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Take Your Customer Support from ‘Talking At’ to ‘Listening To’

By Björn Gülsdorff, Chief Business Development Officer

Once upon a time ‘market’ was a noun, denoting the place where people got together and negotiated public affairs. In some markets, like the Forum Romanum, history was made. Then, ‘market’ also became a verb. Now marketing basically means talking at people, often raising the level of volume, colours, and wordings whilst lowering niveau. 😊

Surely, to say such a thing is utterly unfair to many marketeers. Yet, when it comes to customer service, I uphold the claim that the communication is often rather unidirectional, and in the wrong direction on top of that. Countless the websites where FAQs are not “frequently asked questions” but rather “answers we’d like to give”. Or where obviously someone has created a user journey for me. Frankly, nobody needs to design that. I know pretty well where I want to go, thank you.

What I do want on my journey, is to have road bumps removed, gaps bridged, and connections optimised. If customer service was an airport, I don’t want the lounge refurbished; I want another fast lane and quick boarding.

I am aware that people are different and that the same person has different needs at different times. Therefore, there is not the one journey for all and clearing the path is not easy.

That’s where two-sided conversations, aka dialogues, kick in. Customer service is about listening as well as acknowledging that each experience will be unique. Virtual agents can play a role in that as they come with a free text input field. So even when customers are self-serving, they don’t need to guess the one correct search term or scroll through a list of FAQs someone else has selected.

When it comes to creating this dialogue with customers, there are good and not so good ways to start.Things like expectation management, consistency, focus, and coverage make a big difference. It also requires courage (customers will speak their mind!) and the will to act.

It may be an inconvenient truth, but customer service with a virtual agent (or any other tool for that matter) is not a one-off thing. Good customer service means listening to your customers and improving constantly, be it the NLP (natural language processing), answers in the virtual agent, your processes, your services, or your products. In customer service, the journey to design is your way to become a better and more successful company.

Whether you’re ready to add a virtual agent to your customer service plan for the first time or have realised that your current tool isn’t creating a helpful dialogue with customers, I recommend this whitepaper for tips from conversational AI experts.

Register Now: Expert Insights on Conversational AI and Customer Service

By Scott Tompkins, Vice President of Sales

Just like a puppy isn’t only for the pandemic, customer service insights aren’t only for Customer Service Week. This week of celebrating customer service professionals and successful customer service experiences should just be the beginning of a renewed focus on your own customer service and CX strategies.

To help you keep that Customer Service Week momentum going, destinationCRM is hosting a roundtable webinar next week: Conversational AI: The Future of Customer Service? I’m looking forward to hearing the panel of experts, including Creative Virtual’s Founder & CEO, Chris Ezekiel, discuss the current trends and future possibilities of conversational AI technology.

Drawing from his own experiences and those of Creative Virtual’s global team, Chris will share expert recommendations for how your organization can maximize the benefits of conversational AI technology. He will also be delving into ways you can use back-end integrations to take your digital self-service from basic FAQ tool to a personalized, conversational interaction.

Conversational AI solutions, like chatbots and virtual agents, can have a powerful impact on customer loyalty and retention. When designed, implemented, and maintained correctly, these solutions have been proven to reduce support costs, increase sales revenue, and even reduce employee turnover. The next generation of conversational AI advancements are poised to improve customer service even more.

Register now to join us on Wednesday, October 13, 2021 at 11:00 am PT/ 2:00 pm ET for the live webinar, Conversational AI: The Future of Customer Service? This destinationCRM roundtable will be recorded, so be sure to sign up even if you can’t join the live event.

Once you’ve registered, I recommend checking out (or re-reading!) all of the posts from the Creative Virtual team that make up this year’s Customer Service Week Blog Celebration. There are lots of great insights on conversational AI use cases, customer expectations, and customer service trends.

Dialogues are Between People

By Björn Gülsdorff, Chief Business Development Officer

Have you ever heard about the H-H-Interface, aka the H2I? Likely not, because I just made it up. But I did so with a reason and here’s why.

When it comes to transactional tools, there is a lot of talk about the Human Machine Interface (or HMI), the look and feel, and other technicalities. That is all fine and important of course, but customer communication, however, is about people talking to people. Even if this communication is automated and asynchronous, it is still Human to Human.

Customers use conversational AI on the web, in apps and other channels. They interact with virtual agents and chatbots in a technical sense, but they certainly do not converse with them. The replies they get are perceived as coming from a person or a group of people (usually called a company 😊).  Having this in mind makes an important shift of focus in the virtual agent design. The focus goes from designing transactions to creating the dialogues you’d like to have with your customers.

Just think about voice mail: When you are greeted nicely and the message makes you smile, will you think “What a friendly machine!”? Or will it be: “What a nice person!”? See? When creating a virtual agent, the same thinking applies.

You need to create a dialogue between yourself and your customers. You need to ask yourself, who are you talking to and what do you want to tell them.  As a result, it is about personal contact and the tools you use are not the deciding factor. Or let me phrase this differently: You need tools that do not get in the way between you and your customers. You need a platform rather than a readymade, which allows you to create conversations with your customers – or with your customer groups, for that matter.

As this year’s Customer Service Week celebrations come to an end, be sure to keep the H2I focus in your digital strategy. And if your conversational AI solution doesn’t provide you with the platform options to create the dialogue you want with customers, then it’s time to make a change.

AI Growth in the Insurance Industry

By Susan Ott, Senior Customer Success Manager

At the outset of the global pandemic in 2020, there was already a great emphasis on the consumer’s desire for artificial intelligence (AI) in day-to-day life.  As we find ourselves making our way, 18 months and counting, in this new normal it is a safe bet that the world of AI-powered self-service isn’t going anywhere.

One industry that has experienced an influx in the need for self-service is Insurance. With technology advancing every day, the need for instant service and issue resolution is becoming more and more expected. The preference of customers to be able to self-serve isn’t waning, but their patience with companies that don’t provide that option certainly is.

AI remains a major trend in the technology sector that will continue to alter how we work and live. Within the customer service space in particular, conversational AI is enabling companies to successfully meet the growing need for instant service.

These new technologies are being used in the multi-faceted Insurance field to automate Claim Processing, get Pricing/Quotes, and improve the overall Customer Service experience for Auto, Home and Life policyholders. Here are some examples:

  • Claim Processing: Companies spend a lot of money on Claims personnel, often times increasing rates to account for the large number of calls coming into their contact centers. Using AI, these companies can reduce their hiring budget by automating many of the routine questions that representatives field on any given day.
  • Pricing/Quotes: This is a huge area in which AI can be beneficial. Using AI, companies can be more competitive in their pricing and allow for personalization tailored to individual policyholders. Knowing some key criteria about a person, such as geographical location, marital status, and likelihood of filing a claim, helps to set premiums.
  • Customer Service: Companies need to look at AI in terms of it acting as a personal Concierge for users coming into the company’s website. It gets them where they need to be to best resolve their questions, allowing for a seamless and smooth experience, while decreasing phone or other live contacts via this digital channel.

Insurance companies should approach AI projects with the goal of creating better experiences for their policyholders, agents, and contact center teams. When used correctly, these technologies provide instant service that is personalized, convenient, and meets the expectations of today’s consumers. Automating processes and top customer service queries with AI also improves efficiency, increases productivity, and helps build customer trust and loyalty. All of this is more important than ever as we continue to make our way through this new normal.

Conversational AI and the Contact Centre: The perfect customer service pair

By Khushal Hirani, Customer Success Manager

You can’t celebrate Customer Service Week without talking about the contact centre. Onboarding agents in a contact centre can be very time consuming and expensive. From the recruitment process, to training, up until they are on the floor taking calls, it takes a very long time until new agents are self-sufficient.

The job of a fully trained contact centre agent can also be extremely stressful. They must remember how to use several tools and different areas to access certain knowledge. They often must memorise certain scripts and be able to explain detailed processes. This puts a lot of pressure on agents and can result in a poor customer experience, unnecessarily long call times, and low customer satisfaction scores.

For example, contact centre agents tend to keep notepads or workbooks with their own notes at their desks to ensure they remember the processes. This means communication of processes from one agent could be completely different when speaking to clients than from another agent.

Too often contact centre agents are also dealing with many tools and applications to do their job. This means that before they can even start working with customers, they face extensive training to learn them all. Then after completing their training, this makes it hard for contact centre agents to switch between screens while answering customer questions. This increases the time on the call for customers and creates a very disjointed experience.

Fortunately for contact centre agents and customers, conversational AI tools can help eliminate some of these issues and stresses. Here are some benefits of using conversational AI in your contact centre:

  • Training time is reduced – When contact centre agents are onboarded, the training time is reduced as the agents don’t need to learn complicated tools or multiple applications. This means less time to get agents to the floor and more of a focus on training agents on the human side of providing empathetic customer service.
  • Single source of truth – Knowledge and processes are in a single location where everything is accessible to all contact centre agents, giving everyone the same level of knowledge regardless of their experience level. Conversational AI tools like virtual agents can also be set up to provide support through public-facing solutions from the same knowledgebase with answers customised for both agents and self-serving customers.
  • New knowledge identified with agent feedback – Every contact centre agent can identify any knowledge gaps as well as contribute towards creating new processes or updating content with a built-in feedback loop. This keeps the customer experience accurate and consistent by ensuring the most up-to-date information is going out to all the end-users through multiple channels.
  • Integration with back-end systems – Integrations into different applications make it easier for the agents to use conversational AI because they have one tool that lets them find what they need. A customised agent dashboard can bring everything together in one place, including real-time alerts and step-by-step process flows.
  • Reports and metrics tracking – Reporting that is accurate and easy to understand gives important insights into what conversations the agents are having with customers and what knowledge gaps have been identified. This helps you track important metrics and see opportunities to further improve your support experience.

Contact centres are a big investment for companies and important for customer support. When used in the contact centre, conversational AI gives agents easy access to all the knowledge and processes they need to provide a better customer service experience. It makes their jobs easier and lets them focus on the human side of serving customers. Conversational AI and contact centre agents become the perfect customer service pair.

Teamwork Makes the Conversational AI Dream Work

By Mandy Reed, Global Head of Marketing

At Creative Virtual, we are dedicated to working as a team to help our customers and partners reach their customer experience and employee support goals. It’s at the heart of everything we do, from the initial development stages of our conversational AI technology to the ongoing evolution of  V-Person™ deployments that have been live for a decade or more. The fact that our very first enterprise-level customer has worked with us continuously since 2004 tells us that we are doing something right!

While we don’t do what we do for external awards and recognitions, it’s always a nice boost for morale to have experts in the industry acknowledge Creative Virtual’s expertise and success. We are proud that our dedication and teamwork have led us to be named a Conversational AI Leader by the analysts at ISG in their ISG Provider Lens™ Intelligent Automation – Solutions & Services report!

Here’s Mrinal Rai, Lead Analyst at ISG Research, explaining why Creative Virtual has been identified as a Leader in Conversational AI:

 

 

In their Quadrant Report, the ISG analysts evaluated 19 conversational AI vendors against a robust set of market-driven criteria. They found Creative Virtual to be “an established vendor with a focus on developing omnichannel virtual agent solutions” and a clear Leader in the space.

Conversational AI

If you want to learn more, you can:

  • Review a copy of the ISG Provider Lens™ Intelligent Automation – Solutions & Services report featuring the Conversational AI Quadrant: Download here >>
  • Explore a discussion on conversational AI featuring expert insights from Mrinal Rai, Lead Analyst at ISG, Jan Erik Aase, Partner & Global Head – ISG Provider Lens, and Chris Ezekiel, Founder & CEO of Creative Virtual: Watch on YouTube >>
  • Arrange a personalised demo with the Creative Virtual team to see our conversational AI technology in action: Request demo here >>

We know that to continue to be a Conversational AI Leader, we must keep working as a team to ensure our solutions are both innovative and delivering real business benefits. The entire company is currently collaborating on our next product release, Gluon, set to be introduced to the market next year. This release includes updates to our chatbot, virtual agent, and live chat technologies as well as a re-architecture of our V-Portal™ orchestration platform. Be sure to check out our Gluon sneak peek.

Our thanks to the team at ISG for naming us a Conversational AI Leader and sending us this great video. And to echo Mrinal’s well wishes: Congratulations Team Creative Virtual!

Conversational AI Doesn’t Have to Be a Risky Investment: Step 3

By Mandy Reed, Global Head of Marketing

Conversational AI is a technology that is regularly described as ‘innovative’ and ‘cutting-edge’. Simply having ‘AI’ in the name makes some people think of it as being futuristic or only for companies with the resources to implement it for the cool factor. It can be easy for business leaders to associate conversational AI with being a high-risk investment.

For many companies, proven and reliable results are more important than being innovative and flashy. Projects that get budget approval and management backing are ones that are considered safe bets because they utilise established technologies that have documented business benefits. They don’t have the financial flexibility or company culture to take a high level of risk, whether that risk is real or inferred.

The good news is that conversational AI projects don’t have to be risky. In this blog series, I’m sharing three steps for achieving conversational AI success while minimising the risk. You shouldn’t let the common misconception that conversational AI has to be a high-risk investment keep you from implementing it to improve your customer experience and employee engagement.

The previous posts in this series covered the first two steps to minimising your risk:

Once you’ve read through those steps, you’ll be ready for number three:

Step 3: Start with a pilot and expand with a staged approach.

Before you go all in with a conversational AI project, look to do a pilot or proof-of-concept (POC) with the vendor. This gives your organisation the opportunity to test out the technology on a limited basis to make sure it is a good fit for you and your digital strategy. The financial risk associated with this pilot should be shared by the vendor.

Typical pilots run for 30-60 days which will provide sufficient time for you to see results, evaluate initial performance, and make decisions about taking the next step in your conversational AI plan. A successful pilot strengthens your business case and enables you to finetune your strategy based on real feedback and user interactions. Also be sure to use the pilot phase as an opportunity to test integration points to ensure your solution will work end-to-end as you expand the deployment.

Starting with a pilot, and sharing that financial risk with the vendor, makes moving forward with a larger conversational AI investment less of a gamble for your company. When you do convert from the pilot to a full system, you still don’t need to jump directly into a massive project. Taking a staged approach to development and rollout is not only less risky, but also often the best way to achieve success.

Typically, the best method for deploying a chatbot or virtual agent is to use an agile approach, starting small and scaling the solution over time. This could mean focusing on a particular area of content, a specific use case, or a key contact channel that will have the greatest impact as a starting point. Your vendor will collaborate with you to design a staged rollout based on your biggest pain points. This reduces risk because you are streamlining your efforts in a way that supports your identified KPIs. You can also take advantage of new insights as you go to improve the tool and tweak your plan to maximise on successes and avoid potential problems.

It’s a common misconception that conversational AI is always a high-risk investment for organisations, but one that shouldn’t keep you from implementing your own chatbot or virtual agent. Being a risk-adverse business is not a barrier to deploying a successful and valuable conversational AI project. These three steps can help you join other savvy companies in taking advantage of the proven, reliable benefits of this technology while minimising your risk.

To make it easier for you and your organisation to apply these three steps to your conversational AI approach, I’ve compiled them all into a single document which can be read, shared, and downloaded here: Conversational AI Doesn’t Have to be a Risky Investment.

Conversational AI Doesn’t Have to Be a Risky Investment: Step 2

By Mandy Reed, Global Head of Marketing

Innovative, cutting-edge, ground-breaking – these are all words used regularly to describe conversational AI technologies. Being the organisation that deploys an innovative technology typically requires being comfortable with a high level of risk. However, most companies don’t have the financial flexibility or company culture to take that degree of risk, whether real or inferred.

Deploying conversational AI solutions like chatbots and virtual agents can be risky but doesn’t have to be. You don’t need to be an early adopter of innovations to benefit from the technology. These solutions have been used by businesses for over two decades as part of their customer engagement and employee experience strategies, and you can take advantage of those learnings to deploy reliable, successful projects.

In this three-part blog series, I’m sharing three steps for achieving conversational AI success while minimising the risk for your organisation. Last time, we delved into Step 1: Be selective when deciding on a vendor and technology. If you missed that post, I recommend you read it first before moving on to the second step:

Step 2: Build a business case with realistic goals.

Embarking on any business project without identifying the goal is always a risk, so it is essential that you have a realistic business case and clear objectives for your conversational AI project. An experienced vendor will be able to assist you with this process by performing a textual analysis of your existing data, such as live chat or contact centre transcripts, to identify what queries can and should be automated with conversational AI.

Starting with this analysis immediately reduces risk because your business case is being built around your own data. It’s combining the vendor’s expertise directly with the information that is unique to your customers, employees, and company. Instead of guessing your users’ self-service needs or taking a generic approach, your business case is customised to you and your pain points from the start.

Follow that initial analysis with a consultation workshop to review the results and collaborate with the vendor to identify your key performance indicators (KPIs) and set realistic goals. These business objectives will directly inform how your chatbot or virtual agent is built and implemented. Having clear goals and deciding how you will track progress and measure outcomes minimises the danger of investing in a project that won’t really meet your needs.

The key in this step is to build your conversational AI business case around realistic and obtainable goals. Being practical about what you are automating and setting sensible targets for your solution creates a solid foundation for your project. It keeps your investment focused on reliable, reproducible outcomes and business benefits.

In the third and final instalment of this series, we will talk about starting your conversational AI project with a pilot and the best approach to minimise risk while rolling out a full deployment. A great resource for better understanding the financial investment needed for a successful virtual agent or chatbot is the Guide to Enterprise Conversational AI Pricing: Calculating the Cost of a Successful Chatbot or Virtual Agent. Even if your company isn’t at the enterprise-level, this guide provides valuable insights into budgeting and calculating ROI that’s useful for all organisations.

Conversational AI Doesn’t Have to Be a Risky Investment: Step 1

By Mandy Reed, Global Head of Marketing

In the technology industry there tends to be a focus on being innovative, cutting-edge, and ground-breaking. Industry awards, conferences, and articles frequently showcase and reward vendors for technological innovations. Analysts and expert speakers regularly highlight case studies of companies that are early adopters, deploying technologies in inventive ways, or finding success by taking a chance on something new and unproven.

Innovation is essential to the advancement of technology but doesn’t automatically equal practical business benefits. Having companies try out new technological developments and deploy existing solutions in creative and unfamiliar ways is important for finding practical applications for new innovations. However, being the organisation that deploys an innovative technology typically requires being comfortable with a high level of risk.

Most companies don’t have the financial flexibility or company culture to take that degree of risk, whether real or inferred. For them, proven and reliable results are more important than being innovative and flashy. Projects that get budget approval and management backing are ones that are considered safe bets because they utilise established technologies that have documented business benefits.

Conversational AI is one technology that is regularly described with words like ‘innovative’ and ‘cutting-edge’. Simply having ‘AI’ in the name makes some people think of it as being futuristic or only for companies with the resources to implement it for the cool factor. It can be easy for business leaders to associate conversational AI with being a high-risk investment.

Deploying conversational AI solutions like chatbots and virtual agents can be risky but doesn’t have to be. Your organisation doesn’t need to be an early adopter of new innovations to benefit from this technology. Chatbot and virtual agent technology has been used by businesses for over two decades as part of their customer experience and employee engagement strategies, and you can take advantage of those learnings to leverage conversational AI within your organisation.

Over the course of this three-part blog series, I’ll outline three steps for minimising risk and maximising benefits of conversational AI projects. Let’s get started with the first and most important step:

Step 1: Be selective when deciding on a vendor and technology.

The conversational AI market is oversaturated with new, inexperienced start-ups and technologies that haven’t been well-tested in the real world. The first step to reducing your risk is to choose a vendor that is established in the industry and provides a technology that has proven results. Both criteria are important when it comes to risk level.

Vendor experience is critically important because the more knowledge your selected provider brings to your project, the more confident you can be in their advice and guidance. You want a vendor that will become an extension of your own team and knows what they are doing because they’ve done it all before. Working with experts means you benefit from their many years of experience, thereby making your investment less risky even if your company is new to this type of technology.

When evaluating a vendor’s experience, ask specifically about how many years the company has provided conversational AI technologies, as these solutions may be an offering added recently even though the company has been in business for decades. Also ask about the experience of their individual team members and staff turnover rates. If they have high staff turnover and are constantly training replacements for departing employees, then you will likely miss out on the risk-reducing personal expertise you want the vendor to bring to the collaboration.

Just as critical as the vendor experience is having proof of their technology delivering positive results in real world applications. Don’t assume that just because a provider isn’t a brand-new start-up that they have a well-performing conversational AI technology. If the company has been in business for four or five years and only has one customer, you should question why more companies aren’t using their technology and if working with them is a risky option.

To reduce risk, ask about how the vendor has deployed their technology within your industry and what documented business benefits those solutions are providing. Saying they have the ability to deploy important features and functionality is great, but you want to see the technology in action in live installs. Also ask them about the length of their customer relationships as long-term engagements indicate that existing customers are happy with the technology, their results, and the collaboration. The vendor should be able to provide you with customer references so you can get first-hand feedback on their conversational AI projects.

Keep in mind that even if your company is minimising risk by selecting a proven solution with reliable results, you still want to partner with a vendor that is consistently innovating. You may not be the organisation trying out those new innovations first, but you don’t want to invest in a solution that’s not going to improve as those advancements become well-tested and are shown to deliver business benefits.

In my next post, we’ll explore building a realistic business case as part of Step 2 for reducing risk. In the meantime, check out the Guide to Selecting a Virtual Agent or Chatbot Vendor: Forget the Technology & Focus on Experience. It explains in more detail the most important questions to ask a vendor about their experience during your procurement process.

The Success of a Chatbot is in the Details

By Mandy Reed, Global Head of Marketing

Last year many of us were spending much more time at home than usual as we did our part to slow the spread of COVID-19 in our communities. This created a surge of another kind, though: a wave of do-it-yourself project attempts. If you’re at home anyway, why not try to tackle that project yourself?

As many DIYers quickly discovered, the devil is in the details. No matter how easy something looks in the YouTube video or how complete the step-by-step instructions may appear, some projects are better left to the professionals. Sometimes recognising the small details needed to really succeed requires an expertise that comes only from experience.

This is most certainly true when it comes to creating chatbots for customer self-service, and too often organisations fall into the DIY trap. Some companies delegate their project solely to an inexperienced internal team because they underestimate the amount of expertise needed to build and deploy a working chatbot. Some companies treat their chatbot as an unimportant DIY side project not worthy of dedicated resources and investment because they fail to recognise the importance of conversational AI in modern customer experience (CX) strategies. Whatever the reason for a DIY approach, these organisations soon discover that they should have collaborated with a chatbot professional.

A good example of an important detail for chatbot success that is often overlooked comes from Maria Ward in a conversational AI vendor selection guide. Maria, an industry expert with over 15 years of experience working with chatbots and virtual agents, shares this insider tip:

“Avoid using ‘Yes’ and ‘No’ at the beginning of virtual agent answers as it may not fit with the many ways a question may be asked. Adding the subject within an answer also gives the user confidence that they have received the correct answer. For example, when answering ‘Can I have 3 slices of cake?’ instead of ‘Yes, you can.’, use ‘You can eat as much cake as you like!’”

 Besides making me hungry for cake, this quote also illustrates an important point about the importance of the details in chatbot creation. When you read Maria’s tip, you might think that structuring the chatbot’s answers in that way should be common sense. It sounds so logical. But, if you’re not experienced with creating chatbot content, is that something you would automatically know? Probably not.

Really understanding how to structure answer content to work with the many ways users may ask the same question is just one skill that comes with experience. It’s a detail that’s crucial to delivering a quality self-service experience and building user confidence in your conversational AI tool. It’s also a detail that could very easily be overlooked by an inexperienced DIY team.

When it comes to creating a successful chatbot and delivering a positive customer service experience with conversational AI, the devil really is in the details. Unless you have a highly experience internal team, taking a DIY approach is not worth the risk. CX is a critical competitive differentiator for organisations, and a poor performing self-service tool will quickly erode customer loyalty and your brand reputation.