What is AI's potential when it comes to customer experience?

Businesses need one essential ingredient to flourish—happy customers. Regardless of whether a company delivers the perfect product, or provides an ideal solution, unhappy customers vote with their wallets and their time. If customers discover a better experience elsewhere, they probably won’t stay loyal to your brand. 

Customer experience (CX) is a critical aspect of customer retention, loyalty, and brand advocacy. So how do you keep customers satisfied? 

With the global rise of AI, delivering on the promise of CX may be simpler and more powerful than ever before. 

An artificial intelligence customer experience can help stakeholders understand their customers better, personalize the experience, streamline the buyer journey, create a safer online environment, and boost decision-making for better business outcomes. 

AI can improve CX via various tools and technologies. Some of these tools include: 

• Natural language processing (NLP): A subset of AI, NLP is a process by which AI tools can interpret, understand, and generate human text.

• Chatbots and virtual assistants: Through the power of NLP, chatbots and virtual assistants can understand text from customers and offer recommendations, answer questions, and assist without the need for human intervention.

• Sentiment analysis: AI-led algorithms can analyze large data sets to spot patterns and trends. This can highlight overall customer sentiment, spot themes, and help organizations address a low or neutral view of the organization as well as issues impacting their customers.

• Voice recognition: Some AI tools can recognize human voices, enabling voice-activated search, voice controls, and verbal responses. This can improve inclusivity in the customer experience.

• Social media monitoring: Some algorithms monitor social media platforms. They review responses and provide insights on recurring comments, overall sentiment, and common issues arising within a community.

• Process automation: Through the automation of various tasks, some of the data collection, feedback gathering, analysis, and insights processes can be automated to improve efficiency and accuracy. 

In organizations, AI customer experience tools are proving highly effective for boosting CX. They improve CX in the following ways:

1. Deeply understanding the customer 

To deliver a positive customer experience, teams must deeply understand their customers. That way, they can better understand their pain points and create products to solve them. 

Through continuous research into customers' preferences, behaviors, and issues, businesses can learn more about their customers. 

Practices such as focus groups, usability testing, surveys, A/B testing, behavioral analytics, and more are conducted to discover more about customers and what they want and need from products. AI tools can fasten these research processes—helping teams to collect, store, and analyze big data from multiple sources. This can help stakeholders to make better decisions that put the customer first. 

2. Personalization 

Personalization is something that customers now expect. Research has shown that 74% of customers are frustrated if a website’s content isn’t personalized. And personalized recommendations in shopping carts influence 92% of shoppers.

Via the use of algorithms, some AI tools can analyze behavior patterns and customer data—this leads to insights into customer preferences, granting organizations the power to personalize the experience for individuals.

Companies may offer personalized experiences through unique product recommendations, personalized email sequences, or specific customer journeys, to name a few. These experiences are more likely to increase customer satisfaction while also boosting conversions. 

3. Simplicity, efficiency, and productivity

Across the board, AI tools have the power to streamline many CX-related processes, fasten the rate at which tasks are completed and issues are resolved, and increase productivity for teams. 

The boost in efficiency can have positive flow-on effects for customers. For example, utilizing the power of natural language processing can help produce chatbots that answer commonly asked questions in real time. 

Customers will likely be more satisfied as they can resolve their issues much faster. Meanwhile, the process frees up human time to deal with more complex customer issues, thus delivering a better overall experience. 

4. Quicker, more confident decision-making 

AI tools also have the power to improve decision-making for the benefit of customers. By using advanced algorithms, AI tools can analyze big data, spot trends and themes, and discover more accurate insights. 

Specifically, algorithms can be used to boost predictive analytics. By analyzing historical customer data, a tool may be better than a human at predicting future behavior. That’s because manual processes are both sluggish and leave room for error. 

5. Streamlining the customer journey

AI customer experience can also offer a more relevant, personalized, and streamlined buyer journey. Through AI-led customer segmentation, the purchase funnel can be customized to provide relevant recommendations and increase the overall chances of conversion. 

As AI progresses, dynamic pricing may also be used to analyze market trends and competitors’ pricing alongside customer behavior to offer competitive prices that are more likely to convert in that specific period. To ensure customers have the support they need, chatbots can assist throughout the AI customer journey to help customers discover any additional information they need. 

6. Fraud detection 

Online safety, the risk of fraud, and scams are of growing concern globally. In 2022, Americans lost $8.8 billion to scams and fraud—a 30% increase on 2021 figures. Through 2.4 million reported scams, individuals lost an average of $650 each. 

Fraud protection is something that customers may be more interested in than ever before. Ensuring systems are safe is a critical aspect of offering positive CX. Through AI-powered abilities like anomaly detection, behavioral analytics, and network analysis, AI tools may be able to detect fraud more quickly and effectively than humans can. 

7. Self-service availability 

Advanced AI technology can also be used to help customers resolve challenges, discover information, and gain recommendations without the need for human presence. 

Here are some examples: 

• Virtual assistants can offer relevant advice based on a customer’s preferences and behavior, helping shoppers find relevant products. 

• AI tools can continually update knowledge bases in alignment with frequently asked questions and common behaviors. This ensures customers can find the answers to their questions faster than ever. 

• Automation tools can also power self-service analytics to enable customers to see their personal insights and engagement. Whether on a social media platform or e-commerce site, customers could gain the chance to see their analytics in real time with greater insights than before. 

• Natural language is something computers can now understand at an alarmingly intelligent speed. In some circumstances, customers in need can now ask and make requests to bots with little to no need for human intervention.

8. Visual, text, and voice engagement

To help organizations communicate with their customers in the ways that suit them best, AI can boost the types of contact methods. This can ensure organizations are accessible to diverse abilities, learning styles, language levels, cultural backgrounds, and more. 

Voice recognition can help customers navigate a product, website, or app via voice control. Natural language processes can power chatbots for virtual assistance when the customer needs it. And visual search features powered by AI can also increase accessibility and searchability for customers to find what they need faster.

While we can’t deny the power of the AI customer experience, it’s important to recognize there are limitations when it comes to AI use. 

AI tools are commonly limited in many areas, including:

• Context

• Empathy

• Accuracy

• Flexibility

• Creativity

• Nuance

Also, the learning models of today’s AI tools are largely based on human actions and histories. Radical thinking, stereotyping, and other dangerous miscalculations are always a concern. 

With these limitations in mind, human reasoning still appears to be an important aspect of many jobs, and, at present, AI isn’t a perfect replacement. 

While AI is largely in its infancy, the promise of tools boosting CX offerings isn’t a future goal but something companies are already using.  

Some key industries include: 

Retail

The supply chain is an incredibly complex process that’s notoriously hard to manage. Retailers face various common issues—manufacturing, warehousing, shipping, replenishment, and demand fluctuations—many of which can be managed via automation. 

AI in retail can, in some cases, more reliably predict aspects of customer behavior like product demand, buying patterns, seasonal changes, and customer churn, which helps boost decision-making and increase customer satisfaction. 

AI algorithms can even help predict manufacturing issues—such as the likelihood of a machine needing repair or replacement—to avoid the flow-on effects of pauses and slowdowns. 

Healthcare 

In healthcare, CX may help boost patient personalization, remote patient monitoring, and drug discovery, as well as help streamline workflows for patients and medical professionals alike. 

For example, through AI-enabled wearable devices, patients’ vital signs can be monitored remotely. If issues arise, the AI tool can notify their doctor. This can take pressure off hospitals and doctors' surgeries to get medical care where it’s needed most. 

Mobile banking and finance 

Fraud is a major concern for many, so financial firms are using AI and machine learning to improve their services and products. 

Through aspects such as anomaly detection, behavioral analytics, network analysis, and real-time transaction monitoring, AI tools can act as more advanced detection systems than human-only assessments. This means protecting customers’ personal information and increasing their loyalty and trust in organizations. 

Marketing

AI-driven tools can streamline the marketing process too. Chatbots, for example, can be used to deploy consistent messaging across a broad range of touchpoints. This ensures that whether the customer is interacting with a business through the website, app, newsletter, or social media platform, there’s an aligned experience. 

If you want to use AI to improve the customer experience, follow these best practice steps: 

1. Design a CX strategy

Any implementation of AI should begin with specific goals as part of an overall strategy. This will ensure you implement systems that help your organization reach targets and solve the problems you have as a team. 

2. Plan and analyze user journeys

Mapping out user journeys will help your team identify the key areas that need to be analyzed and streamlined, ensuring your AI solutions can address them. 

3. Have a clear understanding of AI solutions

Before onboarding AI tools, you should deeply understand the potential AI solutions. In most cases, it’s best to build slowly, ensuring each element is working well before adding more. 

4. Decide whether to create/buy AI solutions

Some AI tools may be better produced in-house by qualified teams rather than outsourced to external companies. If your team has the ability, this can give your organization a leading edge. 

5. Measure success

No solution is complete without an accurate way to track and measure success. Analysis is an essential part of business improvements and should be completed continuously to understand how tools are benefiting customers.

While no one can conclusively predict how AI will impact CX, there will likely be broad changes across the sector. 

We expect to see companies offering a high degree of personalization, significantly faster virtual support, streamlined buyer journeys, consistency across all messaging platforms, improved accessibility, and products that are continually evolving based on sentiment and feedback—all powered by advanced AI tools. 

While the tools hold enormous potential, there are cautions too. AI tools cannot replace the critical work humans do. Essential factors such as context, nuance, creativity, and reasoning are still needed to manage and oversee such advancements. In addition, it’s important to recognize the novelty and relative newness of AI. 

For the near future, it’s recommended best practice to include human-based analysis to cross-check AI results to verify responses and develop understanding.

Together, AI and humans may radically change CX for the better.

Some AI-powered tools make use of natural language processing. This can provide continuous support to customers through human-like conversations, personalized interactions, and support across multiple channels. 

Where the barrier to entry into technology before was basic knowledge of how to use and communicate with tech, this can now be done through the natural language any human possesses.

For example, in online shopping experiences, virtual assistants can offer advice based on a customer’s preferences and behavior, which can help shoppers quickly find relevant products. 

Amazon is an example of a company using AI to boost CX in various areas. Some examples include: 

• Amazon’s recommendation engine—which produces relevant product recommendations—is powered by AI algorithms. 

• AI algorithms are used by Amazon to create efficiencies in the supply chain, such as in warehousing and fulfillment. 

• Voice assistant tools, Alexa and Echo, also use AI-powered voice features to understand and respond to requests from people. 

Instagram, owned by Meta, is using many AI tools to improve user experience. Some key examples include: 

• Instagram’s Explore page uses AI algorithms to provide relevant recommendations for users. 

• Accessibility is boosted on Instagram through AI-enabled text generation for visually impaired users. 

• AI also plays a role in online safety by filtering comments and accounts to highlight cases of spam, abuse, or harmful material.