The shift to a customer-first experience from static models is fueled by the integration of advanced AI. But for brands to successfully navigate this transition, they will need to leverage AI tools not just as a technological shift but as a strategic realignment toward customer-focused experiences.
CX is experiencing a shift of historic proportions.
The way customers have historically interacted with brands has been largely one-dimensional, dictated by the brand rather than the customer. Whether someone is returning a product, asking a question, or seeking other customer assistance, personalization and flexibility are often lacking or entirely non-existent in the process.
But now we’re seeing a reversal of the paradigm. Brands are tailoring experiences to meet the individual preferences of customers, and adopting agile communication modalities that prioritize customization, convenience, and accessibility.
The shift to a customer-first experience from traditionally static models is fueled by the integration of advanced AI technologies, particularly in customer service functions, that empower brands to better anticipate and meet customer needs. But for brands to successfully navigate this transition, they will need to leverage AI tools not just as a technological shift but as a strategic realignment toward customer-focused experiences.
The limitations of CX chatbots
Six in 10 retailers currently use AI to improve customer interactions, with most focused on automating customer service and improving knowledge management through the use of scripted chatbots. But as brands increasingly prioritize AI-enhanced CX, they have found that simplistic, generic chatbots are falling short.
In fact, 90% of customers still prefer customer service from a human rather than a chatbot; more than half say that humans understand their needs better, provide more thorough explanations, and offer less frustrating experiences compared to a standard chatbot. As AI tools grow more sophisticated and convenient, that experience is bound to change.
How can brands integrate AI tools that provide greater value and better experiences for customers? There are two core challenges they must first address: The performance of AI-enhanced CX tools, and their dependability.
To start, AI tools should provide accurate results and responses that are aligned with the brand’s policies and practices. Brands need to ensure AI tools offer relevant and useful solutions that will actually resolve customers’ inquiries.
In addition, AI results must be accurate, consistent, and dependable. While variability can enrich the customer experience with more personalized and engaging interactions, it requires careful oversight to ensure responses don’t deviate from expected standards or produce harmful, misleading, and inappropriate information. When this oversight is missing, cars get sold for $1 and managers are illegally advised to take a cut of their employees’ tips.
Chatbots can’t solve these complex challenges without human assistance, coaching, and guidance; they don’t have capabilities advanced enough to handle the wide array of unique customer interactions. Instead, brands need sophisticated AI tools that can tailor experiences to the unique context and preferences of each customer.
How retailers can leverage AI agents to enhance CX
As brands look to develop customer-first experiences, many retailers are making the switch from simple, scripted chatbots to advanced AI agents, intelligent and adaptive AI interfaces that enable more responsive and personalized interactions with customers through their preferred channels, modalities, and languages.
By leveraging AI agents, you can bring your CX to a new level. The following best practices can help you get started.
1. Onboard AI like a new employee
Unlike previous generations of scripted chatbots, which offer predictable and static responses, AI agents are sophisticated, autonomous systems capable of learning, making decisions, and adapting to complex information — eliciting unique responses based on context and interpretation that mirror human conversation.
That’s why it’s crucial to treat AI agents like new employees, with AI managers onboarding, guiding, and managing AI agents similar to humans. You should start with rigorous onboarding that provides AI systems with a detailed understanding of your brand’s identity, organizational values, and customer service practices. Similar to other onboarding processes, make sure your organizational knowledge base is up to date, well-organized, and accessible, with prepared documents and APIs in place to provide AI tools with seamless integration into your systems.
Likewise, AI managers should develop a clear understanding of AI capabilities to determine whether systems can manage complex tasks, such as handling multiple queries simultaneously, providing personalized recommendations for customers, and offering consistent, contextually appropriate responses.
2. Concentrate on one channel, then promote
The ideal CX supports continuous conversation between customers and your brand across messaging, voice, email, and other customer touch points. That should be your end goal, but it doesn’t need to be your starting point.
Instead, start by concentrating on a single channel and refining your AI capabilities before promoting your AI agent to other channels. This approach allows AI agents to adapt to various scenarios, communication styles, and customer preferences, paving the way for a more cohesive customer service experience across channels.
3. Continuously train and test systems AI systems are only as good as the data that fuels them. That’s why AI agents need continuous coaching based on the latest data, customer feedback, and evolving market trends to ensure they continue to meet industry-specific customer service needs. In doing so, it’s most effective to use your own data and metrics to refine AI agents based on your brand’s identity, customer base, and the various scenarios in which the AI will operate.
Likewise, it’s crucial to rigorously test and monitor systems to assess how they are performing and ensure they meet predefined standards of performance safety and alignment with brand values. While companies have traditionally focused on measuring containment — the number of AI interactions that lead to a reduction in direct customer service interactions with a human representative — you should instead target metrics to gauge whether your AI agent is helping customers and resolving their inquiries.
By implementing ongoing coaching and robust performance testing, brands can ensure their AI tools deliver high-quality interactions that offer effective service solutions while complying with policies and practices.
Committing to the customer-first experience
In retail and elsewhere, customers’ needs and expectations now dictate the flow of conversation and shape of communication: Seven in 10 customers expect personalized interactions from companies, and more than three-quarters get upset when that’s not the case.
It’s up to brands to ensure their AI tools and practices provide the level of flexibility, personalization, and scalability that customers now expect.
By committing to a customer-first mentality, brands can revolutionize their customer service into a more adaptive, responsive, and personalized function — and follow the lead of customers wherever they might head in the future.
