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 organization 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 utilize 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 organization 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 organization.

Over the course of this three-part blog series, I’ll outline three steps for minimizing risk and maximizing 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 minimizing 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 organization 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.

It’s Time to Pull Back the Curtain on Enterprise Conversational AI Pricing

By Chris Ezekiel, Founder & CEO

Enterprise software pricing is often shrouded in mystery and the subject of intense negotiations between the supplier and customer. For applications where the market is immature then this is necessary as it takes some time to equate the cost with the business value. Whilst chatbots and virtual agents have been around for a long time, it’s relatively recently that they’ve become ubiquitous within the enterprise. I’m very pleased to report that Creative Virtual is stepping forward to lead the way in removing this shroud of mystery around conversational AI pricing.

Long-term relationships based on trust and transparency are attributes that underpin the culture within Creative Virtual, and we’re proud to launch the ‘Guide to Enterprise Conversational AI Pricing: Calculating the Cost of a Successful Chatbot or Virtual Agent’ whitepaper

This comes at a particularly important time as the conversational AI market is oversaturated with solutions that do not deliver the level of sophistication, flexibility, and customisation needed for a well-performing enterprise solution. These tools come with a lower price tag but end up negatively impacting the organisation’s bottom line by harming the customer experience and eroding customer loyalty.

This expert guide pulls back the curtain on enterprise-level pricing to empower organisations with the knowledge they need to properly budget and evaluate costs of conversational AI solutions.

We have drawn on our many enterprise-level customers and partners, together with a world leading amount of experience within the industry, so that organisations can have confidence not only in the pricing but also the advice on the effort and expertise required to maintain a successful solution. And whilst the technology platform is clearly a key part, the experience and expertise are often undervalued. That was the motivation for our previous whitepaper, ‘Guide to Selecting a Virtual Agent or Chatbot Vendor: Forget the Technology & Focus on Experience’.

conversational ai pricingNow, your organisation has two important complementary whitepapers that draw on Creative Virtual’s nearly two decades of delivering successful solutions in many sectors to help you develop a conversational AI roadmap designed to give your company a customer experience competitive advantage.

Download our new guide to enterprise conversational AI pricing for insider tips on budgeting for your solution, typical pricing models, and average costs for pilots and full systems.

When you’re ready to learn more and start building your own business case for a conversational AI solution, our expert team will be here to arrange a personalised demo and discuss your consultation workshop.

Will Old Internal Systems Destroy your Conversational AI Dream?

By Mandy Reed, Global Head of Marketing

Microsoft announced this week that they will stop supporting Windows 10 in 2025, with no new updates or security fixes being released after 14 October. This news comes as the company plans to reveal a new Windows operating system later this month. Screenshots of the new Windows 11 have been leaked online ahead of that virtual event – you can check them out here.

Whether you’re a Windows user or not, this type of announcement can highlight the need for wider discussions about the technology and systems being used internally at your organisation. Are you one of the many companies that relies on old or out-dated solutions? These legacy systems can have a knock-on effect, sometimes creating issues when the restrictions they create aren’t acknowledged at the start of a digital project or even keeping organisations from embarking on new projects at all.

For example, this can be the case when deploying an internal conversational AI solution for employee support. As virtual agent and chatbot expert, Peter Studd explains in a conversational AI guide:

“It’s very important to be aware of your users’ technology when you’re implementing a virtual agent to ensure it will be compatible. For example, it’s not uncommon for large companies to have very old systems and browsers that are still being used companywide. This can cause issues if not taken into consideration when developing an internal virtual agent.”

Constraints created by old systems and browsers don’t necessarily mean you need to abandon your plans for an internal virtual agent. However, they should be identified and discussed at the beginning of your project to avoid any unwanted surprises. If not, you could find that you’ve invested time and money into a solution that can’t be properly integrated with an important legacy system or isn’t user friendly for employees using older browsers.

This is just one of the downsides of taking a DIY approach to building and deploying a chatbot or virtual agent. If you don’t have people with the right experience on this team, it will be easy to miss or overlook older systems that could create project roadblocks. You end up with a case of ‘we didn’t know what we didn’t know’ and a tool that doesn’t meet expectations.

An experienced conversational AI provider will know the right questions to ask to help you pinpoint any potential compatibility issues upfront. They’ll provide guidance on any changes or accommodations you may need to make to your plan. They’ll also be able to offer suggestions for ways to work with potential constraints based on a deep knowledge of their technology and prior experience with similar challenges.

In an ideal world, all of the systems and technologies being used by your organisation would be up-to-date and easy to incorporate into new conversational AI projects. Since that’s not likely to become a reality any day soon, the best course of action is to work with a provider that can not only help you identify potential challenges but also provide the guidance on how to overcome them. Old internal systems don’t need to destroy your conversational AI dream.

A Seamless Support Experience is Music to Your Customers’ Ears

By Mandy Reed, Global Head of Marketing

Every month Creative Virtual’s Founder & CEO writes his Virtual Viewpoint column for Wharf Life, a local newspaper available in the area around the company’s headquarters in London. You can also read the paper online, getting an insider’s look at what’s going on in the area as well as Chris’ perspective on a variety of topics from technology developments to stress management to space exploration.

In his latest Virtual Viewpoint column, Chris shares his recent experience attending a string quartet recital. He marvels at how in sync the musicians were, each bringing their own style and sound together for a cohesive performance. He compares this to running a successful company. Each member of the team contributes their unique skills and style but must work together towards a common goal.

The same principles are true for delivering a positive customer service experience. Creating your overall strategy is similar to writing a musical score – you have to pay attention not only to the performance of each individual component but also how they interact with each other over the course of the journey. You need to ensure each element is utilised to emphasise its strengths but do so in a way that creates a joined-up, seamless experience.

I’m sure I’m not alone in saying that a number of my own personal customer service experiences have revealed a strategy that is out-of-sync. Way too often a company’s digital experience appears to come from a completely different strategy than other parts of the experience. While many customers were willing to cut businesses a little slack as they dealt with sudden pandemic-related changes, that’s no longer a valid excuse for the disjointed support experience so many companies are still delivering.

Recently I’ve come across some articles claiming customers, who are increasingly turning to digital channels, hate using chatbots and just want to talk to a human. However, when you delve into the real reasons behind these claims, you realise that it’s not the automated self-service tool that customers hate but rather the poor experience that some of them are delivering. If the chatbot can understand their questions, provide accurate and relevant information, and give the option to escalate to a human if needed, then customers have no issue with using a chatbot.

This highlights a failure in both the development of these chatbot solutions and their implementation as part of a synchronised support strategy. A quality chatbot must be backed by conversational AI technology that combines machine learning with a human-in-the-loop. It must be integrated with human-assisted support channels, such as live chat, for a seamless handover. It must be approached as one piece of a comprehensive customer service strategy and not as a stand-alone tool or side project. All of these elements are essential for your solution to be effective, but companies often struggle because they don’t have enough knowledge in this field.

Rachel F Freeman, a conversational AI expert, started working with chatbots and virtual agents in 2000. She has experienced first-hand the evolution of the technology, and today collaborates closely with organisations on the development and implementation of their solutions. She shared this important piece of advice in a chatbot vendor selection guide:

“You should feel comfortable saying to your vendor, “we don’t know what we don’t know and are looking to you as the experts”. This applies to everything from possible use cases to suggestions for conversational flows to UI design tips. If you don’t have confidence they will guide you in the right direction, you’re working with the wrong team.”

This is sage advice for companies as they make conversational AI a part of their customer service strategy. If you don’t want your customers to hate your chatbot, then give them a chatbot that delivers the experience they want. That requires working with knowledgeable experts to ensure your self-service tool is properly developed and integrated with your overarching support strategy, goals, and customer needs.

While engaging with a company for customer support will likely never be as enjoyable as listening to a professional string quartet recital, the experience should be just as seamless and in sync. This is certainly not an easy feat, but is one made easier when you work with the right experts. And when you are able to deliver a seamless, omnichannel support experience, it will be music to your customers’ ears.

Content Repositories and Party Menus Mean Nothing if You Aren’t Serving Your Guests at the Right Time

By Mandy Reed, Global Head of Marketing

Anyone who has ever planned a wedding, a surprise birthday party, or a family reunion knows how difficult it can be to get everyone and everything involved coordinated. All the pieces are interconnected, and good communication is essential to putting your plan into action. Often, even seemingly small details can be key in making sure all the moving parts are in sync.

The same is true for customer service strategies. Those that achieve real success are part of a bigger customer experience (CX) approach that is designed to create an integrated, coordinated strategy. Every piece is important and must be linked together to create a cohesive, seamless experience.

Within many companies, the digital customer service experience has evolved slowly and separately from other pieces of the support puzzle, such as the contact centre. For many years, when having a static set of FAQs on a website was enough for online self-service, organisations could get away with that siloed approach. Today that’s not the case. Customers expect a connected and more sophisticated digital service experience.

It’s not unusual for companies, especially large enterprises, to struggle with delivering an integrated customer support experience. Often, they have many of the pieces they need but aren’t sure how to link those pieces – or silos – together.

A good example is an organisation that has built up a robust content repository to house all of their customer help information. This was an important step in their journey to create a more consistent experience because it established a single place for them to manage content. They even enabled visitors to their website to leverage this repository by adding a simple search tool on the help page.

Now the company acknowledges that forcing users to scroll through a list of search results and read through long information articles is not delivering the online self-service experience they want to give existing and prospective customers. It’s the same as selecting a caterer and deciding on a menu for your party, but not making arrangements for the food to be delivered to the right venue at the right time. Despite all the effort you put into the food, you end up with a poor experience – and hungry guests! – because you haven’t put together the pieces of the puzzle behind the scenes.

Rob Foster, Knowledgebase Engineer and a conversational AI expert, shares a way to deliver a better self-service experience with a virtual agent that utilises an existing repository of help content. He explains:

“If you already have an existing content repository in use, consider integrating with it rather than spending time transferring all the data to a separate knowledgebase. With this option, your virtual agent recognises the user intent and makes an API call to retrieve the relevant information directly from the repository. This simplifies content management for you because you aren’t juggling multiple systems. It helps ensure accuracy because when content is updated in the repository, the changes are instantly reflected in the virtual agent. The integration also removes the danger of having conflicting information between the virtual agent and other online help pages since everything is managed in a single place.”

In 2017, a large Telecommunications Company took their first steps to do just this. They had already invested in an Oracle Knowledgebase that housed about 3,000 information articles. They wanted to provide a better user experience for their online help by adding a virtual agent to their website but did not want to move or replicate their help content. Their solution was to set a challenge as part of their conversational AI vendor selection process: 24 hours to build a working integration with their existing content repository.

You can find more details about that 24-hackathon and how their conversational AI solution currently works in the full Customer Success Story. Their approach is saving them an estimated £3 million per year from reductions in support calls and delivering better insights into their customer needs. It is also helping them make the most of their CX investments by linking up the pieces of their customer service strategy for a consistent, seamless experience.

You wouldn’t let your party guests go hungry, so why would you let your website visitors struggle to find information you could easily serve to them with the right tools?

Stop Trying to Improve Efficiency at the Expense of CX

By Mandy Reed, Global Head of Marketing

Earlier this year my niece starting reading Laura Ingalls Wilder’s Little House on the Prairie book series, and I’ve been rereading them along with her. It’s been fun having discussions with her about the books and hearing what part of the stories stuck out for her as most interesting or surprising about Laura’s pioneer life. It’s also made me grateful to have modern conveniences like running water and refrigeration!

Over the course of history, humans have always looked for ways to improve efficiency and productivity. Think about all the inventions you studied in school, like the printing press and cotton gin, that initiated key moments of change for industry and society. Innovation drives progress, but that progress doesn’t innately mean a better experience or quality of life for everyone.

Advances in artificial intelligence (AI) and machine learning have meant more potential use cases for automation technologies. Businesses see this as an opportunity to improve efficiency and productivity – and it is. However, being too focused just on those goals often means they overlook the importance of the experience.

Forrester analyst, William McKeon-White writes about this as part of his research on help desk chatbots. He points out that prioritizing efficiency over experience leads to the critical element of user success being overlooked. If users don’t have a good experience with the chatbot, they won’t keep using it. And if users aren’t coming back to the tool, there’s no way for the organization to achieve positive longer-term outcomes.

It’s important to understand this as you build your business case for a conversational AI tool. As chatbot expert Rachael Needham explains in a vendor selection guide:

“Having a clear business objective will dictate much of what and how the chatbot is implemented. For example, is the objective to reduce phone calls or live chats – and how will that be tracked? Is it to improve customer satisfaction – and how will that be measured? Another key question to ask when thinking of customer experience is: are we really meeting the needs of our customers or are we just trying to make a score look better?”

Improving productivity and efficiency are worthy and important goals but shouldn’t be attempted at the expense of the user experience. Your chatbot or virtual agent should be designed to create a better experience by providing quick, easy support. Reducing phone calls or live chat sessions because you’re giving customers a better way to get help, without having to take the time and effort to engage with a contact center agent, is an efficiency improvement that’s positive for your business and your customer experience (CX).

In a recent discussion with ISG, Creative Virtual Founder & CEO, Chris Ezekiel, pointed out that he has seen a shift in the focus of organizations when implementing conversational AI. Five years ago, the business cases for these solutions were heavily centered around contact deflection. However, as businesses come to recognize the competitive advantage of improving CX, that focus moves to creating better experiences as the key priority.

This doesn’t mean that organizations shouldn’t have the goal of improving efficiency and productivity with conversational AI tools. Instead, they should identify those objectives as part of their strategy to improve the overall experience. Often, you’ll find they go hand-in-hand. Efficiency improvements can be a crucial means by which the experience is made better. Expert conversational AI professionals understand the best ways to balance these needs and set goals that go beyond just making a score look better to achieving real success.

For more tips on creating a conversational AI strategy and building a business case, check out these resources:

Successful Conversational AI: Blending Machine Learning & Human Intelligence, Part 3

By Chris Ezekiel, Founder & CEO

In February ISG, a leading global technology research and advisory firm, published their ‘ISG Provider Lens™ Intelligent Automation – Solutions & Services’ report. Mrinal Rai, Principal Analyst at ISG, and his team evaluated 19 conversational AI vendors in the report, identifying Creative Virtual as a Leader in the highly competitive quadrant.

I joined Mrinal and Jan Erik Aase, Partner and Global Head – ISG Provider Lens, recently on a Zoom session for a discussion about conversational AI. Mrinal kicked things off by diving into the conversational AI quadrant and his research. He outlined the key factors that led to Creative Virtual emerging as a clear Leader in his evaluation.

Jan Erik and I then discussed a number of conversational AI questions that ISG see coming up with their advisors as well as their clients. In my previous posts, I’ve shared the first two parts of that conversation during which we covered current trends and developments, the changing roles of contact centre agents, barriers to achieving success, and the impact of the pandemic. You can watch Part 1 here and watch Part 2 here.

In the third, and final part of our conversation, we delved into the following question: When setting project goals, what KPIs should organisations identify and what results should they expect?

This is a really important question for organisations as they build their business case for a conversational AI solution. About five years ago, there was a big focus on contact deflection when implementing these tools. While this is still important, we find it to be less important as the focus has shifted more to improving the customer experience (CX). Organisations recognise CX as an important differentiator today in competitive marketplaces.

This same sort of thinking also applies to internal solutions, whether that be a solution deployed within the contact centre or one designed for employee support in areas such as service desk, IT support, HR support, and employee onboarding. Supporting employees is more important than ever and, with the right tools in place, presents an opportunity to improve productivity, efficiency, and job satisfaction.

Check out Part 3 of our ‘Successful Conversational AI: Blending Machine Learning & Human Intelligence’ discussion for more on KPIs and results:

 

 

A big thank you to Mrinal and Jan Erik for taking the time for this discussion, as well as to Katie Dickens and Thomas Victor at ISG for working behind the scenes on arranging and producing the recordings of our session!

If you haven’t done so yet, be sure to download a copy of the ISG Provider Lens™ – Conversational AI Quadrant Report.

If you’d like to learn more about Creative Virtual’s expert consultation and see our conversational AI technology in action, sign up here for a personalised demo session with a member of our global team.

Successful Conversational AI: Blending Machine Learning & Human Intelligence, Part 2

By Chris Ezekiel, Founder & CEO

In February ISG, a leading global technology research and advisory firm, published their ‘ISG Provider Lens™ Intelligent Automation – Solutions & Services’ report. The report evaluates 19 conversational AI vendors against a set of market-driven criteria and places Creative Virtual firmly in the Leader category within the quadrant.

Recently I joined Mrinal Rai, Principal Analyst at ISG, and Jan Erik Aase, Partner and Global Head – ISG Provider Lens, for a discussion on conversational AI over Zoom. In my last post I shared Part 1 of our nearly half hour chat. During the first part of the discussion, Mrinal shared why ISG identified Creative Virtual as an industry leader in their report. Jan Erik and I also discussed current conversational AI trends as well as the evolving role of contact centre agents. You can watch Part 1 here.

In Part 2 of our discussion (scroll down to watch the video), Jan Erik and I address two more questions:

  • What are the biggest barriers organisations face when it comes to building, deploying, and maintaining successful projects?
  • What impact has the pandemic had on the implementation and usage of conversational AI tools?

One key barrier to success that we explore is not having a team with the right skills and experience. Often organisations try to tackle conversational AI projects internally with a lack of knowledge and a toolset that doesn’t enable them to scale the solution to different channels, additional departments, etc. or support enough users simultaneously as the project expands. This sets the whole project up for failure. When it comes to conversational AI, knowing what doesn’t work is just as important as knowing what does.

Jan Erik and I also touch on issues some projects face when integration points and APIs aren’t readily available or accessible. Creating a personalised, omnichannel support experience really needs the conversational AI tool to be properly integrated with other systems. The contact centre not being a part of the organisation’s digital strategy is another common barrier we encounter. This is starting to change, but until company structures are more joined up in this regard, we’ll continue to see this as a widespread challenge.

The need to have the contact centre as part of the digital strategy was highlighted over the past year by the pandemic. We saw record traffic to our virtual agents and chatbots in 2020 as customers turned to online self-service for quick answers to their questions. For many of the organisations we work with, having a well-established conversational AI solution was a lifesaver as their contact centres dealt with an overwhelming volume of calls at the same time as new public health measures designed to keep agents safe.

Having a human-in-the-loop combined with machine learning gave our customers the ability to change responses within their virtual agent quickly, safely, and securely so they could deliver reliable, up-to-date information. In fact, one of our customers found that updating their virtual agent was quicker and easier than updating content on their website. Their contact centre recognised that the virtual agent was helping to reduce call volumes and proactively provided feedback and new content to add based on incoming calls from customers.

Check out Part 2 of our ‘Successful Conversational AI: Blending Machine Learning & Human Intelligence’ discussion:

 

My next post will take a look at Part 3 of our session where we discuss setting goals and identifying KPIs for conversational AI projects. In the meantime, be sure to download your copy of the ISG Provider Lens™ – Conversational AI Quadrant Report.

Successful Conversational AI: Blending Machine Learning & Human Intelligence, Part 1

By Chris Ezekiel, Founder & CEO

In February ISG, a leading global technology research and advisory firm, published their ‘ISG Provider Lens™ Intelligent Automation – Solutions & Services’ report. In the report Mrinal Rai, Principal Analyst at ISG, evaluated 19 conversational AI vendors based on a set of market-driven criteria. The result of that evaluation placed Creative Virtual as the clear Leader in conversational AI, surpassing all other vendors with our competitive strengths.

Recently Mrinal and I (virtually!) sat down with Jan Erik Aase, Partner and Global Head – ISG Provider Lens, for a discussion on conversational AI. Our conversation covered a lot of ground, including current industry trends, the impact of the pandemic, and setting conversational AI project goals. We talked about the findings of ISG’s research as well as current successful conversational AI implementations.

We have divided our nearly 30-minute-long discussion into three parts, the first of which I’m excited to share with you in this post (scroll to the bottom to watch Part 1).

Jan Erik and Mrinal start off the discussion by diving into the ISG Provider Lens™ Quadrant Report and why Creative Virtual has been identified as a Leader. Mrinal points out that when it comes to conversational AI, it’s not just about the solutions themselves but also how they blend with human intelligence. His evaluation focused on both V-Person™ (our virtual agent, chatbot, and live chat technology) and V-Portal™ (our innovative orchestration platform). The power of our technology to blend machine learning and human intelligence along with our strong presence in the market were the key factors that led to ISG positioning Creative Virtual as a Leader in the space.

I then joined the conversation to discuss with Jan Erik some questions that ISG see coming up with their advisors as well as their clients. In Part 1 of the discussion, we explore:

  • What current trends and developments in conversational AI are important when evaluating virtual agent and chatbot management platforms?
  • With conversational AI now being a key part of omnichannel support strategies, how are the roles and responsibilities of contact centre agents and customer service professionals evolving?

Check out Part 1 of our ‘Successful Conversational AI: Blending Machine Learning & Human Intelligence’ discussion:

 

 

My next post will take a look at Part 2 of our session where we explore some of the biggest barriers organisations face when it comes to building, deploying, and maintaining successful conversational AI projects. In the meantime, be sure to download your copy of the ISG Provider Lens™ – Conversational AI Quadrant Report.