A customer’s end-to-end experience can build or break a business.
From customer acquisition to retention, exceptional customer experience is the backbone of building customer loyalty.
However, customer experience (CX) has evolved to integrate artificial intelligence to solve prevalent customer experience challenges. Some of these problems AI customer experience would solve include:
- Unanswered questions
- Multiple agent transfers
- Long wait times
- Poor automation without human touch
- Agents who do not understand customer needs
- Services not personalized
To foster accelerated customer loyalty, small and medium-sized businesses (SMBs) can execute AI in customer experience.
Additionally, by using AI, companies can minimize bad experiences and keep their hard-acquired customers.
In this article, we will discuss how customer experience in the age of AI is helping companies retain customers. Here is the deep dive.
Table of Contents
What is AI customer experience?
The AI CX uses artificial intelligence (natural language processing and machine learning) to deliver intelligently designed experiences to customers.
The main goal for customer experience AI is to provide a flawless experience or solve customer problems intelligently for retention and loyalty building.
A positive customer experience powered by AI may include:
- Proactive customer support around known issues
- Real-time customer resolution with AI tools like chatbots
- Self-service customer resources
- Setting realistic revenue targets with AI customer insights
- Intuitive product design from AI customer feedback
AI customer experience vs. AI customer service. What is the difference?
While customer experience is an end-to-end flawless experience a customer interacts with a brand, customer service is an element of the customer journey.
Integrating artificial intelligence in the customer journey map improves customer support and experience.
The difference between AI for customer experience and customer service depends on customer journey touchpoints.
| AI customer experience | AI customer service |
| Streamline customer onboarding | Enable self-service onboarding |
| Deliver better customer resources access experience | Power relevant customer resources recommendations |
| Pre-qualify prospects with personalized sales processes | Customize sales processes hiccups for fast pre-qualification |
| Minimize dissatisfied customers when using products | Reduce response time in case of complaints and deliver customer success |
Why is AI for customer experience important?
According to PwC, 86% of buyers are willing to pay more for a great customer experience.
Additionally, AI in customer experience is tied to the success or failure of any business.
Here is an overview of the benefits of AI in customer experience:
- Increase customer lifetime value
- Amplify company brand
- Improve customer loyalty
- More competitive advantage
- Improve customer retention
AI for customer engagement
With 95% of customer interactions expected to be powered by artificial intelligence by 2025, customer engagement AI is at the frontline to streamline these interactions.
AI-powered e-commerce customer engagement delivers an experience that builds brands and scales revenues. Here are some ways AI for customer engagement helps e-commerce businesses.
- Optimize content recommendations that push customers over the edge to buy products.
- Optimize cross-channel that gets customers buying from the preferred channels. Be it on the website, email, or SMS/MMs
- Personalize repeat orders, upsells, and down sells with e-commerce-focused AI engagement tools.
AI for customer success
According to Bain & Company, with the use of AI, customer success has evolved beyond merely providing insights.
AI customer success is shaping product design and development along with customer engagement. The objective is to deliver exceptional customer experience from product inception to delivery.
Some AI customer success solutions for SMBs that help deliver customer satisfaction include:
- Sentiment analysis
Sentiment analysis is the process of using AI to analyze customer feedback and determine their sentiment towards a product or service.
AI-powered algorithms can analyze customer reviews, social media posts, and customer service interactions to identify areas where customers are dissatisfied.
This approach enables businesses to address customer complaints proactively and improve customer satisfaction rates.
- Chatbots
Chatbots solutions like Aloha Bot allow SMBs to communicate with customers in real time. They can answer frequently asked questions, provide product recommendations, and resolve issues without human intervention.
Such conversational AI tools are programmed to understand natural language and provide personalized responses to customers. The approach reduces customer wait times and improves customer satisfaction rates.
- Predictive analytics
Predictive analytics uses AI to analyze customer data and predict future behavior. With predictive analytics, businesses can anticipate customer needs and proactively provide solutions.
For example, a company can use predictive analytics to identify when customers will likely cancel their subscriptions and offer them an incentive to stay. This approach not only increases customer satisfaction but also reduces customer churn rates.
AI for customer loyalty
Customer loyalty measures customers’ commitment to a particular brand or product.
With AI in customer loyalty, SMBs can retain customers as it increases customer lifetime value and helps to increase profits.
An instance where AI execution can improve customer loyalty would be customer segmentation. Artificial intelligence can analyze customer data to identify patterns and group customers based on preferences, behavior, and demographics.
This enables businesses to tailor their marketing campaigns to specific customer segments, increasing the campaigns’ effectiveness and improving customer loyalty.
How to measure AI customer experience?
Measuring customer experience without the right tools is a challenge at times. However, with the rise of AI for customer experience, businesses can track, analyze and implement insights obtained from customer data.
One way to measure AI customer experience is by using customer satisfaction scores, net promoter scores (NPS), or customer effort scores (CES). These metrics can help you understand how customers feel about their interactions with the AI system.
Other ways to measure AI customer experience include:
- Conducting user testing with real customers can help you understand how they use the AI tools and identify areas where they are struggling or experiencing frustration.
- Collect customer feedback through surveys, focus groups, or other feedback mechanisms. The feedback can help you identify areas for improvement and make changes to improve the customer experience.
- Analyze customer interactions and the AI system using natural language processing (NLP) and machine learning techniques. This helps SMBs understand how customers interact with AI solutions, identify common pain points, and make changes to improve the customer experience.
