The Gist

  • Everyone is all about AI. But how can CX leaders ensure their AI investments have impact?
  • Ensure AI excellence. Five steps CX leaders can take to show their worth with AI.

Delivering a superior customer experience is a critical aspect of building and maintaining a strong brand reputation. As a result, CX leaders are increasingly exploring the potential of artificial intelligence (AI) to help achieve this objective. However, the true value of AI lies not only in its implementation, but also in the ability to demonstrate how it can positively impact customer experiences.

To ensure that impact, what steps should customer experience leaders take to ensure their AI is utilized effectively? We connected with CX leaders from various industries to find out. Based on their insights, five key strategies emerged.

1. Define Your CX Objectives: Key to Success in AI

For years, Customer Management Practice (CMP), the adviser network behind Customer Contact Week (CCW), a premier customer contact event, relied solely on its human workforce to register thousands of attendees.

"These were smart, talented people that spent hours doing data entry work that could have easily been done without human assistance,” said Mario Matulich, president of CMP. “The simple adjustment to deploy some basic self-service and automation not only removed a friction point for our customers but for our employees as well. These same people were able to then turn their attention to higher-value work that helped us grow the event series exponentially.”

Founded in 1999 as Call Center Week, CCW will host its 25th-anniversary event in June.

Matulich figured it out. CCW’s objectives were to remove a customer friction point and free up staff to focus on more important work, enabling them to make the event bigger and better.

With these objectives in mind, AI-enhanced automated event tech fit the bill.

The first step for any brand is to identify the specific areas you believe AI could help improve the customer experience — anything from reducing customer wait times, to improving response times or better personalizing the customer journey.

“In order to choose the best way to implement AI into your organization, you must first define your CX goal,” said Abdul Saboor Khan, head of marketing at Your PCB, a printed circuit board assembly factory. "Do you want to boost sales, client satisfaction, loyalty, or retention, for instance? Would you like to lower expenses, turnover, or complaints? You must establish precise, doable goals and keep tabs on your development.”

Related Article: Hyper-Personalization: How AI & ML Are Building a New Framework for Ecommerce CX

2. Identify the Right AI Tools for CX Success

Once you've identified your CX objectives, you need to find the right AI tools to achieve them, such as chatbots, voice assistants, predictive analytics and machine learning algorithms. It’s important to choose the tools best suited to your individual business needs.

For Piyush Tripathi, senior engineer at Square Inc., the team's CX objectives were to reduce customer churn, decrease average tickets opened, improve resolution time and provide support during off hours.

"To achieve these objectives, we implemented an in-house chatbot powered by ChatGPT 3.5 Turbo and used Google Analytics to track metrics. We also utilized machine learning algorithms to detect unusual patterns during holidays," Tripathi said. "As a result, our customer satisfaction increased by 43%, churn reduced significantly in Europe, and average tickets opened decreased."

Tim Clarke, senior reputation manager at Rize, an online reputation management company. said defining CX objectives is crucial to delivering top-notch customer service. He believes reducing customer wait times, improving response times to customer queries and personalizing the customer experience are some of the most common CX objectives that businesses aim for. And to achieve these objectives, AI tools such as chatbots, voice assistants and machine learning algorithms can be incredibly useful.

"Chatbots are perfect for reducing wait times and improving response times since they can handle multiple customer queries simultaneously, 24/7. Voice assistants like Amazon Alexa and Google Assistant can also personalize the customer experience by remembering previous interactions and preferences, making customer engagement more natural and efficient," Clarke said. "Machine learning algorithms can help businesses analyze customer data to predict customer behavior, preferences, and needs, which can, in turn, result in more personalized customer experiences. These AI tools can significantly enhance a company's CX strategy, resulting in increased customer satisfaction, loyalty, and revenue."

Alex Alexakis, chief experience officer and founder of the SEO web design firm, PixelChefs, finding a generative AI tool to assist with email marketing campaigns was a priority. His company now uses content generation and optimization tools to create and improve the subject lines, headlines, body text, images and call-to-actions of emails. To segment customers and personalize email content based on preferences and behavior, they integrated predictive analytics and machine learning algorithms.

“We also use A/B testing to compare the performance of different email variants and optimize them accordingly,” Alexakis said. “By using generative AI tools, we have been able to increase our email open rates, click-through rates, and conversion rates significantly.”

3. Ensuring CX Excellence: Putting Your AI Tools to the Test

Before deploying your AI tools to the wider customer base, Alexakis says to test them with a small cluster of clients, gather input from users and fine-tune the tools until they're ready for a broader rollout.

“We test them with a small group of customers who have opted in to participate in our beta testing program. We collect feedback from them and refine the tools until they meet our quality standards and expectations,” Alexakis said. “We monitor our AI performance closely using various metrics such as response times, customer satisfaction scores, conversion rates, retention rates, churn rates, and net promoter scores. We also use dashboards and reports to track the progress and impact of our AI tools on the customer experience. We constantly evaluate and optimize our AI tools based on the data and feedback we collect.”

Learning Opportunities

Dan Charles, CEO and founder of the digital marketing agency, Codarity, said testing is a critical stage in the development and implementation of AI tools, making it possible to identify problems and possibilities for improvement quickly. He agrees that it’s frequently advantageous to test AI products with a smaller sample of clients first to detect any problems or potential improvements before rolling them out to a larger customer base.

“A common approach is to run a beta test with a select set of clients who are willing to offer feedback on the effectiveness of the AI technology. To find any problems or potential areas for improvement, this input can be gathered through surveys, focus groups, or one-on-one interviews. The beta test data can be utilized to improve the AI tool and make sure it is prepared for a wider rollout,” Charles said. “Another strategy is to compare the performance of the AI tool to a control group that does not utilize the tool using A/B testing. A/B testing can assist in determining how the AI technology affects the consumer experience and any areas that require improvement.”

Related Article: What Defines World-Class Customer Service Now and How to Get There

4. Track the CX Impact of Your AI: Monitor Performance

Once your AI tools are in use, monitor their performance closely. Use metrics such as response times, customer satisfaction scores and conversion rates to measure the impact of your AI tools on the customer experience.

Depending on the use case and key performance indicators, there are various techniques to monitor AI performance, said Jesol Umeria, CEO of the footwear retailer, Wide Fit Shoes.

There are machine learning algorithms, utilizing metrics like accuracy, precision, recall, F1-score, AUC and ROC curves to judge how well they can categorize data and to assess the effectiveness of AI systems. In addition, Umeria said, other data, like response times, customer satisfaction ratings and conversion rates, can be utilized to assess the effect of AI technologies on the customer experience.

“Response times and customer satisfaction ratings, for instance, can be used to track the efficiency of an AI-powered chatbot deployed to address consumer inquiries, conversion rates can also be used to gauge the effectiveness of an AI-powered product recommendation system that is being utilized to increase sales,” Umeria said. “Overall, it is crucial to keep an eye on how AI systems are performing to make sure they are achieving the desired goals and providing consumers with value. It enables speedy problem-solving and the possibility to tweak things for better performance.”

Ryan Faber, founder of Copymatic, an AI-powered content platform, said his company’s main focus for tracking progress is to monitor conversion rates.

“My business's premise is about dealing with clients and consumers by learning what they like; our goodwill relies on customer retention. Through AI, managing and delivering have become more accessible,” Faber said. “A mere piece of content doesn't win you much in this competitive market. AI's efficiency in working at the speed of light has given us more time to interact with our consumers by reviewing feedback and even talking directly, if possible.”

5. Communicate Your CX Success With AI

Finally, communicate the success of your AI initiatives to stakeholders. Use data to demonstrate the impact of AI on the customer experience and highlight any cost savings or efficiency gains that have been achieved.

“Our approach to communicating success is primarily internal. We utilize the results from A/B tests to showcase the impact of our AI initiatives on the customer experience. We also highlight any cost or time savings, as well as reductions in churn and support tickets,” said Tripathi. “While we don't directly communicate these successes to our users, we prioritize sharing them with our stakeholders.”

Leo Ye, CEO and co-founder of Cubo, a client engagement platform, said, in the current digital era, it is becoming more and more crucial to incorporate AI into your CX leadership strategy.

“Start by investing in your own education on AI and how it affects the customer experience if you want to establish your value as a CX leader. Learn about the most recent AI tools and technologies and how they might be used in CX. Create a roadmap for AI integration with your team, starting with modest test projects and progressively expanding them,” Ye said. “Finally, make sure to let important stakeholders in the company know how successful your AI projects have been by emphasizing the positive effects on client retention, revenue, and happiness.”