With machine learning, you can change the way the contact center works by focusing on customer experience.
Today’s customer wants a personalized service experience (CX). They want personalized service on every channel where they interact with brands, even though the brands are having a hard time figuring out how to please customers and cut costs.
During the fight for customer experience (CX), the contact center is at the heart of the fight. Why? When a brand has a customer for the first time and only time, the contact center can make or break the customer experience (CX). It’s time for brands to stop thinking of their contact centers as a cost center. Instead, they should think of them as places where they can invest in technology that will help them build a closer relationship with customers and be more unique from their competitors.
Machine learning (ML) and new ways of looking at data are changing the way some of the world’s most well-known brands run their contact centers. This is revealing operational efficiencies, easing the burden on live agents, and improving customer experience (CX).
A lot of customer expectations have been met by contact centers over the last few years.
In the past, the traditional contact center couldn’t keep up with customer expectations. Now, the traditional contact center can’t keep up with customer expectations. Scaling agents to meet growing customer demand for always-on, personalized experiences isn’t possible with the old model. Instead, the modern contact center needs a 360-degree view of the customer journey, which includes quick access to real-time, contextual customer information that can be used right away.
Truly customer-focused businesses use advanced, real-time analytics to come up with data-based strategies for improving the customer experience in the contact center. Most businesses have used basic data analytics, but only 37% of businesses say they’re using advanced analytics to make money. This shows that there is a lot of room for improvement and that more intelligent solutions are needed.
It turns out that companies that use advanced analytics can cut their average handle time by up to 40%, increase self-service containment rates by 5-20%, save up to $5 million, and boost the conversion rate on service-to-sale calls by almost 50%.
Cloud technologies are going to change the way people communicate with each other at the call center.
Brands can use cloud-based contact centers to get customer data and use it to serve customers better at a large scale. This allows contact center representatives to quickly show relevant customer data so they can find and solve customer problems faster and more quickly. The use of AI and machine learning makes contact center operations more intelligent and changes the way contact centers work in a number of important ways, like:
With quick routing of questions to the right agent, customer service departments can cut down on call wait times and the time it takes to get a problem solved.
- The efficiency of the agents has been raised. Chatbots can be used to answer simple questions and do simple tasks. This reduces the number of calls that agents get, so they can help people with more complicated problems in real time.
- Increased business opportunity: Self-service technologies cut costs and make service more efficient, giving businesses more time to improve and come up with new ideas. In addition, data and real-time analytics give businesses the information they need to keep customers happy and loyal.
ML improves almost every part of the contact center by reducing call volume, making self-service more effective, and making it easier for representatives to get customer information and sentiment analysis quickly. When agents don’t have to deal with low-value interactions, they can focus on the tasks that need their unique skills, which increases productivity.
A modern contact center can be made by putting together the parts.
Intelligence technologies allow brands to think of the contact center as a way to be more competitive. Every business has different needs, but there are a few things you can do to make your contact center run better and use more of your data.
1 First, move to the cloud.
When you need to provide quick, personalized service to a lot of customers at a large scale across all seasons, you need a lot of data. The old data infrastructure wasn’t built to handle that. AWS has smart contact center solutions that can help businesses of all sizes solve problems faster, while also meeting the needs of small businesses and start-ups.
Consider how the financial software company, Intuit, has done. Technical help, tax document reviews, and help buying things are some of the things Intuit helps more than 16 million people with each year. Even so, customers were annoyed by long hold times and having to repeat information every time they were switched from one person who answered the phone to another person who answered. When Intuit used Amazon Connect, it was able to unify customer data across different business units, cut down on wait times, and add more agents during peak tax season thanks to AWS.
2. Think of data as a valuable strategic asset, not just a piece of paper.
People who work for businesses can use the cloud to better collect, store, organize, and process important customer information. That data can then be used for detailed analytics and sentiment analysis, which help businesses find important feedback about their businesses and products. The help of machine learning makes it possible for this important analysis to happen in the contact center at the same time as the call.
For example, Peraton, which provides mission services, digital transformation, and enterprise operations to U.S. government organizations, used Contact Lens for Amazon Connect, a solution that uses natural language processing (NLP) to detect customer experience issues during live calls. Contact Lens for Amazon Connect is a solution that uses NLP. Real-time ML helped Peraton improve its first call resolution rate by 25%, and it also cut the number of calls and costs by 5%.
3. Make new things with AI and ML.
When businesses have all of their customer information in one place, they can use more tools to make their agents and customers happier. In many cases, these tools help the company come up with new ideas using AI and ML-based technologies.
Amgen is a biotechnology company that uses advanced science, like human genetics, to find, develop, and make new human therapeutics. But it can be hard to keep track of call records from patients and doctors because they talk about side effects and adverse drug events in very technical terms. AWS Contact Center Intelligence (CCI) was used by Amgen to solve the problem. AWS CCI’s more accurate call transcriptions are powered by ML, which makes it easier for Amgen to analyze calls at a large scale, find customer insights, ensure compliance, and improve agent performance.
Modern contact centers are smart contact centers.
Organizations that can’t help their customers quickly and use data to help them are more likely to lose customers, and it costs a lot to get new customers. So, companies like Intuit, Peraton, and others are using ML to improve customer service, agent productivity, and business opportunities.
AWS solutions can help contact centers become data-driven, insight-driven profit centers. If your company changes the way the contact center is set up with data, it can improve customer experience, make agents more productive, and find new business opportunities.
