Achieve Better CX With Conversational AI and Automation


Customer Experiences Concept. Happy Client Using Computer Laptop to Giving Best Review

84
Filed under - Industry Insights,

Talkdesk’s Jay Gupta outlines the 7 fundamentals of customer-centric automation providing customer insights, supporting staff, and driving continuous improvement.

In every sphere of life, consumers are accustomed to interfacing with automation technology, from supermarkets to airports.

They might not even be thinking about how automation tools improve their experience. But consumers are thinking about their desire for convenience and speed in customer experience (CX).

Automation tools and artificial intelligence (AI) tools can enhance CX, both in customer-facing interactions and by improving processes behind the scenes.

To support today’s business models, contact centres need automation tools and conversational AI to help lower costs, boost productivity, and improve customer satisfaction.

Automation not only reallocates staff time from repetitive tasks to empathy-driven customer interactions, it can also gather critical insights to drive more customer-centric experiences.

I participated in an AI and automation session at CX Network Live where I discussed the well-known framework from Deloitte’s fundamentals of a customer-centric organization.

Applying seven of these principles to contact centres, I shared how AI and automation can help contact centres meet customer-centric goals. Read on for these seven components of customer-centric automation.

1. Top-Down, Customer-Centric Vision for Automation.

CX leaders need a clear vision of what customer-centric automation means to the company, and they should communicate that vision to contact center staff, especially frontline teams.

With a focus on business outcomes, leaders should explain the anticipated productivity gains and the way customer-centric automation offers upskilling opportunities to staff.

For instance, the use of AI-powered tools can improve working conditions for staff, relieve them from repetitive tasks, and give them new ways to resolve customer problems.

CX leaders can (and should) frame conversations about the role of automation to leverage three key ways automation boosts customer centricity.

Automation Increases Self-Service Rates.

In many cases where customers contact support, their need is simple and human assistance isn’t essential. Conversational AI lets customers get answers to their questions quickly at any time of day.

Automation Helps Agents Solve Issues Quickly and Correctly.

The more efficient and effective the response, the better CX contact centres can provide. AI improves customer centricity by providing staff with real-time, intelligent guidance on the right next steps to resolve customer issues.

Automation Can Identify Causes of Customer Issues.

AI furthers customer centricity by automating the discovery of what causes customer issues. In turn, understanding the cause drives the improvement of automation to make contact centres even more customer-centric.

2. Meaningful Metrics from Customer Interaction Data.

In today’s digital world, data is essential to boost customer centricity for contact centers. To make decisions that enhance CX—and positively impact agents, managers, and executives—referencing real-time and historical data is critical.

Contact centres should use customer interaction transcripts and AI-driven analytics to gather CX insights. Then, they can foster a truly data-driven culture of continuous improvement by using the data findings to make more informed and customer-centric decisions.

Focusing on real-world data from customer interactions leads not only to better CX but also to more successful sales and marketing strategies.

Customer insights reveal the truth of what your customers think, what they expect from customer service, and what they expect from a product or brand, which are the foundations for campaigns that resonate.

For contact centres, AI will deepen the ability to harness interaction data and decrease the cost of data analysis to drive value. This means they can find the right data for automation and use that data to affect business and CX outcomes.

Unstructured speech and text are the largest human-generated data source for businesses that interact with thousands of customers every day. With more and more online interactions, this data source keeps growing.

The right tools—like no-code AI tools and language processing models—can tap into that data to extract value.

3. Interaction-Based Insights to Support Automation Practices and Understand Customers.

To provide a high standard of service, companies must understand customer needs. Even while using a data-driven approach to decision-making, it’s key to continue tapping into the wealth of knowledge and experience of contact centre staff.

Put interaction data to good use by gathering authentic customer insights that can help both staff and automation tools better solve their problems.

Automation using conversational AI can quickly gather customer intent and identify emerging issues using interaction data that is already available.

Whether customers are reporting website accessibility issues or explaining product defects, conversational AI can quite accurately point out patterns in customer calls to unearth critical business issues faster.

Extracting key, actionable customer insights from interaction data provides a foundation for making informed changes that truly improve CX as companies understand more about customer needs.

4. Customer-Centric Experiences from Start to Finish.

Automation tools help to minimize the effort needed to solve customer problems by prioritizing the speed and accuracy of support.

With customers growing ever more impatient and accustomed to immediate service, a truly top-notch and customer-centric experience needs to be flawless. This means minimizing customer effort and maximizing customer value.

Contact centres must embed customer-centric values through every part of the customer experience. Customer-centric automation must eliminate friction points in automation journeys and save valuable staff time by automating tasks that require low empathy or that handle high volumes of data.

Customers are the true drivers of business change, so organizations should be agile enough to adapt automation to customer trends.

AI-powered insights should constantly drive improvements in the automation experience. These improvements include customer-facing front-end automation, such as virtual agents, and back-end automation that drive workflows and business processes.

Moreover, changes to automation shouldn’t be delegated to the IT department. Rather, customer service teams should have the required tools to care for automation without needing technical skills or developer support.

5. Supportive Tools that Empower the Frontline to Resolve Issues.

The story of human productivity is a story about tools. Providing customer service teams with the right tools prepares them to face even the most complex challenges.

Beyond hiring experienced and intelligent staff, customer-centric contact centres must equip agents with tools that foster customer-centricity and cultivate innovation, like AI and automation.

Frontline staff should be a central part of automation design, testing, and scaling processes. Training frontline staff on the core inputs and outputs of AI and automation—removing the shroud of mystery—empowers customer-facing teams to bring ideas for improving automation. This diversity of thinking allows for better, more customer-centric automation practices.

Rather than heavily relying on data science teams for changes to automation, AI and automation training should be done in a non-technical way. As a result, contact centres can upskill customer support teams and turn them into powerful AI and automation champions.

Customer-centric organizations will always need to customize automation in new ways and train AI to learn new things. By making automation more observable and trainable contact centres can weed out biases and bad data to drive more value through automation.

6. Back-Office Engagement and Collaboration.

Customer centricity isn’t just the role of customer-facing team members. It’s a company-wide responsibility.

Being a truly customer-centric company demands effort and buy-in from all levels of the organization, not just educating frontline staff. Luckily, conversational insights can bridge automation gaps and improve CX functions well beyond the contact center.

Back-office functions need access to data-driven customer insights so that they, too, can drive AI and automation improvements.

These teams should also spend time on the frontline of the business to deepen their customer understanding and their appreciation of the contact centre’s efforts to drive customer centricity.

In addition, developing automation systems for back-office functions that integrate with internal tools, like Teams or Slack, can enhance collaboration and improve workflows.

One great resource to drive collaboration between the frontline and the back-office is a conversational AI-powered knowledge base. Central knowledge management lets the contact center create a unified environment to manage information that would be otherwise scattered across locations and systems.

Managing and centralizing knowledge can enhance collaboration and automation company-wide—and ultimately improve the customer experience.

7. Continuous Improvements Based on Customer and Staff Feedback.

Automation and frontline staff are the ultimate “power couple.” For both of these aspects of customer support, feedback is essential to creating a better CX. Monitoring customer interactions provides real-time insights that can help contact centers to resolve issues.

Automation tools can help agents to improve performance by analyzing and scoring customer interactions. Customer feedback can also offer insights to improve automation and further boost agent productivity.

Customer-centric automation needs the input and feedback of those who make up the contact center: agents, supervisors, admins, and managers.

Rather than depending on outsourced help from those who are far away from customer service, truly customer-centric companies must democratize the settings and changes to automation by empowering non-technical staff to make those changes.

Making frontline teams the custodians of automation can unlock the diversity of thinking to improve automation performance and the customer experience.

Customer-Centric Automation Wins in a Variety of Ways.

Automation through conversational AI brings a wealth of benefits, unlocking reduced costs, higher revenue, and better customer satisfaction. But it can also support business outcomes in the face of staffing shortages by saving time and boosting productivity.

What’s more, customer-centric automation will lead the way to the next generation of customer support: Gen Z. This up-and-coming portion of the workforce will demand that workplaces use technology for more efficient and innovative workflows.

AI and automation don’t signal the end of incredible customer service. On the contrary, customer-centric automation is the future of CX.

This blog post has been re-published by kind permission of Talkdesk – View the original post

To find out more about Talkdesk, visit their website.

About Talkdesk

Talkdesk Talkdesk is a global customer experience leader for customer-obsessed companies. Our contact center solution provides a better way for businesses and customers to engage with one another.

Read other posts by Talkdesk

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Published On: 24th Nov 2022
Read more about - Industry Insights,


Recommended Articles

Person stopping domino effect and avoiding mistake
Avoid Common Automation Mistakes When Using Conversational AI – Part II
mistakes to avoid is written on a white sheet of paper that lies on a colored background among stationery
Avoid Common Automation Mistakes When Using Conversational AI - Part I
A picture of a robot thinking
Customer Service AI: Where Are We Now?
Get the latest exciting call centre reports, specialist whitepapers and interesting case-studies.

Choose the content that you want to receive.