need for artificial intelligence in contact centers

What Is The Need For AI In Your Contact Center?


19 January 2023

Artificial intelligence has a strong presence in today's competitive marketplace. AI advancements are opening up vast opportunities to businesses, especially in the field of customer service. For businesses that primarily provide call center services, using AI and AI-based solutions at cloud contact centers has a substantial financial advantage. Additionally, it relieves you from the high cost of setting up and running the complex infrastructure that is required to run AI-enabled applications. All of these advantages can encourage businesses to make the most of their contact center. Existing systems can become more effective, spend less, and provide more output both qualitatively and quantitatively. When properly implemented, it can have a significant impact on how your agents treat your customers and the degree of customer satisfaction.

AI has demonstrated to be of utmost significance for customer service, to modernize your customer service strategy and keep you ahead in the CX curve, Let’s look at some of the popular contact center applications powered by AI.



1. Artificial Intelligence to help Contact Center Agents

2. Live Call Analysis

3. AI Aids in Call Prediction

4. Sentiment Analysis

5. Call and Channel Routing

6. Self-service

7. Managing Big Data

8. Real-time Coaching

9. Personalized Customer Service


Artificial Intelligence to help Contact Center Agents:

During a phone call, as an agent is listening and interacting with the customer, AI can work in the background and perform some of the labor-intensive knowledge base searches, freeing the agent to concentrate on customer engagement. The agent can analyze the results immediately after being given the information, choose the course of action that will be most effective in each circumstance, and transmit the response to the client.

AI also performs better when receiving data from customers in the form of emails or chat conversations that are in written text. Accents, translations, and other dubious input are eliminated to make it simpler for automated processes to interpret the data and react to interactions. Agent assist tools can double as a rebuttal engine and can aid the agents with the next best action or response.


Live Call Analysis:

With the power of AI, each call can be monitored in real-time and the admin can set certain keywords, phrases, or intent that need to be monitored. As soon as such an event is triggered (with the set frequency), the call can be flagged to the supervisor.

The supervisor can choose to monitor the call (viewing the live call transcription) and decide to do a call whisper or call barge.  In this way, the supervisor can provide coaching to the agent whenever necessary or directly speak to the client to avoid any escalation or dissatisfaction.


AI Aids in Call Prediction:

Many contact centers use artificial intelligence to predict customer behavior, such as how many calls they can expect during a shift. Predictive analytics, when applied to historical data, can provide call forecasts.

In the CZ Admin dashboard, the supervisor can view the forecasted calls for the coming days or shift hours. This can help the supervisor to plan for the workforce.


Sentiment Analysis:

Contact centers can do sentiment analysis using artificial intelligence technologies to track customers' feelings, attitudes, and opinions to learn how they feel about the business. This technique uses machine learning (bag of words) and natural language processing (NLP) on customer interaction data. All of these interactions are then given a positive, negative, or neutral score, and the reporting tools make these scores visible. Organizations can quickly understand the sentiments of their customers with sentiment analysis.

In the CZ Admin panel, the sentiment score within an interaction is tracked as how the sentiment trends during the conversation. Apart from knowing the customer sentiment, this also helps to know if the agent can pacify an irate customer or even vice versa! Good interactions can be tracked and used for training purposes.


Call and Channel Routing:

Contact center solutions are omnichannel, which means support is offered across a variety of channels. By meeting the client where it is most convenient for them, an omnichannel structure powers good experiences. The imbalance can be corrected with the aid of artificial intelligence.

CZ IVR (interactive voice response) systems collect data from callers and offer automatic responses. If a customer is facing difficulties to resolve an issue themselves with IVR, with artificial intelligence recommendation, it can direct the call to the agent who is most qualified to handle it. AI-enabled self-learning algorithms will provide businesses with a competitive edge since they will make the most of their available data. As a result, rule-based systems will transition to "cognitive" systems that enable smarter routing.



Self-service platforms are now much more effective with the development of artificial intelligence. Self-service now allows customers to resolve relatively more complicated issues. IVR dialogue can sound natural with artificial intelligence. IVRs have been around for a while, yet customers still prefer speaking to a human.

IVRs can be trained to converse with customers effectively using artificial intelligence. IVRs that allow customers to speak their responses rather than pressing buttons can be created using speech recognition technology. While modern-day customers get used to Alexa or Google home, they expect to interact with the businesses IVR similarly.


Managing Big Data:

By automating and improving complicated analytical activities that would otherwise be time-consuming and labor-intensive, such as data preparation, data visualization, and predictive modeling, AI makes big data analytics easier. AI expedites the processing of large, complex datasets and provides users with pertinent insights.

Big data serves as the fuel for artificial intelligence. Large volumes of diverse data allow machine learning algorithms to learn and perfect a skill, which is what they were designed to do. Artificial Intelligence can learn and improve its capacity for pattern recognition as more data is made available to it. The visualization can be in the form of a Word cloud (major issues getting reported) or a summarization of customer interactions. There are more ways that the data can be converted to actionable insights. Technologies contact centers plan to use in the future are led by AI (56%) and robotics and process automation (33%).


Real-time Coaching:

 The use of artificial intelligence (AI) in customer service is evolving quickly. Contact centers are using real-time coaching to boost employee productivity, enhance customer interactions, and reduce expenses. Real-Time Coaching enables managers to monitor agent progress in real time while providing each agent with dynamic, live guidance. The usage of AI in coaching is always beneficial because it can bring far more value than actual trainers. This is particularly true in the fields of unlimited capacity, location analysis, bias detection, and voice and pattern recognition. AI-based assessment tools enable users to reflect on content learned via reminder features and receive daily notifications based on their assessments.


Personalized Customer Service:

A virtual agent is an online chatbot that converses intelligently and knowledgeably with customers using machine learning and artificial intelligence (AI). When it comes to handling frequent and automated calls, like altering delivery slots, canceling appointments, carrying out password changes, etc., they are incredibly effective. These questions are frequently routine and shouldn't necessitate speaking with a staff member.

Your entire operational model will alter if you augment your live agents. At a lesser cost, the capacity is enhanced without sacrificing customer satisfaction while the hold time and average handling time (AHT) are decreased. Voicebots are finding more usage in collection bots whereas chatbots are more pervasive, right from lead generation to customer support – it is a game changer and acts as digital workers for your team.



Given all the perks, you can see how having AI in contact centers has a lot of advantages. AI has the potential to revolutionize the way customer service organizations operate, including its capacity to lower operational costs, personalize the customer experience, deliver actionable analytics, and boost customer agent productivity. It is a solution that, when used properly, does wonders for the contact center industry. So don’t think twice, this is indeed the best time. Get in touch with C-Zentrix for a seamless AI implementation for your contact center.


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