Artificial intelligence (AI) is an essential tool for modern businesses. It can impact many areas—operations, customer support, analytics, and marketing. It’s no longer a novel concept that companies are hesitant to embrace. According to an S&P Global report, 95 percent of businesses believe AI is critical to digital transformation initiatives.
The acceleration of AI is partly due to the pandemic, but it had momentum before 2020. One key channel where brands are eager to apply AI is customer marketing strategies. In this post, we’ll describe how organizations can use AI to evolve customer marketing strategies.
Different Types of AI and How They Work
AI creates a simulation of how human intelligence works. It’s often used in customer-related applications to create personalized experiences at scale. Machine learning—a subset of AI—is also critical because it automates tasks and learns from interactions. The more data the AI engine ingests, the more adaptable it becomes.
There are many use cases for AI technology. In terms of customer support teams, they’ll be driving better customer experiences with conversational AI or operational AI.
Conversational AI includes chatbots, virtual agents, and voice assistants, and it uses natural language processing (NLP), natural language understanding (NLU), and machine learning to interact with people and answer questions in a human way. It’s much different from a traditional chatbot that simply uses keywords and decision trees to respond. Conversational AI understands sentiment and intent.
Operational AI involves using NLP to tag and triage incoming customer queries automatically. Using this as a tool improves the accuracy of demand forecasting, routing, and workload distribution. It’s technology that performs an operation or function rather than actual customer interactions.
Self-Service That Actually Serves
Enhanced self-service is the first way to leverage AI in customer marketing strategies. Customers desire ease in communicating with companies—they want to do it on their own terms and have little tolerance for waiting.
Self-service, powered by conversational AI, works to resolve queries quickly and accurately. Conversational AI self-service analyzes the question, looking at intent and sentiment to provide the most accurate answer.
For example, a customer may ask, “How can I find replacement parts?” The conversational AI technology recognizes that the person needs information on purchasing parts and then directs them to options for purchasing online or through other channels. A standard chatbot may not register the intent and therefore provide less dynamic responses, such as simply providing the customer with a link to a page about all the types of replacement parts without a path to purchase.
Improving the Agent-Customer Interaction
Not all consumers will find answers through self-service. Some questions are more complex, so the user creates a ticket. In that one action, conversational AI breaks it down to best comprehend the need. Operational AI also becomes a factor here, as it tags incoming queries.
From there, the system routes the ticket to the group of agents most able to respond. Then when the agent picks it up, AI assists them further by providing knowledge base information, past tickets, and macros that help the agent quickly and accurately respond.
When resolutions are fast, customers are happier and more satisfied. That can create stronger relationships and loyalty.
Personalization of Digital Interactions
Another way that AI supports customer marketing strategies is through the ability to personalize just about everything. The more data you have on a customer, the better you can communicate with them. That includes emails, website experiences, and customer service interactions.
Conversational and operational AI contribute to personalization. Conversational AI delivers better customer service. Operational AI works on the backend to move through the processes required to personalize. The more personalization you can foster, the more customers will trust your brand.
AI Helps You Understand Customer Needs
AI is also instrumental in understanding customer needs. It’s collecting data from many sources, and all of that data found in your customer support history is valuable. For example, you can track patterns of topics or question types as AI tags them.
With these insights, you can improve your knowledge base, product pages, guides, instructions, or even improve the product or service. These data insights translate to genuine feedback from your customer base. Making these adjustments is critical to retaining current customers and attracting new ones.
AI Will Power the Future of Customer Marketing Strategies
Keeping up with customer demands and expectations is easier with AI. It can deliver benefits in many ways, helping you transform customer marketing strategies.
Learn more about how it can benefit your organization by reading What Is Conversational AI, and Why Does It Matter?
