Interview With John Forrester, Chief Marketing Officer, Inbenta

There’s an increase in the use of chatbots in recent times by service providers to offer human-like customer support to customers without really involving any humanbeings. This demand has fueled the deployment of AI and NLP (natural language processing) to make the experience more personal, more inclusive. We caught up with John Forrester, Chief Marketing Officer at Inbenta, a cloud-based, AI powered NLP search solution provider for customer support and e-commerce, and a leader in conversational chatbots, providing an easy-to-deploy solution that improves customer satisfaction, reduces support costs, and increases revenue. Excerpts :

Q. From a global perspective, how big is the revenue loss for telcos because of inefficient customer support?

Considering the cost to serve telco customers is constantly growing and the NPS/CSAT scores of telcos are quite low compared to other industries, the cost to the entire industry is massive. Though I cannot quote specific numbers (this would be a major study needed to be conducted by an independent analyst firm), what we see with Inbenta customers is a 30-50% reduction in customer service costs and a boost to growth. So if you added the up total cost to serve telco customers as an industry and quantified 30-50% of those costs being squandered on inefficient customer support, you’d see hundreds of millions of dollars, if not billions, being wasted each year. I found that Comcast alone had $2.5B customer service cost. At a 30% reduction in cost to serve, that could represent over a $1B+ due to inefficient customer service – including phone, email, web, and chat. NLP and AI technologies could represent a massive gain in customer service efficiency and a reduction in costs along with an improvement in customer satisfaction.

Q. What are the challenges with the traditional customer support mechanism involving human beings? And how a chat bot based or mechanism involving machine learning, NLP and AI is going to be better solutions?

Humans are less informed than robots and require constant training and management. They have less access to information. Often, each customer interaction requires time for the agent to research the customer questions. In many cases, call centers are utilizing NLP and chatbots to provide answers to agents searching internal FAQs and knowledge bases for answers. Ultimately, the most efficient solution will be to have customer facing chatbots that are plugged into these databases to provide immediate, 24×7 answers. The chatbots can function as a level-1 support providing answers to questions, while leaving the human-based support teams to problem solve more complex, level-2 questions.

Q.Can you give me an estimate of the finances involved in both the models (with human beings as customer support vs AI based support) for a telecom operator with, say, 100 million customers?

Typically the cost-to-serve for telco operators is around $4-10 per customer interaction. Considering Comcast has 23M customers, and it spends $2.5B per year on customer service, at an estimated $10 per customer interaction, that means that Comcast likely has around 250,000,000 customer interactions per year. If telco operators deployed AI and NLP technology, the savings to those companies would be massive, as chatbots typically have a cost-per-customer interaction of below $1 and they work 24×7, reducing overtime costs and the need for multiple shifts, along with eliminating the need for outsourcing, which are unpopular for brands and frustrating for consumers. The cost savings and deployment of chatbots could allow telco operators to in-source their customer service, focusing US-based staff on level-2 support.

Q.When the telcos all over the globe moving towards an all-IP network, especially in case of India, do you see AI based customer support makes more sense than traditional methods? Can you elaborate, please?

It makes even more sense. Customers are demonstrating their preference for chat compared to traditional phone and email support. They like the immediacy of the solution. However, due to its popularity, it is overwhelming call center operations. Chatbots can help, reducing volume to human agents and reducing the time-to-wait for customers.

Q.Data security and privacy become prime concerns as soon as you hand over the reigns to a robot or machine. Do you see any security related challenges in deploying chatbots and how to overcome that?

No different than existing contact center technologies, either on-premise or in the cloud. They all conform to the highest levels of security, especially when handling customer data. Inbenta serves global financial institutions and adheres to their demands for the highest level of security and conforming to privacy concerns.

Q.How are your solutions helping telcos? And why a telco should consider your solution?

We help telcos today improve the customer support operations and increase their customer satisfaction scores. Ultimately this helps the industry and helps their brands in the marketplace. Telcos should consider an intelligent answer like Inbenta to the problem of inefficient call center operations.

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