What is a CallBot and how does it benefit customer service

Konstantin Sadekov
June 19th, 2021

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callbot

In this article we are going to discuss a tool called Callbot, that can actually autopilot the calls and handle the biggest customer service problems. We show how it can benefit the business and what are the stages of implementing the Call automation bot.

  • What is a Callbot

  • How does it work

  • What are the business benefits

  • How to make a Callbot

callbot

Why do you need a Callbot?

The growing number of customer inquiries and the high staff turnover rate are the biggest problems that customer service is facing nowadays. As taught by biggest corporations like Google and Facebook, customers expect to get solutions instantly, as if by simply googling.

Waiting on the phone line longer than a couple of minutes might cost a company a potential sale, as often clients call to buy something, lose their patience and never call back. In worse cases, long waiting times can lead to customer churn due to unsatisfactory customer experience. According to a study conducted by Velaro, 60% of consumers are not willing to wait on the line any longer than 1 minute. 

call operator
telecommunications

What is a Callbot?

Callbot is an AI solution that automates your call center and enhances the representatives to serve inbound contacts more effectively. Some use the term “voicebot” but the technology is actually much more complicated.

Instead of listening to a bunch of options in an IVR and pushing buttons when calling customer service, the Callbot simply asks “What can I help you with?” and automatically provides answers to simpler questions. For more complex questions, the bot will route the call to the right agent the first time. Agents get solution flow suggestions which maximizes the call resolution rate and gives control over customer service quality.

As of today, companies have tried to increase customer service automation with IVR or chatbots using simple pre-programmed flows to guide customers. They provide limited value because as soon as a call goes off-script, these solutions become helpless and create confusion and frustration.

Callbot is based on advanced dialogue systems that utilize memory, personal preferences, and contextual understanding to deliver a realistic and engaging natural language interface. By understanding contextual clues and slang in real-time, the bot enables customers to describe issues in their own words. 

What are the benefits of a Callbot

What are the benefits of a Callbot
callbot

For the customer:

  • Does not have to go through the arduous process of pressing buttons in the IVR
  • 2.4 minutes average waiting time for reaching the agent is reduced
  • Callbot answers simple questions automatically
  • Accessible 24/7; customers can report issues even when there are no representatives at the call center
customer support

For the representative:

  • Callbot suggests solution flows and helps with complex issues by analyzing the conversation in real-time
  • Simplified onboarding: Callbot only forwards those topics to the representative in which they have been trained in
callbot benefits

For the business:

  • Significantly reduced number of calls routed to a wrong representative
  • Abandon rate reduced to near 0%
  • Urgent cases are prioritized
  • Allows to extract information from the calls to know exactly what the customers ask
  • Allows monitoring agent competency by analyzing the calls

Stages of implementing a Callbot

Stage 1: Get rid of IVR with Conversational IVR

Deploying a Callbot and correctly routing calls with AI enables to reduce wait times and meet SLAs, whereas call representatives can focus fully on resolving the customers’ issues. Conversational IVR transcribes the call in real time and classifies its topic using the natural language processing model. It forwards each call to the right agent and can prioritize calls e.g. calls with sales potential or technical failures. 

Stage 2: Empower your representatives with Agent Assist Tool

Agent Assist solution transcribes speech to text and analyses the conversation. it will suggest solution flows to representatives, meaning it will help to ask the right specifying questions, make a quick client’s background check and suggest correct answers. Receiving correct solution flow suggestions means that the representatives can give more consistent solutions faster and with less training. As onboarding time sometimes takes months and agents have to know solutions to hundreds of different questions, the Agent assist tool helps to onboard much faster and ensure the high quality of SLA.

Stage 3: Automate flow with Call Automation Bot 

As soon as stage 2 is automated and the first call resolution rate of the solution flow is high, it becomes possible to fully automate the flow. Not all the flows should be automated as we believe there are cases where representatives will keep on doing a better job for a very long time – for example, calls where a customer simply wishes to be heard. On the other hand, it is best to fully automate all the solution flows that are not very complicated and where the representative is just asking and saying what the AI suggests anyway.

Conclusion

Callbot is an AI solution that automates call centers and enhances agents’ ability to serve inbound contacts more effectively. 85% of customers prefer calling as a faster option to solve issues. With a high agent turnover rate, it is impossible for call centers to maintain the required level of service. This leads to huge losses in revenue and brand value. MindTitan is developing the first truly intelligent and multilingual call center automation solution for delivering human-like customer service without delays.

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Kristjan Jansons
Co-founder, CEO

Kristjan has been studying and working on machine learning projects for more than 7 years.

After acquiring a Master’s Degree in Computer Science and Machine Learning, he started working at Milrem Robotics as the Team Lead for Autonomous Vehicles, helping to build self-driving vehicles.

Kristjan also has experience in building intelligent systems for data centers, robots and electric formulas; also with computer vision and image recognition. He is especially fascinated by how people from different industries combine their knowledge with data science, arrive at new insights and help to accelerate innovation.

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