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Does your contact center give you what you need to solve your customers’ problems or increase agent efficiency?
A contact center with the traditional system can limit customers’ ability to find answers and solve problems autonomously while also adding to agents’ woes.
Built on top of Generative AI, a contact center helps transform the customer service experience by making contact centers and their agents more efficient.
Let’s know what Generative AI can mean for your contact center and how it helps elevate your customers' experiences.
The critical objective of the contact center is to deliver outstanding customer results for the problems with which they want to interact with a virtual agent or a human agent.
However, contact centers often lack the expected customer experience due to several drawbacks.
The overall impact is that contact centers experience a long queue of pending requests with increasing wait times.
With this, the typical scenario is that complex requests could add to an agent’s fatigue and delay responses.
Unsurprisingly, the compromised contact center service hinders superior customer experience.
In a survey by Replicant, 91% of customers reported poor CX post-COVID.
Another IDC survey reported that the industry wasn’t prepared to handle contact centers during the COVID period. 40% of respondents said they had higher call volumes than the trained agents could handle, while 10% of calls were resolved using virtual agents.
It demonstrates the state of contact centers that can quickly impact customer experience and lifetime value while affecting operational efficiency.
Fortunately, Generative AI provides all the necessary capabilities to transform contact center experiences for your customers, agents, and everything involved.
We already know ChatGPT is a game-changer for all-natural language tasks. Relying on its massive underlying technology, Generative AI, industry leaders can reimagine the current state of a contact center—by extending its limited capability of handling tickets through automation.
Generative AI levels up automation capability and accomplishes more for a contact center than a typical chatbot.
Not only can it understand and speak human languages flawlessly, but it also has this unique ability to predict and show empathy.
Imagine chatting with it, and it responds not just with generic answers but with genuine understanding and compassion, almost like talking to a natural person.
Plus, it does not just provide information; it can actually reason and draw logical conclusions, making its responses even more insightful and helpful.
What is more interesting is that conversational AI experiencesaren’t rigid and rudimentary with Generative AI.
Customers can interact with voice or text messages and get answers to solve problems.
Building your contact center on top of Generative AI can deliver great experiences by automating responses that help solve problems, improve operational efficiency, and create satisfying customers and agents.
Generative AI can only provide answers—and problem resolution is not its role.
Similarly, Conversational AI can use NLU and NLP to improve interactions. But they can be limiting as well.
With some techniques like integrations with Conversational AI, the GenAI model can perform NLP tasks and handle problems.
As a result, combining these technologies can completely redefine customer service experiences by increasing problem-solving at scale and bringing holistic customer support.
Here are how you can use Generative AI and conversational AI in your contact center to deliver exponential improvements in customer interactions and nurture conversational experiences.
With the world of knowledge infused inside LLMs and integration with business cases or proprietary systems—CRM, ERP, or intranet, you can use conversational AI and Generative AI to improve natural language processing with machine learning techniques efficiently and ultimately improve intent detection and context switching to better understand user queries on text or voice. This gives your users the ultimate interaction experience without vagueness or confusion.
Generative AI helps translate a contact center experience into a multichannel experience by integrating calls or requests from different disparate channels into one integrated platform—CX platform or chatbot.
With unified visibility into one integrated channel, agents can reduce the time to track the right message from customers on their issues, thereby enabling faster identification of cases and resolution through natural language understanding.
Using an LLM-powered orchestration layer, you can build your workflows with multiple use cases across customer interactions and deploy your models with low effort and less time.
Workflows or automated contact center conversations become a powerful AI Copilot to guide your agents to handle varied interactions across multiple channels.
Customers can handle common to complex tasks or queries easily, alleviating pain for agents to address mundane issues and reducing the rate of errors.
The best thing about LLMs is that they can learn faster from interactions or human behavior.
This helps contact centers derive insights from chat or voice interactions, enabling them to understand customer personas and demographics.
As a result, AI-powered contact centers can support agents to determine the best offerings or recommendations to improve their experiences on a rather complicated issue.
LLM-powered contact center leverages deep understanding to apply sentiments to queries and respond in a human-like way.
Compared to text-based sentiments, contact centers built on Generative AI can utilize continuous understanding for sentiment analysis and deliver empathetic answers for more sophisticated user sentiments such as humor or sarcasm.
Based on its understanding, contact centers can easily personalize responses and align with users' sentiments.
LLMs are best known for text generation. The best way to apply text generation in the contact center is by asking for appropriate email response recommendations with some related keywords and crafting a better response in real time.
LLM-powered recommendation for email responses saves time for agents without having to ask for help from an expert, yet delivers empathetic responses and maintains compliance.
The ability to interact in multiple languages makes your contact center an ideal touch point for self-help.
Multi-language responses can work efficiently for users from different locations and still get help in their preferred language to resolve problems.
At a time when this does not involve any agent to translate messages, large language models can help augment the speed of problem-solving for global users.
The capability of LLMs depends on how frequently you update your training data in the repository.
Reviewing and crafting databases is a lot of new effort, often leading contact centers to continue working with outdated data.
However, Generative AI interfaces provide the ability to generate new content and update existing data effortlessly.
That’s why you can keep your knowledge bases updated and relevant to industry-specific unique challenges.
As a result, contact center AI can help users address issues autonomously and derive great customer satisfaction.
With the ability to generate innovative text or content, the contact center can leverage this feature to summarize calls for voice or text-based messages.
Call summarization is an essential responsibility for agents to present a consolidated idea of how customers get resolution, which otherwise takes several hours of time to craft and share the information among stakeholders for real-time awareness of an incident.
As the LLM-powered contact center automates call summarization, agents can handle more critical issues and solve problems.
Generative AI contact centers easily harness scattered data across disparate channels into one platform, ensuring that data no longer remains siloed.
With robust visibility into centralized data, LLMs improve predictive analytics for contact centers, providing great insights into customer behavior and future actions. As a result, predictive analytics can recommend the best action to reduce customers’ problems in less time and improve customer retention.
Predictive call routing helps the contact center cut agent expenses by intelligently routing the call to the right person.
With smart identification of unique customer problems, a contact center allows customers to use conversational AI that simplifies routing the call to the right team for specific problems, allowing agents to focus on critical issues, reducing wait times, and solving problems in real-time.
Generative AI-powered conversational AI is a transformative support for contact centers to facilitate operational efficiency for a variety of business functions.
The use cases above have significant value across Finance, IT, and Legal areas.
The contact center provides reliable customer interactions for users with fintech business operations.
Multiple fintech operations can utilize workflows to automate contact center conversations for users.
Common queries such as the next subscription bill, wrong credit notes on account receivable bills, early discount criteria, commission charges for each transaction on trading apps— and many more queries can have workflows for contact centers to automate interactions and solve customers' problems.
In the digital age, remote IT support is pretty common.
Customers who use various IT products on-prem or in the cloud, such as networking support, cybersecurity patches, productivity tools, or development tools, face daily challenges with their IT operations.
IT companies can build their contact center support withLLM-powered chatbots or Generative AI-driven workflows to automate common queries and solve problems at scale.
Generative AI contact centers bring enormous opportunities for public or private organizations to improve regulatory compliance and facilitate security and privacy for everyone.
For example, customers would like to know the penalties for violating several laws, such as driving speed, money laundering, or sometimes utter ignorance or callousness in attitude.
LLM-powered contact centers can be a good way to educate people by providing answers to their queries and helping them maintain regulatory compliance.
Research by Qualtrics shows that 63% of customers emphasized active listening for contact center experiences. With that, 60% agree that customers would be happy to stay with a company that delivers enriched experiences.
Contact centers powered by Generative AI and conversational AI can bring transformative potential for businesses with significant benefits.
Generative AI can dramatically reduce the rate of repetitive workflows and streamline operations for contact centers by transforming conversational experiences for customers.
With calls being routed automatically to the right representative or increasing self-service efficiency, wait times decrease. This eliminates the need for agent involvement, giving them more time to focus on critical issues and provide real-time resolution.
This translates to dramatic improvement of CSAT, long-time customer relationship, fewer efforts for a marketing team to work on customer onboarding practices and steady growth.
You can effortlessly automate workflows for mundane activities your agents handle and reduce the dependency on them with LLM-powered self-service contact centers.
With customers managing everyday tasks, agents have fewer responsibilities to handle mundane activities, reducing their involvement 24/7 and dramatically reducing the costs of contact centers.
Virtual agents driven by Generative AI-powered workflows and predictive analytics improve the problem-solving rate autonomously for customers.
A contact center with Generative AI properties can demonstrate remarkable capabilities to solve problems in real-time and help increase CSAT rates, allowing them to adopt self-service at scale and increase their trust in a brand.
Your existing contact center may be limited in various ways to automate contact center workflows.
It has rudimentary conversation flows that only add to customer frustrations and force them to connect with an agent, which they otherwise prefer avoiding.
The enormous potential of Generative AI properties shows huge promises to transform how you manage your contact center operations and leverage all new innovative processes to build unique conversation experiences for your customers.
Starting from automated workflows for self-service to call summarization predictive analytics or NLP-based sentiment analysis, craft engaging experiences for your customers and win their advocacy to reduce churn and retain them for long.
The future of scalable contact centers lies in Generative AI. It means businesses that leverage GenAI tend to remain competitive, and those that do not lose significant value.
To build holistic contact center experiences, embracing GenAI is necessary.
Workativ brings similar contact center-like experiences for your internal support with an LLM-powered conversational AI platform to help you transform employee support and revenue growth.
Want to build Generative AI-powered workflows for your conversational AI chatbots to automate employee support? Get in touch with Workativ.