Businesses now realize the need for a customer-centric approach to transforming their customer experience (CX). According to the Zendesk Customer Experience Trends Report 2021, 75 percent of company leaders agreed that the global pandemic accelerated the acquisition of new technologies to get customer-centricity right.
But, there are challenges too.
- Some of the businesses don’t have the systems and technology to segment and profile customers.
- Some lack the processes and operational capabilities.
- Some of them don’t have all of the components in place to claim they are customer-centric.
- Few don’t know what their customers expect and how they want to interact with the business — not the products, features, or revenue model.
However, in the digital-first world, social messaging is the dominating communication channel consumers are using to interact with brands. Forward-looking businesses are tapping this trend to their advantage using industry-ready AI chatbots to manage customer-centric interactions and forge customer relationships online.
While adopting the latest AI technologies to improve customer relationships, it becomes imperative for industry leaders to keep an eye on the latest customer engagement trends. Here are a few reasons that explain why a top-notch customer experience is the need of the hour:
- To enable a Superior Omnichannel Experience
AI-powered chatbots are capable of preserving information across several digital touchpoints and even when it transfers the conversation to a live agent, customers don’t have to explain their issues repetitively. Such availability of information across the channels helps businesses provide a consistent omnichannel experience to their customers. This experience helps businesses save time for customers and amplifies the customer engagement graph.
- To improve Brand Loyalty & Differentiation
Another success metric for businesses is to consistently improve their brand value in this digital competitive arena. Brand loyalty involves an intrinsic commitment of a consumer to a brand based on the distinctive values it offers. Hence, it becomes an obvious reason for CXOs to leverage a Conversational AI technology that enables instant, relevant responses helping brands provide improved experiences and differentiation.
- To expand new Customer Base
The biggest success for brands is to acquire new customers and expand their customer base over time. Providing instant prompts with offers, product recommendations, and guiding customers through their conversational journeys enables businesses to broaden their reachability and increase conversions.
Intelligent AI chatbots are fast becoming key enablers to customer support and conversational commerce teams and are instrumental to improving the end-customer experience landscape.
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AI Chatbots are not a “one-size-fits-all” solution. No two brands have the same business needs, so no two chatbots can be the same. An all-in-one solution that goes right for all the business functions sounds like a myth. Hence, the approach has to be changed as per the business use cases while building and training an AI chatbot.
When catering to customer support and conversational commerce use-case, the “One-size Fit-all” approach is not able to solve all customer queries. The responses will sound generic to customers and increase dissatisfaction. Hence, the right approach is to replace this with the best and most common industry use-cases to improve efficiency and conversions.
Here are a few problems that remain unsolved with the one-size-fit-all approach:
- Every industry has its distinct use-cases. Today, every industry has its unique business use cases depending on the marketplace and audience they are targeting. Hence, a versatile approach that provides solutions to industry-specific use cases should be the topmost priority for businesses when adopting customer experience automation technology.
- Non-personalized responses don’t work anymore. A generic AI Chatbot will not be capable of providing contextual responses across omnichannel digital touchpoints. In the current landscape, this won’t work anymore. The need of the hour is a domain-intelligent AI Chatbot that can end-to-end resolve customer queries, providing a seamless experience to the customer.
- Customer satisfaction matters. Unhappy Customers are an outcome of poor customer service. A generic AI chatbot will not be able to deliver top-quality support and service as they are not supported or trained to handle domain-specific commonly recurring queries, resulting in increasing customer dissatisfaction.
While it is established that a domain-specific, AI virtual assistant is core to enabling superior customer experience, it’s important to understand the technology behind it.
To understand the pain points, intent, and expectations of a customer in a conversation between a bot and a customer, NLP is the behind-the-scenes technology that makes the magic happen.
Natural Language Processing (NLP) is a subsection of Artificial Intelligence that enables chatbots to understand human languages. NLP analyzes the customer query, language, tone, intent, etc., and then uses algorithms to deliver the correct response. In other words, it interprets human language so efficiently that it can automatically perform end-to-end interaction with accuracy.
Key Capabilities that NLP provides:
- NLP allows chatbots to understand voice input as well as text.
- With NLP technology, the chatbot doesn’t need the exact correct syntax to understand customer’s expectations.
- Based on its programming mechanism, it can auto-detect languages, context, sentiment, and intent.
- Chatbots can either process their response through their NLP engine or by analyzing customer’s browser preferences.
Intelligent AI chatbots are now critical to strengthening a brand’s CX strategies. As cognitive AI-powered technologies continue to develop, business leaders must ensure they adopt chatbots technologies that are agile to meet the requirements of their businesses.
An AI-powered full-stack Conversational AI platform enables brands to comprehensively solve business problems end-to-end, and at scale. While looking to adopt a conversational AI solution, some of the key characteristics which CX leaders should look for are as follows:
- Powerful NLU & ML Intelligence: The turning point in the evolution of chatbots was the advent of two key AI technologies — Natural Language Understanding (NLU) and Machine Learning (ML). The architecture of Natural Language Understanding (NLU) is built on a combination of modules such as Language detection, ASR classification, Context Manager, that work in tandem with deep learning-based encoders to accurately understand natural language and handle user queries with higher precision. Businesses should go with a Conversational AI solution that has a high precision, powerful NLU capability.
- Ability to Create Domain Intelligent Conversations: Industry-specific AI chatbots embedded with domain-specific intelligence, data dictionaries & taxonomies are trained on thousands of user utterances to deliver human-like conversational experiences at scale. The in-built Named Entity Recognition (NER) engine helps chatbots to understand user intent and context better. As customer conversations are unique to a business, the Conversational AI solution must be agile and help create domain intelligent conversations.
- Quick to Launch: AI chatbots built using smart NLU and advanced domain intelligence capabilities Smart Skills deliver desired output with minimal effort and training. This platform consists of a comprehensive library of 100+ ready-to-use, domain-specific intelligent use cases for your business. Technology is getting easier to deploy and domain-intelligent chatbots can now be launched in a matter of minutes. Businesses should go for a Conversational AI solution that is faster to value and give quick ROI.
- Comprehensive integration to build a Full Stack solution: An AI solution that can be easily integrated into your existing CRMs, help desk software, etc helps create a full-stack solution with only one source of truth. The best scenario, in this case, is that the integration of these AI solutions should not require deep-coding dependencies or complex technical processes. Businesses should adopt an easy-to-integrate Conversational AI solution that has a comprehensive integration ecosystem.
While the above-mentioned capabilities of Conversational AI sound interesting and intriguing, it is only the tip of the iceberg. Technology has just entered the digital space and is expected to evolve further with time. Talking about the same, here are the top four customer experience trends businesses might come across in 2021 and beyond.
- The build-to-buy switch: Considering the increasing popularity, organizations find it optimal in terms of cost to purchase already-built tools and then customize them, instead of building one from scratch.
- Emphasize on what and how of the customers: 2021 conversational AI tools are more efficient now. They are designed to understand human language quicker, faster and give human-like responses.
- Deploy models (process-oriented) that are more than a messaging bot: Since organizations are on the lookout for automating a large part of their customer interaction funnel, emphasis is laid on the creation of tools that are one step ahead of the basic designs and can automate end-to-end queries and processes which are repetitive.
- Consolidation of customer support, marketing, and sales departments: To offer an omnichannel experience, the next wave of conversational bots is bringing together the different departments in an organization to achieve a common goal of customer experience.
CX transformation is a catch-all phrase that means something different for every business. There should be different strategic approaches when it comes to deploying AI-powered technologies. However, it is established that a simple AI chatbot will not deliver the kinds of experiences that a Conversational AI solution can enable.
In case you’re interested to explore more, here’s an eBook we’ve put together that shares the experiences of a diverse set of CxOs as a part of their journey to identify feasible, realistic solutions to solve the challenge of repairing a broken customer experience and scaling high-volume customer queries with AI Automation. Get your copy here.
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