Five Ways AI is Transforming Customer Experience for Brands in 2023

Creating personalized Customer Experience for brands continues to be an important facet for every client-first businesses. Customers constantly look out for services and products that closely align to their expectations and meet all of their expectations meaningfully. However, despite doing everything humanly possible, brands are failing to reduce customer churn and increase brand affinity. Where humans fail, technology picks up, and how!

The use of Artificial Intelligence (AI) in delivering customer experience (CX) to loyal users is at its peak in 2023. New buzzwords such as Generative AI and robotic process automation for contact centers have the power of completely eliminating trial-and-error methods for delivering customer experience to omnichannel users. In fact, AI has so much firepower in its arsenal today that it could truly improve “quality of life” of both customers as well as CX agents who are responsible for facing happy and disgruntled customers using the same set of digital tools and platforms. While AI is creating a wealth of opportunities for CX-driven brands in its current form, there are more ways it could be used to further improve the engagement rates with better and faster personalization in a more intuitive way.

Recommended: Unlocking Generative AI for Marketing and Sales

Understanding how artificial intelligence makes an impact on any CX-centric brand is worth a read. We have done our bit in highlighting the role of AI in CX in these five areas of application.

1. AI to Reduce Customer Churn

Organizations lose billions of dollars in revenue due to shift in their loyal customer base who switch to competitors in search of better customer experience and service. 

Some level of churn is expected every year. However, if your churn is more than 50% and your competitors are growing their customer base, it is likely that your business needs a proper churn analysis and retention management to prevent loss of revenue in the near future. We are not talking about AI’s role in doing mundane administrative tasks, but total digital transformation of your inside sales and outbound marketing with AI-based churn analysis.

Big Data analytics, powered by AI data management also bring down churn rates through sentiment analysis measured by reading social media posts, email responses, collecting voice samples and reactions to online posts. AI not only helps in identifying customers using behavioral and sentimental cues, but also filter these segments into groups that can be targeted with intelligent content and gamification tools. This is how organizations can reduce churn using Amazon Machine Learning.

Check this put to learn more about AI ML initiatives at Zendesk

Churn analysis with AI is at the center of every customer behavior. Predicting churn and retention ratios at the start of every quarter help brands to scale their efforts accordingly. In fact, brands dependent on AI use business intelligence tools to accelerate their go-to-market efforts around churn reduction. AI’s predictive intelligence is at play across many brands to reduce customer churn and increase brand loyalty.

With access to high-quality data and knowledge, brands can greatly improve prediction accuracy and discovery rates.

• How fast did the customer find your product from the search or recommendation button?
• Was the customer service agent successful in resolving customer queries?
• How much time did it take your customer support team to satisfy the disgruntled customers?
• How many customer issues were fixed as part of First Call Resolution? 

AI helps answer all these questions and many more within a fraction of few seconds. Saving time with accurate answers enables any brand to grow quickly with transparent and accurate CX outcomes. From Zendesk’s definition of CX itself we can understand that the ultimate goal of focusing on experience is not just helping with more sale or purchases.

In fact, brands are using CX strategies to go beyond sells and purchases and grow Net Promoter Score (NPS) to identify their internal strengths and weakness in a competitive market where every other organization is using some or the other tool and platform for CX management.

Companies such as Salesforce and Treasure Data are leading through the Age of CX with highly personalized AI-powered CRMs and CDPs. These gather and analyze key information about every customer and how their conversations with your CX and customer service agents shaped the relationship toward the next sale, abandonment or termination.

2. Omnichannel Service to Customers 24×7

Companies that showcase CX as an extension of their customer service are likely to retain customers, and also turn these into loyal ambassadors who bring in more customers with “voice of customer” initiatives.

According to NTT, nearly two-thirds of the business operations could be automated completely with AI. Customer support is one of them. Customer support is one of the biggest adoption centers for AI applications. Having a solid omnichannel customer service increases the chances of delivering a positive CX. There are many companies that use AI-powered applications for generating omnichannel customer experience. One way to do this is by creating a call center workflow that is available for resolution of customer queries every time.

In a recent interview with us, CTO of Iterate.ai Brian Sathianathan said, “Retailers are using AI/ML to ensure that customer experiences are not only personalized but also contextualized, able to understand and address customer needs in the moment with more granular personalization. AI/ML further automates the work of iteratively improving and optimizing those customer experiences. Other AI/ML use cases can cover everything from smart chatbots, to frictionless shopping experiences, to assessing health risks, to public safety.

Organizations often leverage low-code to pair AI/ML with big data and IoT capabilities, with powerful results. On IoT factory floors where downtime losses can almost-instantly reach into the six-figures, AI/ML, big data and IoT technologies combine to offer preventative maintenance that anticipates issues and avoids those major costs. In other use cases, these technologies are also frequently applied to optimize international supply chain logistics, and can even support real-time security video analysis able to detect weapons and other localized threats at schools and businesses.”

Whether you are an international MNC, or a local service provider, you need a contact center that functions 24×7 and is available for customer requests round the clock. In the era of hybrid and remote working, this is a huge challenge for CX-centric brands that are not only facing churn in their promoters and customers, but also among its employees. Having a Chatbot-based contact center is a good start to your CX goals that allows you to listen to your disgruntled customers when they call your customer support. Zendesk’s Content Cues runs on Machine Learning to identify discoverable assets and resources specifically designed for your agents who have to answer same or similar types of queries from the callers.

In an email statement shared with AiThority.com editorial team, Adrian McDermott, Chief Technology Officer, Zendesk mentioned the role of creating seamless and intuitive experiences across industries and organizations with Artificial Intelligence. Adrian said, “AI experiences have become more evolved, seamless and increasingly important across industries and companies of all sizes. In fact, nearly two-thirds (62%) of APAC leaders and managers believe AI or bots will drive large cost savings over the next few years, and 68% have indicated AI and chatbot integrations as one of their top operational priorities.”

3. Conversational AI’s Emergence in CX Management

A large number of customer support teams now consider conversational AI as their go-to tool for managing customer experience. Like how brands are using data to learn more about customers, the customers are also seeking more clarity on how their data is being collected by brands. When brands specify that customer data is collected to improve customers, it’s a win-win for both parties. 

The use of programmatic tools for chatbots and virtual assistants are sweeping customer experience trends in 2023. The greatest benefit of using AI for customer experience-centric brands is the differentiated engagement it offers to every customer without sounding too “machine.” For example, IVRs. Customers who have similar queries as others need not wait for too long for resolution. The rise of voice-based CX is important event in the whole CX journey management. Customers prefer to shop with brands that have a faster speed of resolution that can save more time for them when doing business more than once.

Conversational AI such as AI chatbots and NLP-powered virtual assistants are imitating human interactions, and in some cases, even replacing the need for human agents within the customer relationship management lifecycle. Conversational AI is a great tool for call centers that receive thousands of customer queries in a day, and need technology to filter “important calls” from peculiarly repetitive ones.

Two ways conversational AI benefits your organization:

1. It improves NPS with superior CX personalization goals
2. Conversational AI in sales processes increase revenue generation within very short time, leading to increase in customer acquisition and reduction in churn.

One thing leads to other in conversational AI. Every data that is extracted from millions of calls and emails shared between the customer and brand helps in building a much stronger foundation for NLP-based voice analytics. This empowers CX agents in creating a future-ready call center using a highly-differentiated conversational AI.

4. Self-service Automation

Intelligent Automation (IA) and Artificial Intelligence (AI) are inseparable entities when meeting customers online with superior CX features and personalization.

Self-service automation with artificial intelligence adds value to the overall CX management plans. Firstly, you could cut down costs of running a full-sized contact center by automating whole or part of customer service workflow. Businesses can cut down up to 70 percent of costs with self-service CX plans that align with overall brand health.

Secondly, you offer more control to customers who can pick and decide their own CX roadmaps. Both these advantages help in building personalized CX journeys with automated knowledge management, content generation and conversational dashboards.

But, can AI alone deliver on CX expectations with self-service automation?

No, as per Adrian. Adrian explained, “Implementing AI is not a one-and-done initiative. Instead, businesses need to think of AI as an ongoing partner – one that continuously complements their employees’ efforts to collectively drive productivity and elevate the customer experience. AI’s beauty lies in the never ending learning journey by both machines and humans. Continuing to find new ways to assist the human workforce with AI will allow for a better use of resources, improved productivity and, ultimately, a better experience that will have customers coming back for more.

Moving beyond initial implementation means developing a broader AI strategy and roadmap that see AI and chatbots as an essential technology across every stage of the customer journey. For this to succeed, businesses need to invest in maximizing the opportunity to truly expand AI’s reach to more than just basic, reactive actions.”

5. Artificial Intelligence Payments Management

• How convenient is your payments processing and transaction management page?
• Do you ask the buyer to create an account before they can make the purchase?
• Does your page take more than 30 seconds to checkout from the shopping cart to payments processing page?
• Is your pricing model clear to the buyer?

All these and much more influence the customer experience! Good thing, all these are manageable by AI.

CX is measured not just in quality of service, but also in time and effort taken to fulfil the order. It links to Customer Effort Score (CES). Consumers are spending more time figuring out how to complete the payments process than what they would spend for actual shopping. A faster mobile transaction is what customers are expecting from their brands. If the page takes more than 30 seconds to load, 50% of your buyers would bounce to a competitor’s site.

In some cases, trust is the biggest challenge for shoppers, because they do not trust online payments process at all due to security issues. Nonetheless, payments processing is the ultimate frontier for CX managers- – closing sales with confirmed payments always has been that way, right?

The success of CX is the rate of completed transactions by customers. Abandoned carts and payment failures are the biggest nemesis of any business order. E-commerce sites are the worst hit businesses. They lose up to $18 billion due to abandonment. According to a research, mobile and tablet users make up the largest number of dropouts at the payments stage. Compared to these smart device users, desktop users find it easier to shop and transact with sites that offer payments link.

Losing sales opportunity is still recoverable at a later stage, if the customer chooses your brand after returning to the site. You can still show them the journey they had experienced and retarget with the products they have left in the cart. But, what if the customer never returns and worse, chooses your competitor with better CX to fulfil the needs.

Only 8% opted for a physical brick-and-mortar option to fulfil the order. Others either returned to the same site, or found a different seller altogether.

AI for payments processing acts as a recommender engine for buyers who could choose a payment option depending on their last choices — BNPL, credit card, COD, or mobile wallets payments.

How to use AI for creating personalized CX journeys for everyone?

To answer this question, Adrian gave example from Zendesk’s recent AI campaigns. Adrian said, “One way of doing this is to ensure that AI touchpoints are expanded into more proactive stages of the customer journey. In the context of developing a broader AI-enabled CX strategy, businesses can use AI to leverage industry expertise and insights from customer data points and apply a vertical lens, creating custom models capable of identifying the intent, language and sentiment of each customer interaction. For instance, our recently launched Intelligent Triage and Smart Assist features offer new AI solutions that empower businesses to triage customer support requests automatically, leveraging valuable intent and sentiment data at scale. This also allows businesses to instantly route and prioritize certain interactions, ensuring agents are working on business-critical requests.

The adoption of AI and its use cases within CX will continue to expand, particularly as the technology continues to evolve. Businesses that evolve AI with additional data insights, like intent and sentiment, can accomplish deeper personalization and build greater trust. This has a ripple effect, whereby customer retention increases and customer acquisition costs decrease in the long run. Take Thunes as an example. The global payments infrastructure company made use of smart automations and custom dashboards using data on customer interactions and employee performance to deliver faster responses and a higher quality of service. And it doesn’t stop there for them – they have big plans to look for ways to improve productivity, and deliver a more personalized, proactive customer experience.”

Conclusion

The CX market continues to evolve with AI and machine learning, and with tools like ChatGPT4 readily available for testing and experiments for customer support, the demand for AI would further increase. AI could be a costly tool to deploy, maintain and train. However, if you have a clearer agenda for your CX management with AI-powered contact center and AI-powered CRM software that integrates with your sales and marketing, you can make a great impact on your bottom line.