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Customers often contact brands with issues and complaints. The response time in such cases is a critical factor in customer satisfaction.
Interaction automation focuses on intelligently automating customer-facing processes. The automation of communications, through interaction bots, enables modern-day brands to chat with their customers any time, any channel, all while triggering back-end activities automatically.
Interaction bots use natural language processing (NLP) and machine learning (ML) to understand customers. Making machines understand context, emotions, sarcasm, and other complex human attributes is an ongoing learning exercise. The level of insight and understanding that a machine can achieve – which humans have always been able to do – is what makes interaction automation the future of contact centers.
These are meant for rule-based interactions where bots answer simple queries based on frequently answered questions, most of it based on the existing knowledgebase.
These bots tap into a database and/or knowledgebase and use ML, NLP, deep neural networks, etc. to understand the context of the interaction to help customers and also trigger relevant back-end activities to carry out transactions, like order-placing.
These are text-based interactions using modern media, such as text-based apps that are already found in customers’ phones. This reduces the dependence on complicated technology for communication and helps carry out the conversation at the customers’ convenience.
This type of bot uses voice-assisted apps and tools supported by ML to help customers in query resolutions, giving way to a new era in business communication.
Interaction automation can be applied to all industries and verticals. Here are a few advantages of an interaction bot, both from a customer and a business perspective.
At the heart of an interaction bot, there are ML, NLP, and deep neural network algorithms that manage customer interactions. Using artificial intelligence, these bots are capable of understanding incoming data in any form, be it text, image, voice, or video.
Depending on the customer journey and the stage of the interaction, a number of interventions can be provided through chatbots, virtual agents, or even RPA at the back-end, all triggered by the front-end activities. To avoid trapping customers in machine interventions, we always provide the ability to switch to a different mode of interaction.
Our interaction automation solutions are designed to help customers smoothly transition to another channel or human intervention when required. While doing so, we ensure that the entire interaction history is provided as a background to the agent to avoid customers repeating themselves.
The interactions can either result in instant resolution or in RPA to carry out the desired back-end activities (e.g., placing an order, making a cancellation, sending documents or receipts). This not only improves the turnaround time and CSAT but also reduces the human intervention.
The scope and strategy for automation may vary depending on the type of company, size, and the process design. With experience in automating across verticals, processes, and scale of operations, we partner with you to find solutions that will yield significant ROI.
We provide end-to-end automation.
Initially, we used RPA solutions only for clients but quickly institutionalized automation within our own business. Today, we use ML and natural language processing (NLP) as a virtual workforce that is capable of executing tasks and learning from data sets, including decisions based on emotion detection.
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