AI & ML in Contact Center – The Next Thing for Improving Customer Relationships

AI and ML in the Contact Center – The Next Big Thing for Improving Customer Relationships

Contact centers need to proactively connect with customers to gather feedback, as well as other critical metadata such as buying behavior, claims history, lifetime value, and demographics. In turn, this data can be used to train machine learning algorithms to derive customer insights. Let’s explore some of the benefits contact centers can realize by utilizing Artificial Intelligence (AI) and Machine Learning (ML).

How AI and Machine Learning Influences Customer Relationships

Artificial Intelligence and Machine Learning are widely used to improve control of several Key Performance Indicators. These KPIs include average time in queue, average speed of answer, the call abandonment rate, customer satisfaction levels, and more. Contact centers can manage and control every critical touchpoint associated with their customer journeys with the help of AI and Machine Learning integration.

The following are key ways by which integrating AI in contact centers is transforming customer relationships:

● AI-powered knowledge base built with Natural Language Processing

Contact centers require powerful tools to gather, analyze, as well as interpret and share customer data via necessary touchpoints and interaction channels. This is possible with AI-powered customer analytics. Additionally, NLPs (Natural Language Processing) can detect customer dislikes and issues in voice calls and even escalate it to live agents if necessary. RTSA (Real-Time Speech Analytics) assists in call quality assurance.

● Chatbots or VCAs For Self-Service

Chatbots or Virtual Call Assistants can help solve customer grievances on complex issues and thereby streamline customer relationships. Gartner predicts a 25 percent increase in businesses adopting chatbots by the year 2020.

● Machine Learning for Intelligent Behavioral Pairing

Machine learning technology can assist live contact center agents by providing personalized customer recommendations based on the customer’s history. The key factors involved in pairing or matching up customer and agent objectives also known as behavioral pairing analyzes the customer’s product preferences, buying behavior, time spent, and previous issues. The suggestions provided can help contact center agents understand customer preferences better and thereby reduce AHT (Average Handle Time).

● Intelligent Routing

Artificial Intelligence poses as an upgrade to the standard IVR (Interactive Voice Response) systems as it allows customers to listen to a list of menu options and respond closely to the reason the call was made. This solves the pressing concern that contact centers deal with – customer dissatisfaction with the standard and general options alone to solve their issue.

Intelligent routing analyzes the statements of the caller and directs the call to the concerned agent or resource accurately. With AI-powered Intelligent Routing, it is also possible to determine whether the caller has been directed to a live agent or a VCA as it has access to past call history as well.

● To Improve Compliance with Rules and Regulations

Artificial Intelligence techniques can be utilized in contact centers to make the contact centers compliant. Customer identification and verification processes can now be undertaken by ensuring access restrictions to customer’s sensitive personal data, thereby improving GDPR compliance.

● Reduces Operational Expenses

AI-powered automation helps contact centers improve customer relationships along with reducing operational expenses. Due to its availability in real-time, contact centers can boost their scalability with seasonal spikes in call volumes without an increase in costs. Additionally, the customer journey is improved by avoiding long waiting cycles and improving contact center agent efficiencies.

Read More:Harnessing Contact Center Data for Actionable Results

● To Plug Skill Gaps in Contact Centers

Skilled resources are always in short supply, especially in contact centers where the demand can be seasonal. This is a major reason why many contact centers employ AI-powered chatbots as the primary port of call to interact with their customers. Virtual Call Assistants can then direct the call to the concerned agents to resolve the customer’s queries or issues by directing the customer to the right part of a website or FAQ. If they cannot answer the query, it can simply direct the customer to a live web chat advisor. Biometrics and pre-authentication are other crucial applications used by contact centers to identify customer requirements accurately and thereby improve customer relationships.

Key Takeaways of AI and ML in Contact Centers

Artificial Intelligence and Machine learning can seamlessly blend chatbots with human agents to gather crucial customer data. The key benefit of AI and ML for contact centers is the collaborative environment it provides combined with scalability and improved efficiency . Through cognitive automation provided by AI, contact centers can automate processes and work efficiently with chatbots or Virtual Call Assistants for a better, more personalized customer experience.

Read More:How to Improve Contact Center Quality Scores and Customer Service

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