marketers and sales teams use these data to improve marketing strategies and call management.
Marketers use call analytics in conjunction with web analytics to figure out which ads are generating appropriate calls. The objective of implementing call analytics is to improve, handle and analyze marketing metrics in order to maximize efficiency and return on investment (ROI).
Both call tracking and call recording metrics are critical success factors in call analytics. You may use the information to make better budgeting decisions for your campaigns, discover issues that are affecting conversion rates, target callers with ads based on the content of their conversations, and generate potential leads.