With the emergence of regulations like GDPR and CCPA putting a stranglehold on the use of third-party consumer data sources, it is now more important than ever to have access to actionable first-party data. Being a marketer, you probably still have access to data such as customer purchase history, website, and paid search interactions. Still, there are limits to how many insights one can garner from these sources. 

As a response, leaders worldwide are rapidly embracing Conversational Analytics – a brand-new paradigm for CX data. Conversational Analytics represents one of the last bastions of precise first-party insights into how your customers interact with your brand, how they perceive your product/service, and how exactly they talk about it to their peers.


But What EXACTLY is Conversational Analytics?

Conversational Analytics is a technology that records speech and converts it into data. The concept is based upon the NLP (Natural Language Processing) technology of computers, where it “understands” the human language and allows computers to be posed queries and answer them verbally.

For Conversational Analytics to be practical, it requires vast volumes of voice data created from repeated conversations with voice chat assistants and chatbots. The overwhelming level of data produced through these interfaces allows Conversational Analytics to transform these voice data into insights. And also enhances its performance by forming a neural network of an algorithm for deep learning. 

The efficiency of Conversational Analytics depends upon its ability to attain data from various sources and its capability to leverage the same in real-time. For this purpose, virtualization supplements Conversational Analytics with a catalog of curated data sets, allowing quicker data access. Data virtualization creates a logical data layer that bridges the irregular chasms between different data types siloed across disparate sources. 

Conversational Analytics helps businesses through its AI capabilities. With companies looking to capture intent data, conversational AI is becoming a game-changer. AI can inform CX decisions in architecting customer journeys and the evolution of overall product and service offerings. According to a report by The Wall Street Journal, Conversational AI, which powers the interfaces and automation systems and feeds data into conversational analytics engines, is a market projected to grow to $15.7 Billion by 2024. 

Use Cases of Conversational AI

When people think of conversational AI, voice assistance and online chatbots frequently come to mind. Most conversational AI apps have extensive analytics built into the backend program, enabling a human-like conversational experience. 

While an AI chatbot is the simplest example of conversational AI, there are many use cases across an array of businesses. When integrated with business systems through APIs, AI bots can authenticate customers and access their information securely, offering the added benefit of conducting personalized conversations at scale. 

1. Online Customer Support is booming; one can even say it’s replacing human agents along the customer journey. Online chatbots answer frequently asked questions or FAQs surrounding topics like shipping, suggesting sizes for users, cross-selling products, and more. This technology is reshaping the way people think about customer engagement across websites and social media platforms. 

2. Conversational AI is constantly making Health Care Services more accessible and affordable to patients worldwide. Along with that, this AI is improving operational efficiency and administrative processes like claim processing much more hassle-free.

3. Internet of Things (IoT) devices are gaining popularity, with most households having at least one IoT device like Alexa speakers, smartwatches, or cell phones. What these devices do is leverage automated speech recognition to interact with end-users. Some prime examples of IoT devices with conversational AI are Google Home, Apple Siri, Amazon Alexa, etc.

4. Thanks to Assistive Technologies, companies are now able to become more accessible by reducing entry barriers. Text-to-speech dictation and language translation are some of the most commonly used features of Conversational AI for these groups.

5. Many HR Processes got optimized with the help of Conversational AI. These processes include employee onboarding, training, updating employee information, and much more. 

The Salient Benefits of Conversational AI

Without a shadow of a doubt, Conversational AI, when used wisely, can give your brand a competitive edge. Recent reports say that Conversational AI was responsible for a 67% increase in sales. So, here are some of its key benefits in 2021:

1. Augmented Productivity

The availability of automated customer support 24/7 for simple requests enables customer service representatives to focus on critical areas quickly. This, in turn, lowers the overall resolution time. The combination of conversational AI and automation also helps enhance employee productivity by allowing human agents to engage in multiple messaging conversations simultaneously, addressing more straightforward tasks and requests as they arise. 

2. Cost Efficiency

Staffing a customer service department can be very costly, especially for a small or medium-sized company. Here, providing customer assistance through conversational interfaces can lower business costs around training and salaries. Chatbots and virtual assistance can respond instantly, offering 24/7-hour availability to potential customers. 

Since, most of the time, the interactions with support are information-seeking and repetitive, and companies can program Conversational AI to manage different use cases, paving the way for assured comprehensiveness and consistency, all the while saving cost. 

3. Proactive Customer Engagement

Given the adoption of mobile devices, businesses worldwide need to be prepared to offer real-time information to their end-users. Conversational AI tools, being more readily accessible than human workforces, allow customers to quickly and frequently engage with brands. This immediate support leads to drastic improvements in the overall customer experience. 

Personalization features embedded within Conversational AI also provide chatbots with the power to roll out recommendations to end-users, giving businesses the ability to cross-sell products that customers may not initially consider buying. 

4. Scalability

One of the critical benefits of Conversational AI is the mere fact that it is very scalable. Adding infrastructure to support Conversational AI is a lot faster and cheaper than the whole process of hiring or onboarding new employees. Such a unique characteristic is beneficial when products expand to new geographical markets or unprecedented short-term spikes in demand. 

Keeping the Conversation Going…

According to a report by Market and Markets, the global Conversational AI market size is projected to grow from USD 4.2 Billion to USD 15.7 Billion by 2024, at a Compound Annual Growth Rate (CAGR) of 30.2%. 

With the COVID-19 pandemic still at large, companies looking to adapt to the “new normal” have to embrace the digital transformation. It is high time for businesses to start investing in intelligent automation using Natural Language Processing to effectively communicate with the customers and know what they are thinking.

Losing relevance can cost the company its future. The best way to survive this cut-throat competition is to stay current and speak ahead!

The Media Bulletin (TMB) is a diversified publisher and a digital media service company. Consistently at the forefront of innovation and technological advancement, TMB endorses digital technology to provide unique experiences to its audience through news, objective-oriented research and articles, and industry expert commentary.

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