This rapid evolution means that the industry buzzword “transformation” is itself transforming. Historically, when we think about transformation in CX, we would make large sweeping plans leading to big changes and, finally, that mic-drop impact that really changed our business—a transformation.

The problem now is that a big plan like that might take a year or more to execute, while today’s current best CX technology is evolving faster than that—quarterly or even monthly. What happens a year from now, when you are set to unveil your grand transformation and it turns out you’re unveiling something three tech-generations behind? Moreover, consider the implications of signing a long-term contract with one tech provider, only to find out a few months later that your shiny new system is already outdated. If you’re dealing with a large stack of tech products, coordinating all the stakeholders to implement these systems can extend timelines even further.

How Transformation Is Evolving with Technology

Transformation as a concept is still so important in CX. So what does it look like today and who are the brands achieving it? The answer lies in adopting short, “sprint” style planning that emphasizes flexibility. Once upon a time, it was efficient to execute it all at once. Today, the brands who win are those who red-circle two or three things that would be highly impactful to their business and can be executed in less than three months. You focus on a couple of impactful changes achievable within a single quarter, then refine them based on performance, keep what works, and discard what doesn’t. And then you do it over again, following a defined roadmap moving towards your goals, banking value as you move forward.

Why do it this way? Well, think about it like this: The traditional plan, even if it worked out perfectly and you got great results from it once it finally launched—let’s say a year later—your customers have really not seen any improvement in your CX for that entire period of time. They’re going to be benchmarking your brand against other companies they interact with that do have some of these advancements, and they’ll wonder why you’re still doing things the old way. That’s the aforementioned consumer demand for automation and AI. And now that we’re seeing some of the most pronounced improvements in CX in decades, consumers will expect it. 

Innovating with Intent

In this new era, transformation is no longer about overhauling systems in monumental, infrequent leaps; it’s about innovating with intent and agility. This approach not only keeps a brand technologically relevant but also deeply attuned to the evolving expectations of customers. Those companies that excel are the ones that consider transformation an ongoing process, rather than a one-time event. By embracing shorter, focused cycles of innovation, they are able to continually introduce improvements, learn from real-time feedback, and rapidly adapt to emerging technologies and market dynamics. This constant state of evolution is crucial, not just for staying competitive but also for leading the charge in customer experience innovation.

Creating a Culture of Continuous Improvement

The shift from large-scale transformations to iterative improvements demands a cultural shift within organizations. This new culture prizes flexibility, speed, and a tolerance for failing fast, allowing lessons to be learned quickly and incorporated into future initiatives. As a result, organizations not only keep pace with technological advancements but also foster an environment where innovation thrives. Continuous improvement becomes part of the organizational DNA, empowering teams to experiment and continually enhance customer interactions. Ultimately, this dynamic approach to transformation equips businesses to not just respond to customer needs but anticipate them, ensuring that their customer experience is always at the cutting edge.

Guest post written by Jeff Fettes, Founder and CEO of Laivly.

Laivly’s proprietary artificial intelligence platform, Sidd, enables the world’s biggest brands to leverage AI, automation, and machine learning into their existing customer service programs, swiftly and without extensive integration barriers, with industry-leading agent copilot and self service solutions.

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I didn’t know it at the time, but KITT is what we call a cobot or collaborative robot today. Cobots are AI that are capable of operating in human environments and using tools designed for humans. They do similar tasks as a human would, except with the benefit of extraordinary speed, memory, consistency, and computational power. By mimicking human work but accelerating those tasks, cobots can take advantage of existing infrastructure—making them quicker to deploy and easier for users to understand and manage.

Thinking About Cobots Through a Real-World Lens

To understand cobots, let’s look at an example of traditional automation: the monorail at Walt Disney World. The Walt Disney Company connected its first couple of Orlando theme parks and its early hotels with a self-driving train. However, after it was built, Disney added several new resorts and additional theme parks, routinely changing entrance locations and traffic flows.

At first, the company tried to keep up, building new tracks and monorail stops but quickly realized that the constant changes paired with the subsequent costs of rebuilding the monorail every few years made it hard to justify the benefits of the automation. So, Disney stopped modifying the monorail and instead added buses and shuttles to keep up with the changes. If you needed a new stop, you just added it to a driver’s route, no problem.

But with cobot technology, you never even build the monorail in the first place. Instead, you make the buses automated. They would drive on the existing roads with other traffic and easily learn how to add new stops to keep up with the constant changes. Even better, these automated buses could be completely repurposed for any number of challenges on Disney property requiring the transportation of groups. New areas of the park would have automated transportation available instantly—without building anything new.

Cobots Applied to Customer Care

So how does all of this connect to AI and automation for contact centers? Just like KITT before it, Sidd, Laivly’s artificial intelligence platform, is also a cobot. Drawing inspiration from the self-driving car concept, we developed Sidd, our own “self-driving” contact center agent. The “roads” it drives are your telephony system, your CRM, and those shipping websites that agents access when your customer asks for a specific delivery time.

In the realm of customer service, the integration of cobot technology is akin to the leap from static, inflexible systems to more adaptive, responsive solutions. These AI-driven cobots, much like the autonomous buses in the Disney analogy, operate within the existing infrastructure but with greater flexibility and adaptability to change.

Cobots in customer service environments are designed to interact naturally with customers, providing responses and solutions in real time. They are programmed to understand and process human language, gauge sentiment, and even personalize interactions based on customer history and preferences. This level of interaction is not merely about following a script. It’s about understanding context, much like how an autonomous vehicle interprets and reacts to its surroundings.

One of the key strengths of cobots is their ability to customize and adapt, flexing the rules like a human would. In a customer service context, this means being able to address multiple customer needs at once, with each interaction tailored to the individual customer’s specific issue. This is not replacing human agents, but rather enhancing their capabilities, allowing them to focus on more complex, nuanced customer interactions where human empathy and understanding are irreplaceable.

As cobot technology continues to advance, we can expect even more sophisticated and seamless integration into customer service environments. The future of customer service is one where AI-driven cobots work in harmony with human agents, each playing to their strengths to provide a customer experience that is efficient, empathetic, and continually evolving.

Embracing the Future of CX with Cobot Technology

In essence, the evolution of cobot technology in customer service is not just a shift in how services are delivered—it’s a transformation in the very nature of customer interaction. From reactive to proactive, from standardized to personalized, and from operational to strategic, cobots are redefining the landscape of customer service, promising a future that is more responsive, efficient, and attuned to the needs of the modern consumer.

These cobots, with their blend of efficiency, adaptability, and continuous learning, are not just tools but partners in enhancing the customer experience. They might not have KITT’s flashing red light or flair for drama, but in the realm of customer service, they are certainly making a similarly impactful entrance. Just as KITT was a harbinger of a future filled with intelligent machines, today’s cobots are a real-world embodiment of that vision.

And I still get to pretend I’m Michael Knight.

To learn more about how Laivly applies the cobot concept to real-world CX solutions, visit www.laivly.com.

Guest post written by Jeff Fettes, Founder and CEO of Laivly.

Laivly’s proprietary artificial intelligence platform, Sidd, enables the world’s biggest brands to leverage AI, automation, and machine learning into their existing customer service programs, swiftly and without extensive integration barriers, with industry-leading agent copilot and self service solutions.

Laivly will be joining us at Customer Response Summit (CRS) in Tucson, March 12-15, 2024. Learn more about CRS Tucson here.

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With the advent of Open AI’s ChatGPT, eCommerce brands have gotten a taste of generative AI. This technology upgrades the agent experience by freeing up their time to develop deeper customer connections, while shoppers are able to solve most issues on their own or reach a human as needed.

The promise of such technology is generating a lot of optimism about where it can take eCommerce — but will AI let personalization remain a key component of the customer experience? Understanding where a tool like ChatGPT comes into play in the service world can answer this question — and show how personalization and automation can coexist.

The Positive Impact of Automation in Action

CX leaders across industries are more capable now than ever of infusing automated customer experiences into their support centers. From more productive self-service to enhanced intelligence, the tangible impacts of ChatGPT can apply across the customer experience.

Of course, the goal of automation is always to give both customers and agents more time, offering simpler solutions for shoppers and allowing support teams to focus on the most important tasks at hand. Automation eliminates the need for customers to reach out about redundant issues. Instead, they can easily utilize self-service options once you do the following:

• Implement chatbots that are easy to communicate with and can handle the most commonly asked questions.
• Use AI to provide consistent product and service information that ensures customers get the correct information every time they reach out.

This is just the baseline of self-service automation. In our recent webinar that we hosted with Thankful, we discussed how ChatGPT makes it possible to train your support infrastructure to make emotionally intelligent decisions — and since the tech is inherently more empathetic than previous iterations of AI, it’s a useful tool for bolstering the loyal relationships you’re building.

Personalization Is Just as Critical

There’s no question that personalization is vital to fostering positive sentiment with shoppers, making them feel like they are being treated as an individual, not a ticket number. Can AI be the solution to meeting these customer expectations?

Customer service agents and shoppers alike might view AI as a robotic solution that can’t offer  the same level of care as a human. But the increasing sophistication of the technology means personalization in AI is no longer a pipe dream.

However, while automated customer experiences can be a major asset in boosting customer LTV (long-term value), driving emotional connections with customers is also essential. Brands must focus on driving empathy and loyalty during the most difficult customer journey touchpoints; otherwise, they’ll fail to capitalize on the moment and ultimately disappoint customers.

Agent Capability Is the Missing Link

The new frontier of automation is encouraging and can be an enormous boon to your ecommerce business. But it’s still a singular piece of a more intricate formula for success — without a support staff that embodies the same ethos of personalization and can leverage the functionality of that AI, customer service will still hit a threshold.

Think about how a more holistically trained staff can elevate the application of AI. Typically, agents bring up customer information in conversation to provide personalized service. Highly advanced AI, like ChatGPT, draws on transparent data from integrated systems to provide your customers with even better, more personalized self-service experiences. These improved hands-off interactions work whether customers contact your company on channels like chat and SMS or over the phone and through email. The potential for loyalty-boosting personalization is endless:

• Identify the customer issue faster based on previous purchases and conversations and proactively recommend a solution right away.
• Create intelligent answers to nuanced customer questions by synthesizing solutions from your internal database of product and customer knowledge.
• Deliver personalized messages on prioritized or preferred channels during a shopper’s unique peak purchasing periods to drive them to shop more.

Fundamentally, AI is a mechanism of empowerment — making a support agent’s every move more successful. This effect should also carry over to agent happiness, which is the overall state of satisfaction and autonomy your staff feels in the workplace. Achieving this happiness comes from a carefully crafted recipe:

• Soft skill training to allow for open conversations with customers, empathetic communication, and deeper connections
• Hard skill training that includes in-depth product expertise and the ability to create revenue opportunities through upselling and cross-selling
• Complementary automation that makes the implementation of the above skills more effective per use case while never undercutting on personalization

At the end of the day, personalization and loyalty are two sides of the same coin. Achieving the latter is only possible when the former is optimized. You can start planning how your ecommerce brand can be a leader in AI-driven personalization by transforming your infrastructure to better elevate automation for truly dynamic customer service.

Automated Customer Experiences Are the Future

Much of the discussion around ChatGPT’s possible uses in the service space has been inconclusive (albeit optimistic). But we do know automation breeds efficiency. Layering this new technology into your support architecture, under a unified platform that supports all channels and agents, will generate faster responses and decision-making across your organization. When you feed automation tools the right data and apply it effectively, you can actualize the true promise of personalization — valuable, long-term relationships with loyal customers.

Gladly has seen numerous customers take a technological leap with highly efficient, AI-driven support. Our platform is on the cutting edge of service and is aiming to easily incorporate ChatGPT and similar third-party options to develop its potential even further.

Guest blog post written by Gladly. To learn more about this topic and others, visit Gladly’s events page to check out all of  their upcoming events.

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Click here to catch up on Part 1 – Customer Expectations, Part 2 – Channels, and Part 3 – Operations.

The fourth installment of this series focuses on thoughts on technology.

• AI will begin to automate tasks for the agent and the customer – however AI will take longer to mature than previously thought, due to data infrastructure not mature enough to fully leverage.
• Companies will begin to shift from handling transaction to personalizing service.
• Digital will continue to experience strong growth, powered by mobile usage.
• Messaging channels will continue to grow social volumes.
• More conversations around the “social ethics” of AI deployment.
• Continued push on technology – moving infrastructure to the cloud.
• Deep/machine learning will play a role in 2018 for brands to meet customers where they are. I think brands are starting to get on board with the concept of machine learning and using data to predict behavior. But deep learning can extend beyond things like chatbots. If a brand can predict what a customer might be looking for, it can tailor content to the customer that allows the customer to self-service, send push notifications, etc.
• Thinking about AI secondarily to the types of use cases and outcomes desired that require it.
• Companies will have to address AI and ML in their strategies for customer acquisition and engagement. 2017 may be seen as a year of hype as lots of new vendors emerge on the scene. Expect consolidation and actual AI/ML deployments to increase in 2018.
• Interest in – and deployment of – customer journey analytics tools will increase, as companies try to identify and solve problems upstream before they occur.
• Strategic enterprise automation (front to back office) will help businesses begin to improve the customer experience, while optimizing back office operations, leading to stronger sales and a better bottom line. Examples include automated machine learning/AI, self help, chatbots/avatars, to RPA and beyond.
• People continue to overestimate innovation in the short term and underestimate it in the long term.
• We will see the first practical examples of AI in the areas of contact center routing, compliance and quality, with practical use cases.
• Some brands are testing AI for knowledge management (ie. agent support tool powered by AI vs. a traditional knowledge management tool). A lower risk approach to testing AI vs. directly with clients.
• Over the next 3 to 5 years, I believe that the majority of inquiries that come into the contact center will no longer be voice or email, but some form of messaging. SMS is only one form of messaging: it encompasses a broad swath of methods including iMessage, Facebook Messenger, Kik, WhatsApp, and more. Many people are following WeChat, which is now one of the largest standalone messaging apps with over 963 million monthly active users. Part of the reason it has been so successful is that you can do more than just send messages. Apple is moving down the path with the announcement of its Business Chat messaging solution which is an extension of iMessage and will include some ApplePay capabilities. The convergence of these technologies will be what ultimately tips the scale to shift consumers and businesses away from phone and email to messaging.
• Maturity issue with emerging virtual assistance technologies (chatbots, AI capabilities, etc.), continues to lag – requirements for specific user case studies at an all-time high.
• Buzz and hype are high, but adoption is low. Brands realize they need more data in order to leverage these technologies to be accurate.
• I’m not convinced that brands have the capacity/talent/full understanding of what precisely goes into machine learning and true AI (beyond chatbots). I think we’re going to see a wave of failed adoption on that front.
• Technology – Proliferate of technology out there – from measuring CX, to ‘omnichannel’, to speech analytics.

Stay tuned next week for the final installment in the series Part 5 – Use Case Studies/Data and Security/Risk. 

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The following is a guest blog post from Greg Sherry, Vice President Marketing at Verint. For more information about Verint, visit their website. 

Thank you for taking part in Verint’s interactive general session at Customer Response Summit Las Vegas called “Customer Engagement LIVE!”  where we broke into discussion groups for interactive discussions and summary read back presentations. Here are some of the recommendations we heard from the groups as part of the breakout group notes and read backs:

What’s Old Is New Again. When is the last time you received a handwritten note or personal email from a business you engage with? It was memorable, wasn’t it? Think of ways you can incorporate genuine, personalized touches with customers. The strategy can be scalable: one “wow” moment can generate genuine delight and powerful word-of-mouth amplification.

Think Mobile. Do you have a mobile strategy? The need is clear: provide information, customer support, “wow” moments via mobile channels. But be careful: consumers often have limited ability to “digest” content you are sharing with them (because they are at the airport, walking, at home, multi-tasking), so be sure your content and communications are as short and to-the-point as you can.

Establish a common knowledge base across all channels to ensure consistent response. One company recognized the need to consolidate contact center systems to a single agent desktop. Customer service agents had difficulty serving customers in a timely manner and providing accurate information because information resided in 13 disparate systems. By consolidating all the systems into one agent desktop view, the company quickly reduced agent average handle time (AHT) and saw increased customer engagement scores. The unified access to the applications and information also increased employee productivity and helped provide a personalized experience for customers.

Develop a Journey Map as Part of Your Customer Experience Strategy. Our group defined a journey map as a diagram that illustrates the steps your customers go through when they engage with your company, across different channels and touch points. The more touch points you have, the more complicated — but necessary — the journey map becomes. Creating a customer journey map is an investment but is well worth the cost. For some creative ideas on journey maps, check out this recent blog post by Verint’s Nancy Porte – Five Tips for Building a Customer Journey Map.

Millennials/Diverse learners. Move away from phone to proactive chat; offer chat if automated resolution doesn’t work. Find ways to be “proactive” with communications when you anticipate that a customer’s expectations won’t be met.

Develop a Comprehensive Work-From-Home Strategy. One great reason to offer work from home is that you have the ability to recruit some of your organization’s biggest “fans,” regardless of their location. If you offer part time or flex time, you could have highly enthusiastic providers of information – and raving fans – who support your solutions or services. The customer experience these fans deliver could be very meaningful.

Use analytics not just for customer projects, but also for agent performance and metrics. Many companies use in depth analysis for customers, but more straight forward measurements for agents (AHT, quality score, Adherence etc.) Look at ways you can analyze agent performance more to impact customer experience. Identify which associates have the best cross selling abilities? Use their recorded interactions to train others. Who are the agents with best overall cx abilities?  Have “gold” and “platinum” customers (highest value customers) routed to them since they are top in delivery of CX. Drive pilots of business changes based on analysis/date- and “go big” with winning ideas. Also explore further: how can you provide different levels of service based on the “value” of your clients to your business.

Drive customer experience excellence while also handling call-types that are more and more complex. One organization is leveraging contact recording and speech analytics to determine the reason for calls that fall into the highest 10th percentile of average handle time, which are the longest calls. We can’t solve everything, but we believe that if we can “fix” the issue(s) that cause the top three to four call types, we can free up resources and focus that will help us enhance the customer experience.

Build the Feeling of an In-Store Experience Online. Meet customers at the right moment when they are challenged. Know when they are about to defect. Provide the support they need when they need it. (How are you doing in this area? One idea is to implement a journey map project as mentioned above.)

Consider an Automation Pilot. Organizations are under pressure to increase processing efficiency and productivity, reduce errors, cut operational expenses, and maintain security and regulatory compliance. Key advancements in the areas of robots/bots, artificial intelligence, and machine learning are creating opportunities to service and engage with customers like never before.

Organizations should consider automating repetitive and time-consuming processes, allowing employees to focus on more complex tasks, cross-selling and delivering a personalized experience. The net: position automation as beneficial—and not a threat to your employees’ jobs.

Do you have some creative or best practices ideas to add? We’d love to hear those, too! Help us continue the conversation and submit your idea on Twitter by using the hashtag #CustEngLive. You can also follow and tag us on Twitter @ExecsInTheKnow and @Verint.

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