You likely already know that providing a better customer experience leads to increased customer loyalty, satisfaction, and advocacy. But how can you ensure that you understand customers well enough to build an excellent customer experience?
Enter artificial intelligence (AI).
From recommending immediate action on opportunities for sales to generating highly personalized marketing messages at scale, the use of AI technologies like machine learning and natural language processing can help analyze customer sentiment and feedback at a scale, accuracy rate, and speed that humans cannot match.
How can your organization start to leverage AI in the area of customer experience? Our blog has a few ideas for you!
How is AI transforming retail? We have the scoop for you here!
4 Ways AI Improves Customer Experience
Recent research indicates that 39 percent of IT leaders are currently using AI or machine learning, with 33 percent reporting they expect to start using AI within the next three years. Here are 4 ways customer experience is benefitting from AI:
1. Using AI to better understand customers: When AI and machine learning are combined for gathering and analyzing social, historical, and behavioral data, brands can gain a much more accurate understanding of customers. What sets AI apart from traditional data analytics software is the mere fact that AI is continuously learning and improving from the data it analyzes, which allows it to anticipate customer behavior. As a result, brands can provide content that is more relevant, increase sales opportunities, and improve the customer journey.
Further, the usage of AI makes an even stronger case for sales, customer service, and marketing departments to work together. By supporting this synergy, AI has the potential to help brands connect with customers on a more personal level, increase loyalty, and secure their trust through functionalities like real-time decisioning, predictive analysis, virtual assistants, and more. Further, AI can be used to unify customer data and supply marketers with real-time functionality and decisioning, paving the way for a deeper understanding of customer wants, feelings, and actions.
2. Real-time decisioning and predictive behavior analysis: “Real-time decisioning” is defined as the ability to make a decision based on the most recent, available data with near-zero latency. There are several ways real-time decisioning can be used to create more effective marketing to customers. For instance, real-time decisioning can identify customers that are using ad blockers and supply them with alternative UI components for continuous customer engagement.
Further, AI is key to providing insights dynamically through finding patterns and making predictions over a huge amount of data points. Overall, the combination of AI and real-time decisioning can help us recognize and understand a customer’s intent through the data they produce. Then, in real-time, brands can respond by providing hyper-personalized, relevant content, and offers to different customer segments.
On the other hand, predictive analytics gets a boost from AI due to the fact that AI can analyze large amounts of data in a very short amount of time. Through predictive engagement, brands respond to real-time, actionable insights that guide customer interactions, which often provides customers with a greater emotional connection to the brand that appears to deeply understand the customer.
3. Even more effective AI virtual assistants: According to a 2020 MIT Technology Review survey, customer support (via virtual assistants) is the leading AI application being deployed today. While today’s virtual assistants are not being used to replace human works, they can supplement the human workforce in order to help human agents be as effective as possible. Further, they are saving businesses money by allowing customers to take care of minor issues on their own time. It’s important to remember, thought, that an AI chat isn’t just about resolving customer service inquiries.
By analyzing customer history, a virtual assistant can create a proactive personalized offer for a customer. Depending on the channel, they can also share pertinent imagery and product photos or a link along with their recommendation. Virtual assistants can also be used to predict when a customer may need a new service, and proactively offer it to them. Finally, today’s virtual assistants are constantly learning, which further allows them to offer a personalized customer experience.
4. Hyper-personalization: By combining AI and real-time data, hyper-personalization is being used to deliver content that is specifically relevant to the customer, as well as resolving pain points found along the customer journey. Conversational AI is providing consistent, personalized experiences that are much quicker and more convenient than traditional ways of interacting with businesses.
Conversational AI can also connect to conversation histories, which makes them aware of customers’ previously stated intentions and data. All of these characteristics can facilitate a more personalized, consistent customer experience, which will be a powerful differentiator for most businesses in the future.
What’s the difference between artificial intelligence and machine learning? We break those concepts down in this blog!
Steps for Improving Customer Experience With AI
Clearly, brands leveraging AI to improve customer experience are on the right track. Now, the question is, how can leaders use AI to get a quicker, real-time understanding of customers? Gartner outlines the following tips:
- Formulate your customer experience strategy: Now that you know what AI can do, it helps to have a CX vision and strategy in place. You can work with a dedicated CX leader, customer relations lead, or the chief marketing officer to get an idea of all of the components your strategy should entail.
- Map and analyze customer journeys: In order to understand the touchpoints and experiences customers have with your brand, map the current customer journey from discovery to presales to sales to customer service reps and beyond. When you understand how your customers typically experience your brand, you’ll have a better idea of the ways AI can be used to improve the customer journey.
- Get to know AI solutions that help users understand customers faster and more efficiently: Does your data reveal real-time customer insights? With AI technologies, you can categorize, organize, and analyze customer data in real time, which will lead to an even better understanding of customer sentiment.
- Should you build or buy? Do you have enough skillsets and budget in-house to create a CX/AI solution? If not, find a vendor that prioritizes and effectively handles critical customer-understanding issues. You can ensure the vendor will focus on this area through proofs of concept or pilots.
- Track and measure success: Identify the right metrics and key performance indicators to track how successful your AI/CX initiative is. To build momentum for future initiatives, aim for “early quick wins,” which are initiatives that can be easily tracked and can quickly show success (or failure).
How is Sophie powering personalized CX? Learn more here!
Stefanini’s Capabilities for AI and Customer Experience Solutions
Today’s landscape is focused on personalized experiences and an omni-channel approach. With our SAI suite – which stands for Stefanini Artificial Intelligence – we can work with you to co-create the right AI-enabled CX solution for your business. SAI is comprised of different technological capabilities, which includes a focus on data science that enables the development of powerful analytics and visualization for reactive, proactive and/or prescriptive systems.
Further, our virtual assistant Sophie is building better user experiences through hyper-personalization. With an omnichannel approach, she can interact with various personas and provide human-like interactions.
Ready to learn more? Our experts are standing by. Reach out today and let’s get started on your AI journey!