Generative AI powered Conversational AI Solutions

What Is Generative AI?

A kind of technology that uses artificial intelligence to develop different types of content is generative AI. Notably, this technology initially found its application in conversational AI tools in 1960. However, with the emergence of a machine learning algorithm called generative adversarial networks in 2014, generative AI could produce realistic pictures, audio, and videos.

In other words, generative AI is like a virtual artist or writer, that is, a collection of algorithms that are developing infinite possibilities. Not only can it form new data, but it can also work on pre-existing algorithms for high-end applications.

Generative AI offers

Humane Conversational
Flow

Seamless Customer
Service

Automated Conversation Summary

Improve
CSAT

Improve Resolution
Time

The reason for incorporating Generative AI in Conversational AI solutions is its technology model:

Deep Learning: – Deep learning involves harnessing vast volumes of data to train an artificial intelligence system, enabling it to execute a specific task.

LLM Model: Large Language Model is the underlying architecture of Generative AI, to generate coherent and contextual responses based on input.

Dialogue Model: It is an extension of LLM to enable conversational interaction.

Why Do You Need a Dynamic Conversational AI Solution Powered by Generative AI?

Create coherent Responses

Human-Like Conversation Flow

Expand/Rephrase Messages

Document Cognition

Adjust the Tone of Messages

Create Summary

What’s More..

Several venture capital firms have made investments crossing $1.7 billion in generative AI solutions during the last three years. According to insights from Gartner, the inclusion of this technology will result in the generation of 30% of outbound marketing messages by 2025. Moreover, they expect that the entertainment industry will release a hit film with maximum usage of generative AI by 2030.

How Does Generative AI Work?

In recent times, generative AI has been transforming our interactions all over the world. Besides churning out cutting-edge products, it streamlines work processes and forms engaging marketing campaigns. Thus, this artificial intelligence-based technology helps in gaining long-term success in a competitive business landscape.

Improve Business Processes

Using generative AI, you can improve your businesses through a better and more informed decision-making process.

Generative AI is the future of Customer Experience

Statistically speaking, the present focus of generative AI is on improving customer experience or retention. 44% of respondents in a survey mentioned that generative AI and machine learning will impact digital customer experience in the next five years. In other words, generative AI has an exciting future with a massive potential to revolutionise various aspects of customer experience.
Here’s why.

Generative AI drives lead generation and other business procedures for a superior customer experience.
You can also utilise generative AI to improve your customer experience by training your chatbots to offer quick replies to customer queries.
It increases customer loyalty and satisfaction to a great extent.

Generative AI and Conversational AI

You might be wondering if conversational AI is a component of generative AI, isn’t it? Conversational AI is a kind of artificial intelligence-based solution that enables users to interact with chatbots or virtual assistants. It identifies text and speech inputs and translates them through natural language processing techniques. On the other hand, generative AI employs deep learning techniques, such as GANs to analyse patterns for the formation of new data from input data. Using generative models, the generative AI systems generate new data based on the training data. Verloop has succeeded in merging the two and transforming the customer experience by overcoming staff shortages and labour costs.

Generative AI And Predictive AI

Though each of the tools is beneficial for modern businesses, you should understand the difference between them to choose the right one. While the former makes new data according to preexisting trends and patterns, predictive AI makes predictions after analysing data through statistical methods and algorithms. The objective of predictive AI is to label a data point, but generative AI focuses on producing the output of a data point. Predictive AI is currently stuck due to the data gap necessary for labelling and re-labelling training data for a particular task setting. However, experts are working to bridge this gap by accelerating the progress of predictive AI-based models.

Generative AI And Automation

Applications Of Generative AI

The potential of generative AI has come in handy for generating data in several industries.

Generative AI And Healthcare

Generative AI assists medical professionals in making better decisions about medicine and treatment plans. Its promising application is personalised drug discovery that creates treatments according to individual patients after analysing their medical records and diseases. Thus, specific treatments succeed in reducing trial-and-error procedures.

Generative AI And Marketing

Client segmentation, generation of marketing messages, and presenting strategies for upselling and cross-selling have been possible due to generative AI. It has increased sales for companies by leaps and bounds. The self-service portals and messaging apps provide customer service channels throughout the day. Generative AI has also contributed to a marketing experience without cookies on platforms like Safari, Chrome, and Apple.

Generative AI And NLP

One of the fastest ways in which AI is developing is its evolution through Conversational AI. Several firms are presently using artificial intelligence to create human-like responses for conversations with customers. Thus, the whole scenario of interactions with machines has changed to suit our preferences. Through generation AI, you can train machine learning models. It also provides data for testing so that you do not have to do it manually. The generation of test data is extremely useful for discovering technical bugs.

Generative AI And Customer Management

The automation of customer lifecycle management using generative AI helps in increasing sales, increasing engagement, and retaining customers. Through personalised onboarding experiences, companies can onboard new customers through personalised tutorials, welcome emails, and product recommendations. Based on customer behaviour, a firm offers personalised content to increase the chances of repeat purchases. The delivery of personalised content is also helpful for target promotions and loyalty program rewards throughout the customer lifecycle.

Generative AI And Content Management

Besides content generation in the form of new blogs, articles, etc. according to specific words or phrases, it can optimise earlier produced content. Thus, it helps in improving the relevance and quality of the content. Generative AI is capable of translating content into different languages to make it accessible to a wider audience. It is easy to find and categorise content with the help of a content management system. Therefore, generative AI has created a starring impact on customer service across various domains. Its immense potential has automated mundane tasks for small-scale and large-scale businesses.

Extend Customer Service With Verloop

Verloop uses dynamic generative AI technology to deliver the best results across all segments. If you are unsure of whether Verloop will benefit you, take a look at the following pointers.

Efficiency

The primary goal is to assist users receive immediate responses to their queries. Trained bots are equipped with full coverage of FAQs. In addition, you can automate the FAQs from documents or URLs in short timespans.

Productivity

Verloop is well aware of the role of high-quality customer service in higher CSAT scores. So, if you are using Verloop, your agents will not have to spend crucial time creating responses for communicating with customers. Instead, they can work on developing solutions to help customers. The platform not only saves your costs and time but also improves First Contact Resolution Rate (FCR) and First Response Time (FRT).

Customer Engagement

A vital factor of customer engagement is the adoption of a policy that is centred on customers. It has to be inclusive of the changing preferences and requirements of customers. Since every customer looks for a personalised and seamless experience, Verloop’s AI-powered model generates the most crucial content for marketing campaigns. The outcomes are improved– CSAT and engagement rates.