That’s exactly what our upcoming virtual event, Practical, Real-World Application: Rapid-Fire AI Use Cases for Customer Experience, is built around. You’ll hear directly from our expert panelists on testing, deploying, and scaling AI. They’ve worked with the world’s leading brands, and now they’re ready to share what works.

Turning Pilots into Progress

Nearly 90 percent of brands are experimenting with AI or plan to do so in the near future. However, according to recent research, more than half of all CX leaders report that their AI strategies are still falling short, particularly in terms of complex interactions and achieving real business impact.

Each expert panelist will take you inside a real-world AI use case to share what sparked the initiative, how they built momentum, where they faced resistance, and what happened on the other side.

You’ll get a rapid-fire tour of successes and stumbles across various industries and functions. From operational wins, such as agent assist, to customer-facing innovations like predictive service, this is your window into what’s delivering a return on investment (ROI).

Closing the Execution Gap

AI isn’t a magic button. But it can be a game changer if you know how to move from strategy to execution.

You’ll hear how top brands bridged the gap between idea and implementation, how they addressed budget, stakeholder buy-in, integration challenges, and scaling hurdles. These are the stories your team can learn from, adapt, and act on.

Come for inspiration. Leave with a roadmap.

Why Now

The AI conversation is now strategic. And whether you’re just starting out or scaling fast, there’s urgency to figure out where AI works and where it doesn’t.

This virtual event is timely and essential. With CX pressure mounting and the pace of innovation accelerating, the brands that will win are those that can operationalize intelligent, human-centered AI today.

Join Us on July 15 (1-2:30 PM ET)

This virtual event is exclusively for corporate brand CX leaders shaping the future of service, support, and experience.

Moderated by Execs In The Know President Chad McDaniel, it is designed for clarity, candor, and conversation. Ask your most challenging questions. Learn from your peers. Walk away with ideas you can act on.

Seats are limited. Reserve yours now.

The post Inside the AI Use Cases Delivering Real CX Results appeared first on Execs In The Know.

Recent surveys indicate that only 15 percent of consumers express high satisfaction with the self-service options provided by businesses today. The challenge is clear: meeting and exceeding consumer expectations in the realm of self-service.

Enter the era of intelligent virtual assistants and BrandGPT, a transformative AI architecture pioneered by innovative platforms like Knowbl. Instead of focusing on the brand, let’s delve into the broader trends reshaping the customer service landscape.

The paradigm shift toward self-service isn’t just about cost reduction for businesses; it’s about meeting evolving consumer expectations. As we navigate this dynamic landscape, it’s crucial for businesses to understand the key factors influencing the future of customer engagement.

Understanding the Self-Service Dilemma

Consumer dissatisfaction with current self-service options highlights the need for innovative solutions. Rather than solely promoting products, businesses should explore the untapped potential of leveraging AI to enhance customer experiences.

The Role of AI in Crafting Next-Level Experiences

Embracing a customer-centric approach, AI-powered virtual assistants are emerging as game-changers. These intelligent companions, trained on diverse brand content, offer clarity throughout the customer journey. Knowbl’s BrandGPT, for instance, transforms the customer experience by delivering intelligent responses tailored to each phase of the journey.

Addressing Chatbot Concerns

The pitfalls of irrelevant responses from chatbots are well-documented. Such as in a recent case where an AI assistant for a car dealership in California ended up pointing customers in the direction of their competitors. However, the solution lies in training AI models on the brand’s authentic content. By making the brand’s information fully accessible through AI, businesses can provide relevant self-service intelligence with speed, ease, and scalability.

Reducing Operational Costs and Boosting Revenue

The integration of AI, particularly platforms like Knowbl, isn’t merely a customer-centric strategy; it’s a strategic move that holds the potential to revolutionize a company’s operational landscape. Beyond the realm of enhancing customer satisfaction, the impact extends to the very core of business operations.

1. Operational Efficiency Through Streamlined Setup:

Knowbl’s unique self-learning AI model is a game-changer in the realm of operational efficiency. Unlike traditional AI engines that often require months of intensive training, Knowbl’s approach is characterized by an effortless setup. The platform eliminates the steep learning curve, requiring only a data source such as a website URL or knowledge base. This not only accelerates the deployment of AI-powered solutions but also significantly reduces the associated operational costs.

2. AI-Powered Conversational Solutions Across Channels:

Once trained, Knowbl provides AI-powered conversational solutions that seamlessly integrate across a brand’s digital channels. This comprehensive accessibility ensures that the benefits of AI-driven efficiency extend to various touchpoints of customer interaction. Whether it’s through a website, mobile app, or social media, the consistent and intelligent assistance enhances user experience, driving operational efficiency and reducing the need for extensive customer support teams.

3. Strategic Cost Reductions Through Automated Processes:

The strategic implementation of AI, such as Knowbl’s BrandGPT, facilitates automated processes that contribute to significant cost reductions. By automating routine tasks and responses, businesses can redirect human resources towards more complex and value-driven activities. This not only optimizes the allocation of human capital but also generates cost savings by minimizing the need for extensive manual interventions in customer interactions.

4. Scalability: A Path to Revenue Growth:

Scalability is a pivotal aspect of Knowbl’s AI architecture. The ability to handle a growing volume of customer interactions without a proportional increase in resources positions businesses for scalable growth. As operational efficiency improves, the potential to accommodate a higher volume of transactions, inquiries, and engagements becomes a catalyst for revenue growth. The platform’s unlimited scalability ensures that businesses can adapt and thrive in dynamic market conditions.

In essence, the reduction of operational costs and the boost in revenue aren’t isolated outcomes of AI implementation; they are interconnected facets of a strategic transformation. Knowbl’s commitment to simplicity, accessibility, and scalability lays the foundation for businesses to not only meet but exceed their operational and revenue objectives through the efficient deployment of AI-driven solutions.

Mitigating Risks with Innovative Features

As businesses embark on the journey of integrating AI into their operations, it’s crucial to address and mitigate the associated risks effectively. Platforms across the industry are introducing innovative features to ensure a smooth and risk-free experience, making AI more accessible and adaptable to diverse business needs.

1. Contextual Enhancement and Low-Code Accessibility:

To tackle the challenges often associated with generative AI, cutting-edge platforms are introducing features like contextual enhancement. These features automatically add context to a brand’s content, ensuring that AI interactions remain relevant and aligned with user expectations. Additionally, the rise of low-code options is reshaping the landscape, allowing teams without extensive coding abilities to deploy and manage AI assistants effectively. This democratization of AI empowers businesses to harness its potential without being hindered by technical limitations.

2. Dynamic Content Updates and Gap Filling:

One of the evolving strengths of AI-driven virtual assistants lies in their adaptability. Innovative platforms recognize the importance of easy content updates and gap filling as users interact with AI assistants. Businesses can now seamlessly update content, refine responses, and fill knowledge gaps as they discover them. This dynamic approach ensures that the AI remains responsive and relevant, reflecting real-time changes in user needs and industry trends. The ability to refine and adapt AI models without extensive technical expertise promotes agility in response to evolving business requirements.

3. Sandbox Testing for Risk-Free Deployment:

A critical aspect of risk mitigation is the introduction of sandbox testing features. Before AI solutions go live, businesses can leverage sandbox environments to test and fine-tune functionality. This allows teams to observe how the AI will perform in real-world scenarios, identify potential issues, and make necessary adjustments. The risk-free deployment approach ensures that businesses can confidently integrate AI into their operations without the fear of unforeseen complications.

4. User-Friendly Interface for Seamless Interactions:

Innovation extends beyond the technical aspects of AI platforms; it encompasses user interfaces designed for seamlessinteractions. Platforms are prioritizing user-friendliness, ensuring that team members across various departments can easily engage with and manage AI assistants. This accessibility minimizes the learning curve associated with AI deployment, fostering a collaborative environment where non-technical stakeholders can contribute to the success of AI initiatives.

The landscape of AI risk mitigation is evolving, with a focus on accessibility, adaptability, and user-friendly interfaces. By leveraging features such as contextual enhancement, low-code accessibility, dynamic content updates, and Sandbox testing, businesses can navigate the AI landscape safely. These innovative approaches not only mitigate risks but also empower businesses to unlock the full potential of AI without the need for extensive technical expertise.

Empowering Customers to Discover, Learn, and Convert

In the decision-making process, consumers seek relevant information. Knowbl’s virtual assistant becomes an invaluable ally in helping customers discover, learn, and convert by tapping into the wealth of information available.

In conclusion, the future of customer engagement lies in harnessing the power of AI for self-service solutions. By understanding industry trends, businesses can position themselves as leaders in providing intelligent, customer-centric experiences.

Guest post written by Abby Nichols, Marketing at Knowbl.

To learn more about AI in self-service go to: www.knowbl.com

Knowbl provides a patented AI virtual concierge platform, optimized to be the fastest time to answer for inquiries and customer transactions. Our businessuser-friendly platform is simple and intuitive, enabling departments and businesses to give accurate support more efficiently and effectively.

Knowbl will be joining our Tech Forum at Customer Response Summit (CRS) in Tucson on Wednesday, March 13, 2024, to discuss Mastering the Lifelong Customer Conversation Across Channels in 2024 and Beyond. Learn more about CRS Tucson here.

The post Revolutionizing Customer Engagement: The Rise of AI in Self-Service appeared first on Execs In The Know.

The brand specializes in designing and manufacturing high-quality bicycles for children. Their eye-catching designs, innovative features, commitment to safety, and boundless fun factor create an experience that is second to none. woom was founded by two dads in a garage in Vienna, Austria in 2013 and has since expanded to over 25 countries around the world.

With just 1,400 bikes sold in the first year on U.S. soil, that number skyrocketed to more than 52,000 bikes in 2022. And that number just keeps on growing! In March, the brand celebrated 10 years of “Magic Moments” and has been recognized by Inc. Magazine as one of the fastest-growing companies in America.

In a recent conversation with April Obersteller, Director of Global Experience at woom, she shared how the brand approaches employee experience (EX) and customer experience (CX), its strategy for connecting with customers, and the “Magic Moments” that set children up for a lifetime of happy cycling.

Execs In The Know: Tell us a little bit about your background and how you came to be at woom Bikes. What is your day-to-day focus in your current role?

April Obersteller: It’s always fun to do that retrospective and look back on the thread that led me here. My background is in a couple of different industries, and that thread was service and being part of the beautiful chaos. You know, what some people consider chaos is my thrive zone; it’s the fun zone. I began my career in the hospitality industry focusing on weddings and I loved it! I loved its dynamics and being part of bringing those magic moments to life on one of the most important days of people’s lives. I did that for more than 10 years. Then, there was that itch to try something new. That’s when I hopped into the product world as one of the first employees for a startup. The goal was to take a natural first aid product from the farmer’s market and bring it to the masses.

Truth be told, I had no clue what I was doing half the time. I knew the product and was a super user of the product. The challenge was bringing it to scale, and we were able to accomplish that. So, I decided to keep on that path but decided to do it here at home in Austin. That’s when my journey with YETI began. At the time, the company was around 100 people. I started on the sales side and represented Texas and that’s where the magic opportunity came for me to move into CX.

I immediately fell in love with directly connecting with the customer and I also fell in love with the team. It was quite the ride with everyone crammed into one little office. It was in this role that I began thinking about how to approach EX and CX together. Today, I get to do both, and woom Bikes was brave enough to see the connection between the two and make it part of the brand’s organizational structure. 

EITK: Since joining the brand, what company-wide initiatives have you implemented or improved as it relates to EX and CX?

April: When I joined woom Bikes, the U.S. and European markets were separate entities. From a CX perspective, the brand was hitting the baseline in the service channels, and in the data insights, and it was hitting the baseline in setting our team up for success. What did our KPIs look like? What did our training look like? None of those things were in place just yet. Today, all of them are in place, and it was so beautiful to see everything come together.

From the EX side of things, we also heavily invested in baseline. Those functional features are business partnerships, operations, intentional engagement, and L&D. One of the deepest for us has been the voice of the customer. For a company of our size, this is huge. We realized that when we know better, we can do better. So, we went all in! It’s been a game changer because it has allowed us to build trust with both our customers and our team members.

The magic that we saw during the pandemic, especially with the increase in those first-time cyclists, got us thinking about how we could keep people on bikes and what that looked like. So, while loyalty and service have always been at the core of the brand, we knew we needed to get post-purchase behavior, word of mouth, and Net Promoter Score (NPS) right. As a company, we believe there should be more bikes than cars on the road. And to do that, we need more kids to fall in love with cycling and make it a part of how they live daily. 

EITK: When it comes to technology, in what ways is the brand differentiating itself from its competitors to improve CX?

April: When it comes to technology or accessibility, that’s where we’re just having some fun with it. Our video consulting from a service side with our bikes is very popular. As you may know, some bike shops are known to be intimidating if you are not familiar with cycling. Additionally, we only sell direct-to-consumer right now, and this is one way we meet them where they are. Whenever they have a question about their bike, we’re able to serve those customers in real-time vs. telling them to take their bike to a shop.

Our number one goal is to show up for them in an accessible way. The technology we have is great but we are continuing to get more sophisticated. We haven’t explored all the beautiful capabilities artificial intelligence (AI) and text analytics have to offer, yet. It’s certainly on the roadmap but there are some other priorities that we’ll be diving into first.

EITK: What does it mean to create a people-first culture in 2023?

April: We need to be asking the important questions: “How does this impact the person? How does this impact my team member? How does this impact the customer?” Let’s say you’re laser-focused on your supply chain, it tends to be more focused on the product but the responsibility is still there to keep the people at the center of all the decisions. There must be a healthy tension between business needs, people, and profit. It’s about accepting the belief that if we’re going to have any kind of long-term impact, we must be holding each other accountable for getting better at it. The responsibility of creating a people-first culture must be owned by everyone across the organization and not happen in a silo.

EITK: When you look ahead to the rest of 2023 and beyond, what new initiatives are you excited about?

April: One brand initiative I can share is our commitment to continuing to show up and take those steps to meet our customers where they’re at. I’m excited about how our customers experience our product and we are committed to rethinking how we can expand these magic moments. 

We have an internal Slack channel called ‘Magic Moments,’ where we share our stories, which boils down to so much of our brand’s reason for existing. We also offer tons of education about cycling, which is important to us. It’s about creating those magic moments and following untraditional paths.

EITK: What’s a magic moment at woom Bikes that has resonated with you?

April: I love this question! A magic moment that resonates with me happened about a year ago. It was right around Father’s Day when a customer reached out to us with a beautiful email. He had lost his daughter and when he was finally able to look through photos of her, he realized that so many moments of happiness captured had a woom in the background. 

He told us how woom was part of his daughter’s most joyous moments. The father also shared her values, and two out of the three values that he shared aligned with our company values. I love that we get to be part of these moments and that we are aligned with the people we are serving. I always get teared up thinking about this story, and I feel so lucky and honored to have this opportunity.

EITK: When you think about the work you do now, is there something that you wish you’d known before you got into this industry?

April: That’s a good question. In terms of CX, I wish I would have known how customer service and CX, in general, translate into financial impact and be able to speak to what services mean to a business. Initially, I didn’t know how to do that or make that connection – whether that be between the data or the EX and how it translates to our customers to tell the full story.

This has all been an incredible learning experience for me, and now I’m seeing the results from it. It’s great to be able to look back and see those little moments along the way.

EITK: What do you think is woom’s CX magical power?

April: I do think woom has a magical power, which is the brand’s ability to create a space for the customer to be acknowledged. I think that’s magic all on its own. In a world that’s so fast and so noisy, it makes a big difference to create that space and say, “I hear you and I’m here for you.”

A big shoutout and thanks to April for her leadership and participation. Interested in learning more about woom Bikes? Head on over to their website, Instagram, or LinkedIn.

The post Q&A with April Obersteller, Director of Global Experience at woom Bikes, One of the Fastest-Growing Companies in the U.S. appeared first on Execs In The Know.

Despite uncertain economic times, contact centers can save money by implementing the following four strategies focused on increasing efficiency without sacrificing customer experience.

Implement Automation

Automation, such as Intelligent Virtual Assistants (IVA), can handle routine inquiries, reduce agents’ workload, and free up their time to manage more complex customer issues.

To underscore this point, HFS Research found that automation is the number one initiative currently underway to support enterprises in meeting their strategic priorities.

Vistra Energy, one of the ten largest electric companies in the U.S., is one example. Vistra used an IVA to handle its large call volume, resulting in a 20% increase in call containment and reduced operation and IT costs.

Provide Self-Service Options

Self-service options reduce the need for customers to interact with an agent, saving the contact center money.

Such was the case with Salt River Project, a large public power utility. The company needed a flexible customer care solution to help reduce customer service costs. It deployed a conversational virtual solution that increased customer satisfaction, reduced dependence on costly seasonal live agents, and improved self-service rates to 35%.

Optimize Staffing Levels

Automation alone is insufficient to ensure excellent customer experience; humans are needed, too. However, contact centers can save money by optimizing staffing levels, ensuring enough agents are available to handle customer inquiries while minimizing the number of idle agents.

Improve Call Routing

Contact centers can use intelligent call routing to quickly direct calls to the most appropriate agent or department, reducing AHT and increasing CSAT.

The email marketing company, Constant Contact, needed a way to streamline their customer service queue and improve cost savings. The company implemented an IVA, which resulted in a 15 to 30 second decrease in AHT and freed agents to address more complex issues.

Conclusion

“This, too, shall pass” is a helpful mantra to remember during difficult economic times. Inflation is temporary. The economy will improve. In the meantime, contact centers can use these four strategies to save money and offer quality customer service.

Guest blog post written by Peter Mullen, Chief Marketing Officer, Interactions. To learn more about how Intelligent Virtual Assistants can save your company money, go to www.interactions.com.

Interactions provides Intelligent Virtual Assistants that seamlessly combine artificial intelligence and human understanding to enable businesses and consumers to engage in productive conversations. 

To learn more about this topic and others, visit the events page to check out all of our upcoming events.

The post How Contact Centers Can Save Money During Uncertain Economic Times appeared first on Execs In The Know.

So is there new hope on the horizon, despite the decade-long graveyard of broken chatbots and dashed automation and self-service promises?  Indeed, there is – and/but, some context and clarity are needed to ensure we as a CX community don’t retrace the same steps and mistakes from the previous chatbot chapter(s).  A CX leader at a large financial services company recently told me in passing that he had just “asked his team to look into how they could use ChatGPT in their business.”  We’re guessing many CX leaders are asking this same question and thought this post would be helpful in kick-starting new journeys toward much more elegant and impactful CX self-service and automation.

Let’s start with demystifying ChatGPT and the core technology enabling it…

ChatGPT 101

ChatGPT (Chat Generative Pre-Trained Transformer) is the ‘branded’ chatbot developed by OpenAI and launched in November 2022. A “ChatGPT for Dummies”, which we all appreciate, explains it in layman’s terms. ChatGPT is built on top of OpenAI’s GPT-3 family of large language models (LLMs).   It is THIS bit of core technology – the LLMs, and not ChatGPT itself – that is the most important and game-changing as it relates to brand-specific CX utility and impact.  So let’s briefly dive into the world of LLMs, and what makes them so powerful.

LLMs: What Are They, and Why Should We Care?

By definition, a large language model (LLM) is a deep learning algorithm that can recognize, summarize, translate, predict, and generate text and other content based on knowledge gained from ingesting massive datasets.  (For those new to the concept of LLMs in general, this article from Kyle Wiggers offers an excellent overview)².  In practice, ChatGPT’s chatbot is a perfect example of this in action, as the LLMs powering it were trained using massive text databases sourced from the internet.  How massive?…

• 570 GB worth of data obtained from books, webtexts, Wikipedia, articles, and other pieces of writing/content on the internet
• 300 billion words fed into the model
• 175 billion parameters

By ingesting all of this data (with ongoing supervision and tuning – more on this later), the LLMs effectively pre-trained ChatGPT (hence, the ‘P’ in ‘GPT) to recognize and respond to context, intent(s), varied speech and language patterns, among many other things.  For CX leaders and practitioners, especially those who have been wrestling with time-consuming legacy approaches to building chatbots and other types of self-service/automation, THIS is the absolute game-changing bit.

Pre-trained LLMs come with thousands of recognized intents ‘out-of-the-box’ – no more intent identification and bot training, one intent at a time.  Pre-trained LLMs recognize variations in speech and language ‘out-of-the-box,’ welcoming natural ‘human’ conversational ways of speaking – no more rigid, ‘robotic’ language within your chatbots and self-service protocols.

Given the above, pre-trained LLMs move fast – no more waiting for months to deploy even a single, simple use-case chatbot.  These use cases alone are driving double-digit percentage increases in customer self-service across industries, as well as double-digit percentage decreases in contact center volume and associated operational costs – and this is before we even approach the generative (‘G’ in ‘GPT’) capabilities that can impact revenue-generating use cases like sophisticated cross-sell and upsell, and loyalty programs.

Now that we understand the value-driving capabilities of LLMs, it’s also critical to understand the watch-outs and challenges associated with applying this technology to brand-specific CX strategies and programs.

LLMs for CX & Self-Service Automation: With Great Power Comes Great Responsibility – Be Careful and Purposeful

Shortly after ChatGPT’s release, and amidst all the immediate excitement surrounding it, OpenAI Chief Executive Sam Altman tweeted the following public service announcement:

“It’s a mistake to be relying on it for anything important right now. We have lots of work to do on robustness and truthfulness.”

This type of warning might seem counter-intuitive, if not downright confusing, coming from the CEO of the most-talked-about technology in recent memory.  But he has good reason for extending such caution at the moment.  One of the biggest strengths and challenges with LLMs is that they’re typically trained without much supervision, per our brief mention earlier.  In the context of AI, ‘supervision’ is the component of training where an external entity, usually human, provides “correct” answers to the AI as it learns its way forward.  On one hand, supervision is very expensive, so removing supervision can greatly increase the amount of data the AI can be trained with, as well as time to launch/value.  However, removing supervision also means that the AI might learn incorrect behavior.  There are already numerous articles highlighting ChatGPT’s inaccuracy, and in some cases its ‘creepiness.’  Following Mr. Altman’s lead and guidance above, OpenAI and Microsoft (its primary investor) continue to iteratively install more guardrails and limits on ChatGPT³ as they learn more from the market and its usage.

For business and CX purpose, there are two primary areas where brands need to be cautious and thoughtful when considering employing LLMs in their CX strategy.  The first is around supervision – specifically, the lack of supervision of LLMs can lead to many mistakes if/when the AI directly generates responses.  Some examples include:

• The AI produces responses that appear to be correct or reasonable, but are, in fact, false.  These LLMs understand the relations between words and context, but do not have logical reasoning capabilities.  This is problematic because the AI might use a sequence of reasoning it found in training, but in an illogical context.  For example, if you ask the AI to provide details about the credit card with a 3% interest rate, it might splice the credit card details with a savings account details to invent a fictional credit card that has a 3% interest rate.
• The AI might ignore certain context in the user’s question or use content that depends on specific context.  For example, if a brand offers a basic tier and a premium tier service offer that have 9-5 support hours and 24/7 support hours, respectively, the AI might respond to a question like “Are you open 24/7?” with “Yes, we are open 24/7 to support our members,” when the hours are actually dependent on the user and specific offer.
• The AI provides answers that are a violation of compliance or even inappropriate content.  Since the AI is trained on massive corpora, including potentially online discussions, it will have learned to respond in ways that are not acceptable in a business setting.

The second area of caution, which has been somewhat surprising to us, is that some brands are attempting to use LLMs as a development tool rather than a customer-facing one.  Specifically, their intent is to leverage LLMs to generate content and training data in service of their traditional/legacy conversational AI solutions – with the hypothesis being that they can significantly reduce the amount of effort that goes into building a chatbot.  However, brands attempting this approach will still concede large benefits associated with LLMs, including:

• Data biases.  The content generated by LLMs is trained using specific terminology and will use certain terms more than others.  Previous-generation models learn based on patterns, so if a specific term shows up frequently, the model might incorrectly learn that term implies a specific intent or meaning.
• Lack of deep understanding.  The data that LLMs produce is only data, though highly predictive – specifically, the conversational context and deep understanding of what the user needs based on multi-turn conversations.  While the LLM has these understanding capabilities, the same capabilities will not be passed down to previous-generation models.  So, any contextual understanding will still need to be manually engineered by the development team, which defeats the purpose of LLMs in the first place.
• Intractable data requirements for complex conversational flows.  Multi-turn conversations, particularly ones where the user is trying to complete an action, present an innumerable set of potential conversational flows.  While an LLM could theoretically produce data for all of these conversational flows, the time requirements to produce the data and train the previous-generation model would be intractable.

‘Caution’ Does NOT Mean ‘Stop’:  The LLM-Powered Knowbl Platform

While the cautions and challenges noted above should not be ignored, neither should the benefits of applying LLMs to your CX strategy in the very near-term – especially if improved self-service, chatbots, and automation are on your strategic agenda.  It’s the very limitations discussed above, along with the ongoing challenges of building chatbots and automation in general, that led to the start of Knowbl.  We set out to leverage the massive advantages LLMs have over traditional conversational AI technologies for brands where CX, NPS/CSAT, compliance, and brand image are critical. By designing and building a transformer-first platform, that solves the hardest part about conversational AI management (few-shot extraction, automated context management), we are able to utilize the full robust understanding and generative capabilities of LLMs, while also avoiding the limitations of minimal supervision, content inaccuracy, and lack of brand control over the AI.

While the Knowbl platform offers all of the functionality seen in traditional conversational AI platforms, its LLM-based intelligence unlocks new features, capability, and business control that drive vastly improved CX outcomes.  Three specific highlights include:

• Ingestion of brand-approved content to automatically generate conversational flows, responses, and intents.  Using few-shot learning, the content alone provides a reasonably robust intent training set out-of-the-box.
• Identification and diagnostics for misunderstandings.  One of the key challenges when using LLMs is that they’re large black box models.  However, as experienced practitioners, we recognize the need to quickly recognize and resolve issues surfaced by the AI.  To this end, we enable a quick development cycle through model explainability and quick incremental model training processes.
• Transactional experience support.  For brands, transactional experiences can represent critical, revenue-generating functionality in chatbots.  The Knowbl platform enables transactional experiences easily by utilizing LLMs to handle slot/entity extraction much more easily and efficiently than a traditional conversational AI platform would.  Rather than requiring thousands of training examples to build a transactional experience like a traditional platform, LLMs allow the Knowbl platform to learn with just a couple examples.

Using these building blocks and more, Knowbl is enabling brands to deliver on their authorized and compliant CX promises and conversational AI/automation objectives in a fraction of the time (compared to traditional models), with increased breadth of capabilities, accuracy, and control.

¹ UJET Research Reveals Chatbots Increase Frustration for 80% of Customers, UJET Research / Businesswire, December 6, 2022

² The emerging types of language models and why they matter, Kyle Wiggers, TechCrunch, April 28, 2022

³ Microsoft Considers More Limits for its New AI Chatbot, Karen Weise & Cade Metz, New York Times, February 16, 2023

Guest blog post written by Knowbl. Visit Knowbl.com or drop us a line at info@knowbl.com to learn more about how leading brands are starting to employ LLMs to drive their CX agenda and strategy.

To learn more about this topic and others, visit the events page to check out all of our upcoming events.

The post Navigating the ‘Magic’ (and Caution) of ChatGPT & Large Language Models (LLM) for CX: A New Era for Self-Service & Hyper Automation appeared first on Execs In The Know.

Think of the last time you found out about a new brand or product/service that intrigued you. What did you do to learn more about it?

Well, if you’re like 87% of shoppers out there, you began your discovery research online, starting with the brand’s web/mobile sites – its ‘Digital Front Door.’

And as you reflect on that experience, how was it? Were you able to find what you were looking for, and was it fast and easy? Were you able to get your questions answered quickly and clearly? Did you have to contact anyone for additional information because you got stuck? Overall, how did the experience compare to the last great experience you had with a different brand?

The Journey Is Broken in 2 Key Areas: Discovery & Consideration. Why…?

As customer experience (CX) professionals, we seem to place most of our focus on the Buy, Use/Service, and Re-Engage/Loyalty phases of the CX journey, while oftentimes glossing over the initial journey phases of Discovery and Consideration – which are THE first-impression-setters that significantly inform the Buy phase and beyond. AND which, unfortunately, are often broken due to subpar web/mobile site experience(s), outdated knowledge bases and FAQs, and under-performing chatbots, among other factors. Taken together, these factors are breaking a brand’s CX journeys in the critical early stages for one simple reason: They are inhibiting and/or fully preventing the fluid and intuitive self-service experience customers crave.

Further compounding this self-service breakage is that the issue is a meaningful blind spot for many brands. According to NICE’s 2022 Digital-First Customer Experience Report, there is a significant disconnect in how brands and consumers view both the performance and priority of their digital self-service. A few notable statistics tell the story:

• In general: 53% of brands believe their customers are very satisfied with their self-service offerings – but only 15% of consumers agree.
• Optionality & priority: 81% of consumers want MORE self-service options from brands – but 40% of businesses believe they have enough.
• Make it smarter: 36% of consumers want smarter self-service offerings – but only 11% of businesses are prioritizing it.

… And the Stakes Are Very High

The consequences of these broken journeys impeding self-service for brands are incredibly high, especially in the post-pandemic world, where we’ve seen customer behaviors, attitudes, and preferences change dramatically. Consider these four (4) consumer mega-trends that will continue to accelerate and fuel the importance of quickly patching the holes in these journeys:

Combine these renewed customer mandates with the fact(s) that 62% of shoppers have reported giving up looking for what they want to buy due to a poor digital experience (Zona Research), and 52% expect a poor experience when they know a chatbot is coming, the gravity (and price) of the problem further increases (Forrester Research).

This Is Fixable—and Fast

While these journey potholes create significant cost and revenue implications if left unaddressed, there is a way forward. With advancements in artificial intelligence (AI) and machine learning (ML) technology, there is a better way to drive conversational and contextual self-service, and fix your Digital Front Door. At Knowbl we have invented an approach that provides brands speed, ease, and scalability of self-service intelligence derived from the real source(s) of truth – your current content. Depending on your specific intents, you can conservatively shift 7-10% of your current contact center volume to self-service almost immediately – which will significantly drive down operational costs, while simultaneously improving CX and revenue. Stop by and visit us at the technology showcase at CRS, or visit Knowbl.com to learn more about how leading brands are ditching chatbots and delivering on next-gen digital self-service.

About Knowbl

Knowbl provides every business the ability to quickly create conversational AI solutions that can be deployed across any digital user interface, including but not limited to search, chat, voice and agent assist. The Knowbl Platform takes your existing content, structured and unstructured, and automatically conversationalizes it so that your employees and customers can get the information they ask for on demand.

Guest blog post written by Knowbl. To learn more about this topic and others, visit the events page to check out all of our upcoming events.

The post Your CX Journey Is Broken at the Front Door — and You Can Fix It, Quickly appeared first on Execs In The Know.

The following is a guest blog post from Ted Hunting, VP North America Marketing at Genesys. 

Next month, Execs In The Know will bring together service leaders from many of the largest global brands to advance the conversation on creating great customer experiences.  From past experience, it’s a very tight-knit group of CX leaders sharing best practices and ideas around omni-channel customer engagement, across all channels, and empowering employees to deliver great customer experiences.  This community is one of my favorites as the people are super-smart and passionate leaders who openly share their challenges, advice, and ideas –  it’s all about candid discussions and one-on-one engagement and networking.

As a member of the Execs In The Know CX Partner Advisory Board, on behalf of Genesys, I am excited to again join this group and will be leading an educational session with group brainstorming on “Journey Analytics and Effortless/Personal Keys for the Next Era of CX” on September 20th. The session will discuss how you can use journey analytics and new digital approaches to orchestrate an “outside in” customer journey that is more personal and predictive, while reducing effort. We will also share best practice use cases where AI, bots, digital self-service, and humans can work hand-in-hand. Join us to discuss and learn about this new era of effortless, personal omni-channel CX where old and new emerging channels come together and robots and humans work as one.

I highly recommend brands who truly understand the importance of customer experience to their business success and survival to join this group.  Execs In The Know is a well-respected organization that people turn to for advice and it’s unlike other similar events in the CX industry, due to the level of attendees and openness in communication. In attendance will be leading financial services firms, retailers, healthcare companies, hi-tech firms, hospitality companies, and utilities from across North America – both traditional leaders, but also some of the new disruptors changing business today. To learn more about joining visit https://execsintheknow.com/events/crs-chicago/ and follow @execsintheknow. And to learn more about Genesys, the industry’s #1 customer experience platform and recognized leader per Gartner and others, please visit http://www.genesys.com/about.  Or checkout some really awesome customer stories from CX leaders like Sabre.

Execs In The Know would like to thank Genesys who have been a long time supporter of the Customer Response Summit event, continue to be involved and valuable to our community of CX professionals, and truly care about seeing progression and enhancement in our industry. 

The post Customer Experience Leaders Share Innovative Ideas for the Next Era of CX: Customer Response Summit Chicago, September 19-21 appeared first on Execs In The Know.

For those who worry that technology is doing irreparable harm to our day-to-day communication, here’s some good news. The art of conversation is not lost, it’s just evolving. In the customer experience call center world, we’re on the front lines of business to consumer communication disrupters, starting with digital channels like a company website and chat, to SMS-text, social media, advancing natural language processing (NLP), artificial intelligence (AI) and cognitive learning, automation, and analytics. These tools bring tremendous opportunity to win and retain customers with better CX.

According to Gartner, 89% of companies are competing on CX, yet less than 10% of consumers think service from the call center is good. Today’s businesses need to improve service, be easier to do business with and open 24X7, and be consistent across multiple channels and digital devices with personalized interactions, empathy, and insight. Without this optimized service, brands risk becoming irrelevant to today’s customers, who show no loyalty. A Unified Customer Experience Strategy® brings a balance that leverages the latest digital innovation, while also cost-effectively improving service through conversations that make emotional connections with customers. This means understanding these three drivers: 

1) Customers’ expectations of service competence are higher every day, with world-class companies like Amazon and Apple setting an excellence standard that is leading with self-service and integrating human expertise when it adds value. Households have adopted digital and AI innovation as a way of life. Think “Hello Siri.” Starting your conversation with a bot is rapidly becoming the new norm. According to a recent Google study conducted by Northstar Research, more than half of U.S. teens and 41% of U.S. adults use voice search on a daily basis. A consistent customer experience that bridges channels is extremely important for Generation C—a demographic of connected customers  that represents today’s  buyer attitude and mindset. Bots, increasingly, provide a strong sense of reliability, consistency, and ease of use, which are critical to meet the demand for a unified customer experience strategy.

2) Conversations are driving commerce. “Conversational commerce” is a term coined by Uber’s Chris Messina in reference to the intersection of messaging apps and shopping. With customers interacting through messaging and chat apps, conversational interfaces have become mainstream, enabled increasingly by AI and bots. Today talking to a bot is more and more akin to connecting with a human. Bots employ NLP for more colloquial verbiage and appropriate tone, recognition and understanding, to increasingly replicate a human interaction. Culture and customization can be applied to mimic character and persona of human agents. And, with their ability to process language, chatbots are able to handle tedious tasks like data entry, scheduling, and other basic assistant-like tasks.Bots, however, are exception prone and can’t deliver on all fronts. For example, in Facebook’s recent launch of a bot API for its Messenger IM service only 30% of requests could be resolved entirely without a human stepping in, according to The Information, a Silicon Valley blog.  So the seamless integration of brains, or human assistance with bots, is critical to an optimized digital customer experience. 

3) Bots are assuming more menial service tasks, requiring service agents to evolve to more sophisticated tier 2 ambassador responsibilities. The ideal self-service approach has proven to be an intelligent integration of more empowered and empathetic human agents with the highly efficient bots. Whether front-end bot or bot-assisted agent, the key is to employ automation where it adds value through reduced customer effort (improving CSAT by guiding customers to the right answer fast), cost-containment, or revenue generation. Bot deployment frees up human labor for higher-minded, more emotional and complex decision making. According to a recent report by Horses for Sources, automation is making way for strong growth of highly and medium skilled personnel—with highly skilled positions in the service provider industry increasing by 56%, and medium-skilled by 8%. However, low-skilled, routine jobs drop 30% as many of these roles get phased out over the next 5 years:

Ultimately, today’s CX expectation is the right answer, fast: an authentic connection that’s also the right combination of automated self-service, driven by bot technology via the web and messaging, or via voice, integrated with assisted support from well-trained agents, or DigiAMBASSADORs. With a unified customer engagement strategy, service providers can customize targeted deployment of these solutions—seamlessly bridging any bot-brain gaps and driving real outcomes. The most intelligent business brands know that good customer experience today is as much about smart, personalized conversations as it’s ever been.

Interested in finding out more about this topic or HGS? HGS is one of the subject matter experts that will be sharing their insights and expertise at Customer Response Summit Chicago, September 19-21, 2017. CR Summit Chicago will feature keynotes from Amazon, Lyft, Square, and Microsoft. For more information about our leading event for CX professionals, visit our event website. 

The post Integrating Bots and Brains for Optimized CX appeared first on Execs In The Know.

To download the full CXMB Industry Insights: Retail report, click here.

The post CXMB Industry Insights: Retail – Select Findings [INFOGRAPHIC] appeared first on Execs In The Know.

CXMB Industry Insights: Retail is aimed at providing insights into consumer opinions and behaviors, specific to the retail industry. Topics in this report include comparisons between online and in-store shoppers in the areas of pre-purchase research, shopping, customer care, drivers of mobile device shoppers, and the multi-channel experience.

Findings reveal differences and similarities between online and in-store shoppers when it comes to the customer journey. Among the most popular methods of issue resolution — in-person, phone and email — online shoppers prefer to resolve issues via email, while in-store shoppers strongly prefer to resolve issues in person. However, both groups had low preference for self-serve solutions, including self-help and automated tools.

Additionally, responses between online and in-store shoppers are strikingly consistent when respondents describe what is most important to them when interacting with a retailer to resolve an issue. Customers want agents who provide clear communication, listen patiently, understand the issue, express empathy, and are empowered to break away from the script to get issues resolved.

Survey Insights:

– In the event of a customer care issue, 68 percent of online shoppers and 75 percent of in-store shoppers would rather interact with a human versus a self-help system to resolve the issue.

– Among consumers who frequently shop from their mobile device, 44 percent would choose email as their preferred communication method with a brand compared to just six percent who would choose a phone call as their preferred communication method.

– Thirty-five percent of survey respondents think retail companies do a better job of providing a positive customer experience compared to other industries.

“We know retail brands have a huge opportunity to differentiate themselves by providing an exceptional customer experience. We conducted this survey to show real customer needs and to provide actionable data that all retailers should consider to improve customer satisfaction and increase loyalty,” said Kathleen Jezierski, chief operating officer, COPC Inc.

CXMB Industry Insights: Retail is the second in a series of industry-specific reports and is an extension of the Customer Experience Management Benchmark (CXMB) Series, also published in partnership between COPC Inc. and Execs In The Know. The first industry-specific report examined travel and hospitality and is available here.

“CXMB Industry Insights allows us to dive deeper into various industries and provide relevant insights that our community members in each vertical are seeking,” said Chad McDaniel, president, Execs In The Know. “Our retail survey offers information about consumer perceptions, expectations and behaviors so that our community can have a better understanding of the customer landscape in online and brick-and-mortar retail.”

For more information about the findings of this retail research or the CXMB Industry Insights survey series, contact Judi Brenstein, vice president, COPC Inc., at jbrenstein@copc.com.

 About COPC Inc.

COPC Inc. is an innovative global leader that empowers organizations to manage complex customer journeys.  The company created the COPC Customer Experience (CX) Standard and provides consulting, training and certification for operations that support the customer experience. Founded in 1996, COPC Inc. began by helping call centers improve their performance.  Today, the company works with leading brands worldwide to optimize key customer touchpoints and deliver a seamless experience across channels. COPC Inc. is privately held with headquarters in Winter Park, FL, U.S. and has operations in Europe, Middle East, Africa, Asia Pacific, Latin America, India and Japan.

COPC will also be giving an educational pre-conference seminar at CRS Denver in September, 2019.

To learn more about COPC Inc., visit www.copc.com.

About Execs In The Know

For over 15 years, Execs In The Know has built a reputation of excellence in the Customer Management Industry and a worldwide community of over 50,000 Customer Experience Professionals. Execs In The Know connects people to engaging industry content, thought leadership, current trends, peer-to-peer collaboration, networking and industry employment opportunities. Examples of this can be seen at their Customer Response Summit events, roadshows, webinars, workshops, Blog Talk Radio segments, Industry Benchmarking Series, blogs, thought papers and social communities. For more information, visit www.execsintheknow.com.

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