(Interactive Voice Response)
Current customers are known to be immensely demanding, needing speedy resolutions, personalised servicing and are looking for complete value for money. Even though traditional IVR systems were deployed with the purpose of customer self-servicing and reduce quantum of mundane questions to be handled by customer service agents, it never achieved the best results for organisations. The psychology of the customer who gets in touch is with a mindset where he wishes to resolve complex issues and escalations. Traditional IVR systems came with touch-tone commands where complex agent routing becomes tough to program and get the customer frustrated due to call diversion times. Traditional IVRs over time posed other issues and led to the advent of the A.I. based conversational IVR.
Conversational IVR typically means the ability to handle customer calls using artificial Intelligence where an intelligently programmed voice BOT, similar to a Digital assistant talks to the customer and uses speech to text mechanism to escalate the call to completion in a seamless manner. System processing powers led to the creation of NLP and NLU that helped in creating a natural language tone while communicating with customers. This as compared to traditional touch tone IVRs seemed to be a breath of fresh air. Conversational IVR systems can pre-determine the intent of the calling customer and make its conversation more human, interactive and relevant for the customer.
SlashRTC has developed their own proprietary NLP and NLU engines powered by automated speech recognition (ASR). Slash BOT that converses with the customer perfectly understands the intent and calculates the accurate meaning and rationale based on the same. This helps in retaining the customers interest and call times towards solving resolutions. The Conversational IVRs are designed to keep the customer from pressing buttons and selecting options via touch tones.
Similar to how we have seen or heard of GUI(Graphic User Interface), There is something known as VUI (Voice User Interface). In order to make a realistic conversational flow for the customer we have to empower our clients to conveniently design a fantastic flow of conversation. We also help completely set up the entire system from scratch for all our clients. By doing this, customers are well guided through the right flow that finally leads to a solution.
Cost Saving methodologies While it may seem impossible to save costs with a rising competitive ecosystem and retain customer service quality, SlashRTC’s conversational interactive voice response (IVR) helps minimise costs significantly while maintaining customer service quality to the maximum. SlashRTC manages to do this by reducing call resolution timings, retransfer rates and also optimising the time spent by the agent on communicating with the customer agent.
Lower Call Volumes & faster resolution rates The conversational interactive voice response (IVR) created by SlashRTC helps with an efficient and optimised flow for a customer and prevents a customer from continuously choosing touch tones to browse the options. The artificial intelligent NLP & NLU engines help understand the customers intent quickly. This helps a customer reaching a resolution sooner than a traditional IVR.
Efficient organisation productivity A conversational interactive voice response (IVR) enables thorough engagement for a customer. The engagement is possible even without the intervention of a customer service agent unless it’s a complex scenario that can only can be resolved by a customer service agent. This ensures perfect agent productivity levels.
Customer-Centric Self-Service Conversational IVRs built by SlashRTC encourage customers to self-service themselves and through this we have learned this becomes a more interactive experience and makes the customer believe that he is truly in control of the product or service that he has purchased. A conversational IVR system can be configured to the tune of the customers preferences as all customers are not the same however, the generic behaviour of customers are similar for specific product types and services.
SlashRTC's Conversational IVR?
Amazing customer reviews
SlashRTC's Contact Centre Solution was the most comprehensive, flexible and easy to integrate with our existing CRM app. We were able to complete the setup within a few days and the agents on the floor loved the Chrome Plugin, a complete transformation of our legacy application. They customised the solution to our needs and their support is commendable.
SlashRTC’s A.I. enabled Voice and Chat assistants have provided us with high quality service at a surprisingly reasonable price. The tracking process is very intuitive and the lead generation from Website visitors has grown by 125% with the help of their conversational chat bots.
The flexible architecture of the SlashRTC Contact Centre Solution helped us get all relevant and critical information pushed onto our systems in real time that allows us to make well informed decisions to increase the overall productivity and enhance our customer experience.
SlashRTC very efficiently replaced our existing On-Premise solutions with Slash Connect and also seamlessly integrated their system with Microsoft Dynamics. Additionally, They set up an Automated IVR for us and other useful features that have augured extremely well for us in terms of Reporting.
Our main aim was to increase our call connectivity ratio which was very low. They offered a one of a kind feature which was a rarity in the industry to find. They deployed Mobile CLI feature which enabled our customer service agents to have their own unique masking numbers. This enabled us to be excluded from spam calls and helped us connect to more customers. We were surprised with their flexibility and expertise in seamless integration
SlashRTC has greatly encouraged quick onboarding and personalised support for every agent in different parts of India. They have consulted us extremely well and have had a proactive approach towards adding additional features and functionalities whenever we needed.
