Generative AI and Customer Service

Discover 3 ways generative AI will reinvent customer service. Learn more about the advancement of AI.

Today, customer service teams find themselves at a crossroads. Customer service employees have never had to deal with so many cases, and customers are frustrated by having to wait longer and longer.

Often, in order to get all their work done, employees resolve issues for multiple customers at the same time while waiting for data to load from the systems.

When an employee closes a service case, they sometimes enter some observations, but these are often lost in the ether and other employees end up solving similar problems from scratch, without knowing that their colleague had already solved them.

With nearly half of customers citing poor service as the main reason they switched brands last year, businesses are forced to find a better way.

Lately there has been a lot of buzz with the appearance of GPT Chat, a model of. help users create text, images and other unique content from written instructions, They are based on pre-trained large-scale language models that Bardand Anthropic developed by OpenAI. Chat GPT and other generative AI models, such as generative (AI)artificial intelligence

Software development services such as generative AI models will completely revolutionize customer service, helping businesses operate more efficiently, offer more empathetic responses to customer requests and resolve cases faster.

Read more about what generative AI is and take a look at some of the ways this technology could revolutionize customer service.

What is Generative AI

Generative artificial intelligence, or Generative AI, is a field of artificial intelligence that focuses on the enterprise software development process capable of creating new data, such as images, texts, music and other types of content, autonomously.

Unlike the traditional approach to AI, which often involves classification or prediction based on existing data, generative AI aims to produce original information that has not been taken directly from a pre-existing data set.

The fundamental concept of generative AI revolves around the ability of a system to learn from existing examples and then generate similar but new results.

This is usually done by training on large data sets, in which the system learns the patterns and features present in the input data. After learning these patterns, the system is able to create new instances that share similar characteristics but can be unique and original.

How generative AI works

We have already seen the impact of AI on customer service. artificial intelligence give employees AI-powered capabilities, such as recommendation engines and answers to customer queries. clients and automatic case summaries.

But a lot has happened since then, with advances in various areas and new technologies launched on the market. With the help of generative AI innovation, we are on the verge of catapulting customer service operations to the next level of efficiency and personalization.

Generative AI and the evolution of customer service

Using generative AI we will be able to automatically generate personalized responses that employees will be able to send to customers without delay, whether by email or by message.

We can also train the AI ​​with all the case observations entered by each employee of the company and automatically generate drafts of consultation articles ready to go through the human review stage, which will greatly reduce knowledge creation time and make it easier to update articles.

By improving the usefulness and quality of knowledge across the enterprise, portals and chatbots of self-service will be more beneficial, which will give employees more time to devote to solving complex problems and Build long-term relationships with customers.

Generative AI will also bring advantages in field service, both for service, marketing and sales teams, and for customers. Service workers will be able to save time in the field with automated reporting.

The AI-generated guides will help new employees and contractors quickly onboard the company and refresh their knowledge with fresh learning materials constantly. For their part, customers will be able to resolve common issues on their own with self-service or even faqs.

The current wave of generative models are very advanced, but in some cases they can produce biased and even harmful results, as well as fabricated data (called "fake news"). Therefore, in the immediate future, it will be important to involve human reviewers, whether they are customer service employees or subject matter experts.

Given the enormous opportunities and complications presented by generative AI,

Also explained the potential of generative AI in enterprise technology (in English), and how to balance this transformative technology with reality and the risks.

But before you read the articles we mentioned, here are 3 ways in which generative AI is going to revolutionize customer service:

1. Super-powered chatbots

By complementing the capabilities of generative AI, it will be possible to have chatbots that provide more intelligent and personalized automatic responses, and also deeply understand customer problems, anticipate them and act accordingly. In this way, better-founded answers will be given to various customer queries, which will contribute to increasing the first contact resolution rate. Because generative AI will leverage data from past resolutions to analyze emotions and conversation structure, customer service teams will be able to continually improve, spot trends, and accelerate training and deployment. bots update.

2. Automatic generation of reference articles

Over time, we aim to use generative AI to create draft advisory articles based not just on case observations but also in Slack conversations, message history and Customer 360 data. The goal is to speed up the resolution process for employees and refer even more cases to the self-service system which will take pressure off call centers and employees.

3. Expediting the swarm of cases

We have already noticed that many customer service teams work more effectively thanks to the technique of swarming of cases, which involves employees calling on experts from across the company to help resolve complex cases or larger incidents.

Imagine how much more efficiently they could work if what was learned in other swarms of cases could be transmitted and applied more widely.

We will use generative AI to recognize previous similar cases, identify company members who have the right skills to address the problem, and recommend solutions and communications with customers to streamline and even automate many aspects of the case swarm.

We are at the dawn of an exciting new era of AI that will completely transform customer service.

Guided by Sparkout Tech Solutions, a software development company with a long history of developing ethical products, businesses will be able to harness the power of generative AI to supercharge productivity, accelerate case resolution, and deepen customer relationships through more personalized and specific interactions.

Yokesh Sankar is the co-founder and chief operating officer of Sparkout Tech. He believes in changing people's lives for the better and developing the skills they need for success.