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AI and the Art of Non-Linear Customer Experience

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In the not-so-distant past, customer experience (CX) was a straight line — a predictable journey from point A (the customer’s question) to point B (the company’s answer). However, as retail landscapes evolved and consumer demands became more sophisticated, this linear approach showed limitations.

Welcome to the future of retail, where the checkout lines are virtual, the service is personal and the experience is anything but linear. AI is opening a realm of non-linear CX and helping turn every interaction into an opportunity to impress, engage and retain. This evolution from a linear to a non-linear approach in CX is reshaping the fabric of the retail industry.

The Fundamentals of Non-Linear CX

Non-linear CX is about responding in real time to the customer, creating a personalized experience with every interaction. This approach deviates from traditional models by responding to customer queries and anticipating them, offering solutions tailored to the customer’s history with the brand.

At the heart of non-linear CX is AI with its conversational and generative capabilities. AI enables engagement with customers in more dynamic and intuitive ways. Today’s intelligent virtual agents (IVAs) pair AI with natural language processing (NLP) to understand customer intent in a way that old-school linear models never could. Imagine a virtual agent that doesn’t just respond to a single question but can handle a barrage of inquiries simultaneously and in natural language.

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Non-linear service powered by AI enables flexibility. It allows companies to meet customers where they are in their journey, whether they’re just browsing, ready to make a purchase or seeking post-purchase support. IVAs can more easily discern what customers are looking for and proactively suggest additional products or services. It’s like having a personal shopper who finds what you asked for and offers items you didn’t know you needed.

Implementing Non-Linear CX

Transitioning to a non-linear customer service model might sound like a Herculean task, but it doesn’t have to be. The key is to start by reviewing existing systems, determining where it makes sense to incorporate AI and then testing it. The next stage is integrating AI into internal processes before rolling it out in customer-facing applications. This phased approach allows businesses to fine-tune their AI systems, ensuring they’re ready for prime time.

The first step is choosing the right AI technology that integrates seamlessly with your existing systems, whether it’s your customer relationship management platform or customer service software. The implementation process might involve technical heavy lifting, like API integrations, but the payoff is worth it.

Training is another critical component of implementing non-linear customer service. Your team must understand how to work alongside AI, leveraging its strengths and stepping in when a human touch is needed.

Here are three examples of non-linear CX in action:

  • Multichannel support: In the non-linear world, customers can jump from social media to email to phone, all without missing a beat. AI ties these channels together, ensuring that a conversation can continue seamlessly across platforms, regardless of where it starts.
  • Self-service options: Self-service tools like FAQs and knowledge bases empower customers to find answers on their terms. The magic of AI is that it can pull from these tools to answer customer questions if they call or start a chat. AI tools can either direct customers to existing tools or provide answers from those resources, reducing the load on your customer service team.
  • Predictive support: The most exciting aspect of non-linear and AI-enabled CX is its ability to anticipate customer needs. By analyzing data from past interactions, AI tools can predict potential issues and offer solutions before the customer realizes there’s a problem. This proactive approach is seen in multiple industries, from telecommunications — where providers address network issues before they affect users — to ecommerce platforms that engage customers at critical moments to prevent shopping cart abandonment.

Challenges and Considerations

One of the primary considerations of the shift to non-linear, AI-driven CX is maintaining the integrity and privacy of customer data. Ensuring that customer information is protected — while still being utilized to its fullest potential — requires a dedicated adherence to data protection regulations, such as those laid out in the California Privacy Rights Act and the EU’s General Data Protection Regulation.

Another challenge is the potential for AI to misinterpret customer intent or provide inaccurate responses. Because of this, having responsible monitoring processes in place is essential to minimizing errors and ensuring that the customer experience remains positive.

The transition to a non-linear CX model is not merely about adopting new technology — it’s about reimagining what the customer experience can be. It requires a commitment to continuous improvement, a willingness to embrace change and a dedication to putting the customer at the heart of decision-making.

If your organization is ready to explore the possibilities of non-linear CX, an excellent place to begin is by evaluating your current model. Identify areas where AI can make the most immediate impacts and consider a phased approach to implementation. Starting small is critical — but so is getting started as soon as possible. As we look forward, the question for retailers is not whether they should adopt non-linear CX but how effectively they can do so.


Matt Whitmer is the Chief Revenue Officer and SVP of Marketing at Mosaicx, a leading conversational AI provider. He has over 15 years of senior leadership experience focused on helping enterprise clients embrace and implement cloud-based engagement solutions.

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