Excellent Ways AI Will Improve Customer Experience in This Year
A Gartner study finds that by 2025, artificial intelligence will empower 80% of customer service and support processes. This surge demonstrates how AI will be essential in shaping the future of customer experience (CX).
With customers demanding faster and more personalized support from their brands, meeting these needs without AI will be challenging.
With AI integrated into your customer support and service system, you can automate responses, provide personalized recommendations, and transform customer interactions. By leveraging tools like CallFluent, businesses can streamline communication processes, enabling faster and more efficient resolution of customer queries.
In this article, we are going to discuss 7 excellent ways AI will improve the customer experience in this year and beyond:
Understanding the Integration of AI in Customer Experience
AI enhances customer interactions via quick and accurate service responses. To deliver its intended solutions, AI works with machine learning, natural language processing (NLP), predictive analytics, and robotic process automation (RPA).
By analyzing vast data points like browsing habits, purchase history, buying behavior, and social media activity, AI crafts tailored experiences.
It also incorporates market trends and historical data to predict customer needs, ensuring that each interaction is uniquely personalized.
Relying on data, AI-powered tools let you adapt your services to align with customer preferences, creating more meaningful and engaging experiences that strengthen brand loyalty.
7 Ways AI Can Improve Customer Experience in the Years to Come
The application of AI may differ across organizations, but it presents valuable opportunities for businesses of all sizes to elevate their customer experience. Here’s how AI can improve customer experience in 2024 and beyond:
Personalized Recommendations
AI uses sophisticated machine learning models and algorithms like collaborative filtering and deep learning to analyze large datasets.
This data includes:
- Customer’s past purchase history;
- Behavioral cues;
- Time spent on browsing;
- Time of the day they purchase usually;
- Devices customers use.
Based on this data analysis, AI algorithms not only tailor product recommendations but also facilitate dynamic content display. It can adjust the application interface to show the most relevant content and products that align with each individual customer’s interest.
For an eCommerce application, this means suggesting products based on the data points we mentioned above and what other customers have bought with similar preferences. Personalized recommendations improve a customer’s shopping experience and increase conversions.
Source
Here are some personalized recommendations in action:
- Amazon customizes its application homepage according to customer preferences, notably product suggestions and promotion offers.
Check the “Inspired by your shopping trends” and “More top picks for you” sections. These are the items a customer may not have bought, but according to Amazon, they may need them now or in the future.
- Netflix’s recommendation engine provides suggestions on movies and TV shows based on customers’ viewing history and preferences. This has helped Netflix achieve a customer satisfaction rating of 89%.
For Netflix, the “Top Picks for Joshua” and “Because you watched Narcos” is a prime example of personalization. It offers the customer to watch shows based on their past watch history, interests, and preferences.
- Starbucks customizes its offers and promotions section for every customer based on their preferences and purchase history.
Just as every other personalization engine works, Starbucks collects data on their customer’s purchase history, store preferences, and visit frequency.
Based on this information, they tailor the application page to add what they deduce to be the customer’s favorite items and change them according to the time of the day. This fuels their Bonus Star program offering customers rewards for repeat purchases.
Growing companies generate 40% of their revenue from personalization as compared to their competitors. This certifies that customers are more likely to make a purchase with personalization as it enhances their experience.
Building a Loyal Customer Base
Brands must focus on delivering exceptional customer experience, which leads to higher sales, better customer retention, and long-lasting loyalty.
Given that 73% of your customers may leave after a single bad experience, it’s crucial to achieve customer satisfaction.
AI can significantly help you improve customer experience by leveraging technology and data analysis. Through this, you can create a customer-centric service system, ensuring they are always engaged, heard to, and satisfied.
[Vineet Gupta, Founder of 2XSaS]
AI-driven predictive analytics is a proven game changer for customer retention and through retention, building a loyal customer base. Customer behavior analysis in real-time means brands can anticipate their future needs and curate a bouquet of customer-centric solutions.
Having received these services even before they ask for it increases a brand’s perceived value in the customer’s eyes. As a result, they will continue to stick with the brand for a longer period, effectively increasing the customer lifetime value (CLTV).
Sephora, for instance, enhances customer experience through its AI-driven Beauty Insider Loyalty Program. Using customer’s purchase habits, product preferences, and skin type, AI predicts what customers might need next.
Customers receive notifications for replenishment reminders of their favorite product or when new makeup items launch similar to the ones they bought before.
Customers who regularly purchase foundations have their data analyzed on the average period between two purchases.
Using this data, Sephora sends restock notifications and recommendations to buy additional products. As a result, customers have a convenient shopping experience and feel cared for, which increases the likelihood of repeat purchase.
Offer 24/7 Customer Support with Chatbots
Salesforce research shows that 75% of customers agree to do business with a brand again, even after a mistake, provided they receive excellent customer service. This shows the importance of top-tier customer support services.
AI driven customer support means you can be available for your customers 24/7, allowing you to meet their demands around the clock.
With conversational AI, you can build digital agents to facilitate human-like interactions with your customers. Chatbots, for example. can provide instant and personalized assistance, increasing customer experience.
AI-powered chatbots can analyze customer data and provide personalized recommendations. They can help choose a product, book appointments with a specialist doctor, or simply guide customers in making a decision.
Have a look at Decathlon's chatbot that is programmed to help people make a buying decision. It asks customers their requirements and helps them make a decision based on answers.
AI empowers customer support agents & chatbots to manage a large number of customer queries, effectively reducing customer service costs and improving customer experience.
A CFPB report cites chatbots can save $0.70 per customer interaction when the same work is done by a human agent. Hence, chatbots are saving over $8 billion annually by participating in customer service and support processes.
Use Sentiment Analysis to Understand Customers and Predict Churn
Utilize sentiment analysis to know your customers better. As you analyze their online interactions, reviews, survey feedback, and social media mentions, it’s easier to gauge the emotional tone behind their words.
By analyzing this data, AI tools can predict potential negative experiences that might not be apparent.
Use this data to identify areas where the customers feel positive and where they express negative thoughts about your brand, products, or services. Access to this information gives you an opportunity to improve upon the product and services.
For example, Hilton Hotel uses sentiment analysis to evaluate customer reviews and feedback to identify areas of improvement. This ensures if one customer has faced an issue, others shouldn’t face the same in the future.
Airbnb also uses AI to analyze customer feedback. They leverage AI to find even the most subtle hint of a bad experience and fix it to ensure no other customer faces the same issue.
For instance, AI finds specific keywords in reviews like cleanliness, utilities, etc. are checked.
More importantly, AI detects the adjectives customers have used to define these words. If a pattern is detected, support teams get an alert, and service improvements are implemented so that no other customer faces the same issue.
This means AI can identify subtle shifts in the languages customers use to talk about your brand to detect an impending issue. Getting these early warning signs means businesses can take timely action to prevent bad experiences and customer churn.
Successful predictions mean businesses can identify at-risk customers, know the reason for churn, and tailor a bouquet of incentives to retain customers.
Entertain Customers with an Omnichannel Experience
A McKinsey analysis from 2021 found that omnichannel experience is a “must-have” expectation of customers, making it a requirement for survival. Without AI, businesses have to shift from one channel to another to orchestrate a good experience, but it’s a labor-intensive process.
AI algorithms gather data like online interactions, reviews, purchases, etc, from multiple channels and bring it all together on a single platform. This creates a unified view of every customer, enabling brands to deliver solutions according to individual preferences.
Having access to all the information at once, along with customer preferences; a company’s support and sales team can personalize interactions.
Building an omnichannel experience also means customers interact with the brand’s representatives on any channel. Doing so, they will also receive a uniform response from all channels, which significantly improves customer experience.
So, these are the six AI trends in customer experience that are currently in force at different levels. Given the significant upfront costs of implementing AI in customer service, we recommend using AI consulting services to integrate the right AI models and build a comprehensive support system.
Beyond 2024 | What’s the Future of AI in Customer Experience?
Going forward, AI is clearly set to play an even larger role in curating better customer experiences.
Even though CX leaders are aware of the benefits, a Deloitte report finds there’s a gap in the implementation of AI-empowered customer experience strategies.
However, this is expected to change in the future as the AI technology evolves further to add new applications and benefits, including;
Use Emotion AI to Understand Customers Feelings
Moving beyond voice and text recognition, AI algorithms will be able to interpret facial expressions and tone of voice, leading to a better analysis of human emotions.
This will make businesses more empathetic to their customer’s needs and respond to their aspirations or issues more effectively.
Deep Learning and Neural Networks in Customer Experience
Ultra-intelligent AI systems will help you make sense of unstructured customer data, including text and visual data customers share on social media, brand websites, and forums.
Where deep learning algorithms will dig deeper into text data to identify trends and key themes, neural network technology will help identify individual customer preferences.
For instance, if a customer frequently talks about eco-friendly products, AI systems can suggest related products, which is a key ingredient to improve customer experience.
Quantum Computing for Faster Processing
AI tools will soon start using quantum computing, most probably on a sharing model, to process data faster. This means brands can provide personalized recommendations and support to customers in real time.
Autonomous AI Will Start Managing Customer Experiences
AI in customer experience is limited to helping humans perform better. Even though chatbots are somewhat self-empowered, their interactions are based on input data built by humans.
But soon enough, we can see autonomous AI programs that can think independently and even make decisions.
To Sum it Up
Delivering memorable customer experiences is pivotal for businesses worldwide. While AI is playing an important role in helping brands build a customer-centric support system, it’s definitely going to become even more sophisticated.
Businesses will benefit from AI enhancements in customer support systems, but you must follow ethical AI practices. Embrace AI, but with a mindset to augment human operations and not replace them altogether.
Author Bio: Irov is a content marketing specialist, demand generation enthusiast, and team player who is currently working with 2xSaS. He helps B2B SaaS companies spread the word about their products through engaging content. When he is not working he likes playing video games on his PS4.
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