We have seen the emergence of the digital contact center in the past 5 years. These cloud-based centers have realized process efficiencies, which are being augmented by platforms and technologies. Business process management platforms have laid down the foundation, which robotic process automation has further strengthened. The overall processes in the contact centers are being powered through the intelligence generated from these processes to continuously improve them.
Organizations across the globe are now trying to understand the correct mix of technologies, customer experience attributes and talent to deploy within their contact centers to achieve the optimum level of customer experience while keeping the process efficiency intact if not having a possible rise in it.
The focal point of contact center transformation: Conversational AI
On the quest to achieve the next level of efficiencies, organizations across the globe have started utilizing or at least charting the roadmap to amalgamate Artificial Intelligence (AI) as a core technology in the contact centers. Artificial Intelligence is of prime importance when it comes to enhancing the customer experience since it provides the dual aspects of efficiency and experience through its ability to not only perform complex tasks but also simplify retrieval, formulation and dispersion of the right content through the correct medium as well as channels.
Artificial Intelligence, therefore, has the ability to go beyond rule-based tasks such as data generation, de-noising to increasing effectiveness through data prediction as well as mood/behavior/emotion-based tasks to further customer relationships as well as provide customized recommendations to the user.
One such transformation lever, which can have permutations to perform the activities in the spectrum from efficiency to experience, is Conversational AI.
A low-level chatbot can address the FAQs and provide a first level resolution to free up agents who can tend to more complex tasks whereas an AI-enabled chatbot with ML/NLP capabilities can gauge and indulge in complex conversations which might involve activities such as optimization, ranking and recommendation. Deep Learning, Sentiment Analysis can help these cognitive chatbots impersonate the agents at a contact center.
How Conversational AI will drive the next set of efficiencies and experience
It is vital for organizations to choose the correct model/solution of Conversational AI for their front office operations. The majority of the cost will go into either the infrastructure for the deployment or creating the level of customizability that will go into the solution. So, it is extremely important for organizations to zero down on their exact requirements to work around the best possible ROI.
The other aspect that will play a major role in the overall cost is the level of AI that is being utilized by the chatbot. A chatbot which can gauge sentiment is bound to be higher in terms of cost and therefore will be highly useful for highly sensitive purchase/relationship touchpoints. A luxury retailer or a wealth management firm will supposedly be the organizations which would deploy a conversational AI with advanced sentiment/mood/behavior-based learning mechanisms.
It’s nearly impossible to have all the capabilities in one organization when it concerns a complete contact center. To provide the client with the best possible Conversational AI solution, leveraging partnerships has become a key factor in deciding the cost of the overall deployment. NLP capabilities form the majority of the chunk where economies of scale are leveraged when it concerns a conversational AI solution. NLP combined with conversational AI with ease of integration across channels and mediums (especially chat) would be the most preferable model for deployment at the present.
Some of the key trends that will shape the use of conversational AI in the coming decade will probably revolve around integration of the back office and the front office processes to utilize the overarching strategy to govern the external facing processes as well.
Organizations are looking for ease of deployment when it comes to any new technology, and platforms that are easy to integrate over existing systems, with low code-no code and have existing pre-built libraries are bound to grow manifold in the coming years. The other aspect will obviously showcase a parallel advancement in analytics assisting the agent or conversational AI through the introduction of a collapsible supply chain and improvement in customer analytics to provide the next best action prediction.
Enabling great customer experience through Conversational AI
Wipro Enterprise Operations Transformation as a dedicated solutions team which specializes in creating customized customer experience solutions for organizations. Conversational AI has been one of the primary transformation levers that clients expect in our solutions. While we have internal IPs that have capabilities ranging from chatbots to cognitive virtual agents; we also leverage our ecosystem of alliances across the CX domain.
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Contact center transformation is not based around one particular transformation technology, however, AI has come to play a significant role as a central enabler for many solutions that go into the creation of a digital contact center. This importance is bound to grow with the ever-evolving importance of the agent and the conversational AI platform, slowly enabling the agent to not only do complex tasks but also start leveraging human interaction itself as an important aspect of contact center proliferation.