E-commerce, retail, and hospitality customers want self-service options that improve their overall experience. Businesses in those industries are eager for automated solutions that streamline operations and make customer experience teams more efficient at scale.
AI-powered chatbots can solve all of these pain points. There’s just one catch: according to a survey from Gartner, nearly two-thirds of consumers prefer not to encounter AI in their customer service journey.
Why? For many respondents, it’s an issue of trust. According to the survey:
60% of consumers are worried that AI agents will make it more difficult to reach a human agent
42% fear that AI chatbots will provide the wrong answers to their questions
Consumer trust is hard-won—and it’s up to customer experience teams to deliver AI-powered service journeys that provide value for your customer base.
“Customers must know the AI-infused journey will deliver better solutions and seamless guidance, including connecting them to a person when necessary,” says Keith McIntosh, Senior Principal of Research for Gartner Customer Service & Support.
That means creating AI-powered chatbots according to the best practices of service journey design. Personalized, engaging, and useful interactions are paramount. However, AI agents should also be developed and managed to empower your human agents and enhance your overall customer experience.
Approaching this process for the first time? We can help. Read on to find out how AI agents can deliver personalized, engaging experiences for your customers—and how Bird’s Service Cloud can help you turn this ambition into reality.
How can AI deliver a ‘personalized and engaging’ experience?
AI agents aren’t sophisticated enough to have a heart-to-heart conversation with your customers. Fortunately, that’s not what customers seek when contacting customer service.
Instead, they’re looking for assistance that is relevant to their specific circumstances or needs. A skeptic might worry that AI chatbots would only be able to provide generic responses to their queries, sending them into a maddening feedback loop where the chatbot is unable to answer any of their questions—and also unable to refer them to a human agent for assistance.
Without proper training for your AI model, that scenario could happen. But, with the rapid advancements of AI technology and its ability to be thoroughly trained and tested, AI agents can leverage a wide range of data points like product inventory, conversation history, knowledge baseto create a tailored experience for each customer.
Personalization based on CDP
The data points collected in a customer data platform (CDP) are readily available for human agents to reference. But AI agents can make even better use of this data by quickly reading, contextualizing, and using all of the data in a single customer’s profile to inform chat-based interactions with that user.
Demographic, transactional, and behavioral data collected across all available sources can help AI agents understand who they are talking to, their preferences, and what they might need. When a customer has a question regarding one of its recent purchases, for example, the AI agent can instantly call up information on specific products from that order to provide shipping updates, warranty details, and other information—all without intervention from a human agent.
Sentiment analysis to better understand user intent
Chatbots equipped with conversational AI capabilities can be trained to analyze and understand customer sentiment in each interaction. By registering customer sentiments as positive, negative, or neutral, the chatbot can tailor its own communication to improve the customer’s experience in that particular interaction.
If the chatbot detects a shift in sentiment from neutral to negative, for example, it may determine that the current chatbot experience isn’t helping the customer and decide that the best course of action is to hand the interaction off to a human agent.
Omnichannel support on customers’ preferred channels
With the right templates and workflows in place, AI agents can provide personalized interactions on whichever channel the customer prefers including email, SMS, RCS, Instagram, and push. From desktops to mobile devices and web-based chatbot widgets to social media messengers, AI agents can move across each platform with ease to give your customers more of a choice in how they want to contact customer service.
Previous conversations on other channels can also be referenced to ensure consistent, value-added interactions each time the customer starts a chat session.
A variety of AI models to choose from to match your needs
When building your AI chatbot, it's crucial to understand that different AI models excel at various tasks. Platforms like Hugging Face offer an extensive library of thousands of models, each specialized for specific use cases. The key is to find the right model that aligns with your unique business needs and customer service goals.
While fine-tuning a model can enhance its performance for your specific use case, depending on the circumstances, this process can be complex and resource-intensive. That's where Bird’s AI expertise comes in – we simplify the process by:
Handling the intricacies of model selection
Managing the fine-tuning process
Ensuring your AI chatbot is powered by the most suitable and optimized model
Escalating unresolved issues to human agents
Lastly, no matter how thoroughly you train your AI agent, there will be situations that can’t be resolved through an automated interaction. When AI chatbots are no longer able to assist with a customer’s question or issue, the chatbot can seamlessly loop in a human agent to continue the conversation.
Escalating these conversations ensures that customers can still get the level of service they need while allowing human agents to focus on conversations where their expertise is required.
How to build the best AI chatbot
As you prepare to build your own AI-powered customer support agent, you’ll need to make sure the chatbot is equipped with the right features and capabilities to support the best practices of service journey design.
If you want to build the best AI agent possible, you’ll need to prioritize the following:
Access to your internal knowledge base
A knowledge base is a centralized repository of organized information relevant to customer service queries. This knowledge base serves as a single source of truth where your AI agent can reference internal documents and generate informative, helpful responses for your customers.
Depending on your business and the scope of your AI agent’s responsibilities, you may want to include product guides; ordering and shipping information; return, exchange, and cancellation policies; FAQ documents; and other information required by your chatbot.
This allows your AI agent to generate quick, reliable answers related to a wide range of customer queries, such as “What is your return policy for my recent purchase?” or “Can you explain the breakdown of fees on my recent reservation?”
Need help creating a knowledge base? Bird can assist through its OpenAI integration.
A voice bot to handle incoming calls
Along with text-based chat, your AI agent should be equipped with a voice bot to handle incoming customer calls. Your internal knowledge base also powers these interactions, but the availability of voice-based chat will offer increased convenience for your customers while reducing call volume for your customer service representatives.
When your voice bot is used to facilitate customer interaction, the bot will record the call and generate a transcript for an agent to review. If the agent identifies any inaccuracies or issues with the interaction, they can reach out to the customer directly.
As with text-based chat, the voice bot is also able to escalate a call to a human representative if the AI agent is unable to help the customer.
Integration with your store
For example, if your business uses Shopify for its e-commerce operations, your chatbot will need to integrate with this store to access its knowledge base of data. Your Shopify store contains important product information that the chatbot can use when responding to queries regarding product inventory, product details, and even recommendations.
Once this integration is complete, your AI agent can pull up order information, update shipping details, update the customer’s profile in Shopify, and handle other queries related to inventory and transactions.
Comprehensive analytics and reporting
Once your AI chatbot is live, analytics and reporting are essential to understand how the agent is performing. Your business should equip itself with an analytics and reporting platform tracking a wide range of success metrics, including:
The percentage of customer service sessions resolved by your AI agent
The average time to resolution
Success rates for first-contact resolution
Customer satisfaction scores (CSATs)
These insights will play a central role in optimizing your AI agent for greater success over time. By digging into these granular data points, you can gain a deeper understanding of your chatbot’s success in creating personalized, engaging experiences for your customers.
AI agent use cases in action
When you build an AI chatbot from scratch, you can customize its capabilities to your specific needs. A development tool like Bird’s Chatbot Flow Builder can help create flexible flows for general customer service queries, lead qualification, post-purchase retention, and other purposes.
Here’s a sampling of the most common AI agent use cases your customer experience team may want to consider:
Respond to frequently asked questions
Generative AI models can auto-generate frequently asked questions to provide quick, efficient answers for common inquiries. By creating an FAQ model for your own brand, you can accelerate your chatbot’s go-to-market velocity while providing a convenient, scalable self-service solution for your customers.
These FAQ models use OpenAI dataset generation to develop conversational scenarios and generate pre-filled questions and responses. They can also take a single question and generate variations of that question that customers may ask—along with the answers—to help you build upon the value of your FAQ model.
Bird’s AI Hub makes it easy to create and test an FAQ model before deploying it with your live AI agent.
Create custom CS flows
Customized CS flows use pre-defined triggers and actions to automate chatbot interactions with your customers in real-time. When customer experience teams commit time and resources to building out these flows, they help ensure that these customer interactions remain relevant to both your business and your customers.
When creating a flow within Bird’s Chatflow Builder, you can mix and match triggers and actions to tailor each series of automations to the behavior and responses of your customers. Automated responses can be caused by dynamic triggers related to new account sign-ups, cart abandonments, or other events. Auto-responders, scheduled actions, conditional logic, and other customizations can also be incorporated to maximize the relevance, personalization, and value of these AI agent interactions.
Gather feedback from customers
Before and after customer service sessions, businesses can use an AI agent to gather feedback from customers related to their recent CS session, as well as their broader customer experience.
This feedback can also be dynamic and interactive to increase the quality of the information collected from each session. If standard survey questions result in the customer mentioning their frustration with a recent product purchase, for example, the survey can shift into a new set of questions aimed at gathering more information, such as why they were frustrated with their purchase, and whether that frustration extends to their broader customer experience.
After the feedback has been collected, a live agent can review this information and make a decision on whether to follow up with the customer.
Assist with appointment booking
An AI agent can integrate with your scheduling software to help customers book appointments without talking to a live representative. The chatbot can present open appointment slots based on the customers’ availability and preferences.
If a customer calls or connects via messenger asking about availability for Friday afternoon appointments, the chatbot can quickly list out the available options and, if the customer chooses one, book the appointment and send an automated confirmation via email or text.
What AI + Bird Service Cloud can do for your business
As soon as you deploy an AI customer service agent, your business will reap the benefits of reduced customer service costs and more efficient CS operations at scale.
But an AI-powered agent doesn’t bring cost-efficiencies at the expense of quality customer interactions. Instead, generative AI can help enhance your CS experience by offering more responsive, reliable assistance to your customers and powerful real-time context and insights for your human agents.
Bird’s AI-driven Service Cloud allows your business to:
Provide always-on customer service. AI agents are available around the clock to interact with your customers, even when your live agent team is offline. If customers need help, they always have somewhere to turn.
Personalize every conversation. Through quick analysis of customer information and other contextual data points, AI agents can participate in nuanced conversations that feel natural, empathetic, and specific to the customer’s circumstances and needs.
Resolve issues faster with intelligent automation. Access to your knowledge base, online store, and internal FAQ model enables an AI agent to provide accurate answers to customer queries in a matter of sections. While complex issues can be seamlessly escalated to a live agent, the majority of support tickets can be resolved without human intervention.
Create powerful customer experiences at scale
Your customers aren’t opposed to engaging with AI-powered customer service agents. They’re opposed to inauthentic and inefficient experiences—which is exactly what happens when AI innovation isn’t mapped to your brand’s service journey design.
When CX teams commit to building comprehensive, flexible flows to guide AI agent interactions, they increase the automation capabilities of the company’s chatbot solution while enhancing the bot’s ability to facilitate personalized interactions with customers. The more training and testing you put into developing your AI agent, the greater your automation capabilities will be. This investment opens the door to:
Up to 40 percent cost savings for your CS operations
Higher NPS scores
Faster ticket resolution for customer issues
Greater capacity for delivering engaging customer experiences at scale
Bird’s Service Cloud can make it happen. Contact us today to find out how.