Welcome to the Creative Virtual blog! Here we cover all of the hot customer experience topics in mobile, social, web, IVR and so much more. We also share company announcements, details about upcoming events and give you a peek into what happens behind the scenes.

Our regular contributors have over 90 years of combined experience specifically with customer engagement, natural language virtual assistants and knowledge management. When you add in the experience of our guest authors and the other Creative Virtual team members who occasionally contribute, there is no better place to get expert insight.

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​Generation AI: Growing up side-by-side with our silicon-based contemporaries

By Olaf Voß, Lead Application Designer

I was born in 1966. That means I’m usually sorted into Generation X. But these days, looking back at the past 57 years, I think we should really rename it to Generation AI. It has been my generation having witnessed AI from its infancy to the breakthroughs we’ve seen in the past few years. And with a bit of luck most of us will witness how AI will be reshaping our societies – for good or bad – in the next 20 years.

So let me give a recount of my encounters with AI throughout the decades.

There’s no way around it: I have to start with ELIZA, which Joseph Weizenbaum developed in the year I was born. I was too young to be aware of this when it was new of course, and even less aware that chatbots one day would play a major part in my professional life, but merely 16 years later I had access to Commodore computers at our computer club in secondary school. The ‘large’ one had 16 kb RAM AND a floppy drive! And we had an ELIZA clone running on them. But I admit I didn’t spend much time with her, I was far too busy with freeing princess Leia in an early text adventure or writing my own very simple games.

​I had my first chess computer at some time around 1980. It could analyze to a depth ​of 5-6 moves. I was an OK, but not great, player and I won against it when giving it up to 30 seconds thinking time and lost at above 2 minutes. In the early 90s I became a club player and soon after I didn’t have the slightest chance against the chess programs of that era even with 10 seconds thinking time. No need to be embarrassed about that I guess, since Gary Kasparov lost against Deep Blue in 1997.

Around 2005 I started playing Go. I was a convert from chess, and by that time I was used to having great chess programs available for training and analysis. Go has a much greater branching factor than chess and is much less suitable for static board state evaluation. With the available technologies of those days, programs could play Go at a mediocre level at best. Well, I still lost to them, but they were not strong enough to rely on their judgement. At that time most Go players, including myself, (apart from thinking that their game is much better than chess) thought it would take at least 50 years until computers could crack Go. It took about 10.

​How did they succeed​ so quickly? Deep neural nets. I read about those first as a university student in the 80s and was thrilled. I played with them a bit on the first computer I owned, an Atari 520st. I quickly thought about applying them to chess. My ideas were not very far from what is done in that field today, but of course I hadn’t heard about reinforcement learning at that time. I very much like to believe my ideas were extremely clever and would have worked. Alas, we’ll never find out, because it was clear very quickly that the hardware (especially mine!)  at that time was totally inadequate for tackling this problem.

​With what I’ve given away about myself so far nobody will be surprised to hear that I ended up becoming a software developer. Around the turn of the millennium I started to work on chatbots. We must have been one of the first few companies worldwide to tackle this commercially. ​At that time I was reluctant to say that I was working in AI. We were using pattern matching, and even a pretty simple form of that. Of course pattern matching IS an AI technique, but I was aware that with our focus on building chatbots that were useful for our customers in their restricted scope and on doing that efficiently, what we did would have bored any AI researcher. I wasn’t ashamed of what we were doing – quite the contrary: I was proud about what we could achieve with our pragmatism. I just wanted to avoid the pointless discussion if what we did was ‘real’ or ‘interesting’ AI.

​Fast forward another 15 years or so.​ Word embeddings came up and made it possible to tackle natural language problems with artificial neural nets. So I welcomed those back into my life. Only now the hardware was somewhat better plus I got paid for playing with them. Heavens!

Then comes 2020 and GPT-3. That was mind-blowing. I’ve heard people characterising deep neural nets as ‘glorified parameter fitting’. And sure, parameter fitting is all there is to it. But these parameters, each by itself just a dumb number, let something pretty astonishing emerge. I am not an expert on these topics and I am not even sure how much sense it makes to compare human and artificial intelligence. But sometimes I feel provocative and want to ask how we can be sure that our own intelligence is more than just ‘glorified synaptic strength fitting’. Once again I think the discussion about ‘real’ intelligence is far less important than considering what can be done. And, since there’s so much more that can be done today, how that will change our world.

Apart from being fascinating and super-relevant to the field I’m working in, GPT-3 is also a lot of fun of course. I remember a conversation I had with it in the early days, before OpenAI put the brakes on it to avoid harmful responses. (Which I applaud, in spite of it spoiling some fun.) I asked it  – actually before the start of the war in Ukraine – for a couple of suggestions about ‘how to achieve world peace’. One of the suggestions was: ‘Kill all humans.’ Well yes, job done … I’m still glad you are not yet in charge, you know!

I want to mention two more recent developments, even though they relate to me personally in a tangential way at best. Being a physicist by education I follow scientific developments closely, which brings me to AlphaFold 2. When I was 4 years old, the first successful DNA sequencing attempts were made. In 2020 AlphaFold 2 predicted and published 3D structures of thousands and thousands of proteins based on DNA sequences alone. Another loop closed during my lifetime. I make the prediction that in 2035 more than 50% of all newly approved drugs will have been developed using the results of AlphaFold or its successors at some stage in the process.

The second one is CICERO. As an avid board game player I reluctantly admit that I have never played Diplomacy, though I did play similar games like Risk or Civilisation. Diplomacy is a conflict simulation game in a WW1 scenario. It involves tactical moves on the board and lots of diplomacy around it – pacts – betrayals – revenge. CICERO can play this game on par with human experts. Apart from making clever moves on the board – easy-peasy these days for AI – it has also to negotiate with other players in natural language. So it needs to bring together strategic, natural language and social skills. Even though this is a model with a  niche application scope, I think it is at least as impressive as GPT-3, if not more so.

​​We are living in exciting times. And I think it’s important to understand that we are seeing the beginning of something, not the end. What will be possible in 20 years? Many things will happen, not all of them good. I’m not much of an expert in AI risks and besides, discussing them here in detail would go far beyond the scope of this blog post. Still I’m asking myself, how we as a society will cope with these – at the moment still largely unknown – changes.

My role at Creative Virtual involves looking at all the new technologies that pop up and evaluate if and how we can use them. So I have a bit of a front row seat in watching this unfold. I encourage you to check out our ChatGPT, GPT-3, and Your Conversational AI Solution blog post for a closer look at how we see these recent developments fitting with the work Creative Virtual does in the customer service and employee support space.

I think it is of the utmost importance that as many people as possible have a basic understanding about what’s going on. An ignorant society will not be able to react. I am trying to play my small part by sharing my knowledge with as many people as possible. Just recently, when an old friend of mine called, my wife burst out: ‘Great, now you can talk his ears off!’

ChatGPT, GPT-3, and Your Conversational AI Solution

By Chris Ezekiel, Founder & CEO

Since the official announcement in November 2022, there has been an enormous amount of buzz and excitement about OpenAI’s ChatGPT. Industry experts are publishing articles about it, social networks are filled with comments about it, and local, national, and global news organisations are reporting stories about it. From students using ChatGPT to complete assignments for class to me getting a little help from ChatGPT to write my latest ‘Virtual Viewpoint’ column, it certainly seems like everyone is testing it out.

As a specialist within the conversational AI space, Creative Virtual is excited about what ChatGPT and the technology behind it bring to our industry. We’ve been having lots of discussions with our customers and partners, as well as internally, about how this can deliver value to businesses using our V-Person™ solutions.

ChatGPT is an extremely powerful language model that is changing quickly and will continue to get more sophisticated. However, like any deep neural network, it is a black box which is hard – if not impossible – to control. Using it as a generative tool means you can’t steer in detail what it’s going to say.  You can’t deliver reliable, accurate self-service tools if you can never be certain what response might be given.

These limitations don’t mean you should write off ChatGPT or GPT-3 (and future versions) as completely ineffective in the realm of customer service and employee support. In some cases, one might be willing to accept a certain risk in exchange for very efficiently making large chunks of information available to a chatbot. Also there are ways to use the language power of GPT in a non-generative way, as we’ll explore in this post.

In any case, ChatGPT can only ever be used as just one piece of the puzzle, like content management, integration, user interface, and quality assurance. ChatGPT alone cannot replace all of that.

One of the design features of Creative Virtual’s conversational AI platform is the flexibility to integrate with other systems and technologies, including multiple AI engines such as transformer models like GPT-3. We are currently exploring the best way to interface with this model and use it to deliver value to our customers and partners.

Let’s take a closer look at ChatGPT, how it works, and the ways it can be used to deliver customer service and employee support.

 

What kind of AI is ChatGPT and how is that different from how V-Person works?

ChatGPT is a transformer model, a neural network, and is trained to predict text continuation. It uses a variation of GPT-3 which is OpenAI’s large language model (LLM) trained on a wide range of selected texts and codes. It is extremely powerful with respect to language understanding and common world knowledge. However its knowledge is not limitless and so on its own it will not have large parts of the information needed for specific chatbot use cases. Also its world knowledge is frozen at the time it was trained – currently it doesn’t know anything about events after 2021.

V-Person uses a hybrid approach to AI using machine learning, deep neural networks, and a rule-based approach to natural language processing (NLP). The machine learning component is integrated with workflow functionality within our V-Portal™ platform so enterprises can decide the best configuration for their conversational AI tool to improve in a controlled and reliable way. At the same time, natural language rules can be used as an ‘override’ to the machine learning part to ensure accuracy, resolve content clashes, and deliver very precise responses when needed.

We developed this approach to give our customers control over the AI to create accurate, reliable chatbot and virtual agent deployments. The use of natural language rules as a fallback option to fix occasional issues and finetune responses is much more efficient than trying to tweak training data.

 

Can businesses use ChatGPT to directly answer questions from customers and employees?

At the time of writing, ChatGPT is still in a research preview stage and highly unstable with no clean API available, so it’s not possible yet for businesses to use it in this way. However with its predecessor, InstructGPT, it is. It’s also worth noting that GPT-3 is high quality only in English and a few other languages which is another potential limitation for global use.

The biggest issue with using ChatGPT to directly answer questions from customers and employees is that it does not give you control over how it will respond. It could give factually incorrect answers, give answers that don’t align with your business, or respond to topics you’d prefer to avoid within your chatbot. This could easily create legal, ethical, or branding problems for your company.

 

What about simply using ChatGPT for intent matching?

There are two ways in which GPT-3 could be used for intent matching.

The first way just uses GPT-3 embeddings and trains a fairly simple neural network for the classification task on top of that. The second option also uses GPT-3 embeddings and a simple nearest neighbour search on top of that. We are currently exploring this last option and expect to get some quality gains from that approach.

 

Can I just provide a few documents and let ChatGPT answer questions by ‘looking’ at those?

Yes, this is absolutely possible. In fact, we have offered this functionality with V-Person for several years without needing GPT but none of our clients have been interested. GPT-3 improves the quality of this in most cases, but also comes with a higher risk of being very wrong. If an organisation is interested in using GPT-3 in this way, we can support it within our platform but what we currently offer already enables us to deliver document-based question answering.

It’s important to keep in mind that using ChatGPT to answer questions from documents is only addressing one aspect of the support expected from a virtual agent. For example, no transaction triggering API will ever be called by GPT looking at a document.

 

Is it possible to give GPT-3 a few chat transcripts as examples and let it work from them?

You can provide GPT-3 with sample transcripts and tell it to mimic that chat behaviour. But unless you want a chatbot with a very narrow scope, a few transcripts won’t be enough. If there are complex dialogue flows that need to be followed, you’ll need to provide at the very least one example of each possible path – most likely you’ll need more.

This raises some difficult questions. How do you maintain those if something changes? If you try to use only real agent transcripts, how do you ensure that you have complete coverage? How do you deal with personalised conversations and performing transactions that require backend integration? It may not be too difficult to train the model to say ‘I have cancelled that order for you’ at the right time, but that doesn’t mean GPT will have actually triggered the necessary action to cancel the order.

When you really examine this approach it becomes clear that this is not an efficient way to build and maintain an enterprise-level chatbot or virtual agent. It also doesn’t address the need to have integration with backend systems to perform specific tasks. Today our customers achieve the best ROI through these integrations and personalisation.

 

What other key limitations exist with using ChatGPT to deliver customer service or employee support?

Using a generative ChatGPT-only approach to your chatbot does not give you the opportunity to create a seamless, omnichannel experience. To do that, you need to be able to integrate with other systems and technologies, such as knowledge management platforms, ticketing systems, live chat solutions, contact centre platforms, voice systems, real-time information feeds, multiple intent engines, CRMS, and messaging platforms. These integrations are what enable a connected and personalised conversational AI implementation.

With ChatGPT there is no good way to create reliable and customised conversation flows. These flows are regularly used within sophisticated conversational AI tools to guide users step-by-step through very specific processes, such as setting up a bank account. This goes a step further than just creating a conversational engagement to employing slot-filling functionality, entity extraction, and secure integrations.

You also won’t have the ability to optimise the chatbot for the channels and devices on which it will be used. This includes using rich media – such as diagrams, images, videos, hyperlinks – within answers. For example, you can’t include an image carousel to display within a messenger platform. You won’t be able to show photos or drawings to help with a new product set-up. You don’t have the ability to display clickable buttons with options for the user.

 

As ChatGPT continues to change and moves out of the research preview stage, our expert team at Creative Virtual will stay on top of new developments and opportunities this technology offers. Our mission is always to innovate in a way that will help companies tackle their real challenges and deliver real business results – and our approach to this language model is no different.

If you’re interested in discussing more about how ChatGPT and V-Person might fit with your conversational AI strategy, get in touch with our expert team here.

Hot Off the Press: The Chatbot Buyer’s Guide for 2023

By Chris Ezekiel, Founder & CEO

Chatbots and conversational AI have been gaining acceptance as essential pieces of successful customer service and employee support strategies. If your organisation doesn’t have at least one of these solutions already, it’s likely you are planning to deploy one soon or are exploring the possibility of adding one to your 2023 strategy.

Unfortunately, as adoption of this technology is increasing so is the oversaturation of the market with poor performing chatbot products. Now many live chat, CRM, and contact centre vendors are attempting to jump on the conversational AI bandwagon with their own ‘add-on bots’. This is creating both confusion for buyers and a starker divide between vendors selling add-on bots and vendors that are true conversational AI specialists.

What makes a chatbot vendor a conversational AI specialist?

A conversational AI specialist is a vendor whose core product is their conversational AI platform. It’s not just something they have tacked onto another product offering to take advantage of the growing interest in chatbots. They have an established history of delivering successful virtual agent and chatbot solutions.

A conversational AI specialist has a focus on creating successful self-service experiences through tightly integrated and personalised conversational engagement. Their technology uses artificial intelligence (AI) to improve solutions in an accurate, reliable way that gives organisations full control. They are driving conversational AI technology forward with dedicated development teams and innovative deployments.

If a CRM, live chat, or contact centre vendor you are already working with suggests adding their own chatbot to your contract, it can be tempting to quickly accept as an easy way to meet growing demand for self-service. However, it is very important that you take the time to properly evaluate their solution and how it will work for your organisation.

If you are considering the purchase of an add-on bot – or any conversational AI solution, for that matter – you should first ask yourself the following questions:

  • Am I looking for a chatbot that will deliver high rates of self-service resolution and containment to reduce my support costs and alleviate pressure on live agents?
  • Am I looking to deliver a personalised self-service experience that goes beyond just a basic FAQ bot?
  • Am I looking for a platform that fits with a composable business approach and can easily integrate with my current backend systems so I can respond to market changes with agility?
  • Am I looking for a solution that offers me scalability, flexibility, and lots of customisation?
  • Am I looking to deploy a solution that will deliver long-term self-service success?

Did you answer YES to any of these questions? Then you need the brand new Chatbot Buyer’s Guide: Benefits of Collaborating with a Conversational AI Specialist.

This comprehensive 2023 guide takes you through the key differences between a solution from a conversational AI specialist and the most common add-on bots on the market today. It also includes a quick comparison chart to help with your evaluation and purchasing decision.

Unless you’re someone working in the conversational AI space every day, it can be extremely difficult to know exactly what questions to ask when comparing chatbot products. That’s why expert guidance is so important for making a smart purchasing decision. Differences in how AI is implemented, the types of self-service experiences that can be delivered, typical pricing structures, and compatibility with composable business models are just a few of the areas covered by this guide.

Download your copy of The Chatbot Buyer’s Guide for the expert insights you need to get your 2023 conversational AI journey off to a good start. Whether you start by reading the in-depth explanations of each key chatbot capability or immediately jump to the quick comparison chart at the end, this guide will help you create an informed evaluation process for a smart purchasing decision.

If you’re interested in learning more about working with a conversational AI specialist, the experienced team at Creative Virtual is always ready to arrange a live demo and consultation session.

Wishing you Joy & Good Cheer This Season & in the New Year!

The end of 2022 is nearly here and as we reflect on the past year, the Creative Virtual team want to express our thanks to all of our blog readers, customers, and partners. We appreciate you!

The last 12 months brought lots of exciting developments for the conversational AI industry and us as a company. We reflected on some of these in our 2022 in Review blog post. Since that look back was published, one of our other blog posts – Can Conversational AI Make Your CX More Human and Empathic? – won first place in the CX Technology category of the 2022 Customer Experience Update MVP Awards!

While it’s always nice to end the year celebrating a win, we’re also busy looking forward to 2023. We have some exciting things in the works, including a new chatbot buyer’s guide and the next release of our V-Person™ technology. While you wait for those, be sure to check out our other educational resources and subscribe to our Blog – if you haven’t already, of course!

On behalf of all of us around the world at Creative Virtual, we wish you joy and good cheer this season and in the new year!

A Look Back: 2022 in Review

By Mandy Reed, Global Head of Marketing

As the end of 2022 draws near, it is time once again for Creative Virtual’s annual year in review blog post. Every year we take this opportunity to reflect on the hard work of our team, our contributions to the conversational AI industry, and a few of our company’s biggest highlights from the past 12 months.

Two of the things we are proudest of at Creative Virtual are our experienced, dedicated team and the unique expertise we provide to our customers and partners. Whether it’s through our product development or our collaborations with individual clients, it’s important to us that we consistently deliver the best solutions possible. Having an analyst group recognise us for this is always an exciting bonus – and that’s what happened again this year.

AIxOutlook conducted an independent assessment of the major conversational AI vendors in the market and found Creative Virtual to be the Innovation Excellence Leader!

“Creative Virtual is the clear Innovation Excellence Leader in a crowded and competitive conversational AI industry. Businesses collaborating with them benefit from their expert consultation, resulting in customised, integrated, and personalised solutions that deliver real business value.”

This Innovation Excellence Leadership award recognises us as the foremost conversational AI innovator driving the industry forward. You can read more about AIxOutlook’s full evaluation by downloading the report for free here. This honour means even more as we prepare for the upcoming launch of the next innovative release of our V-Person™ technology.

The analysts at Celent conducted their own evaluation of intelligent virtual assistant platforms as well, focusing in on the technology within the retail banking space. Creative Virtual was one of ten vendors included, and we are proud of our ‘Luminary’ ranking in the final report. This means we excelled in all three of the dimensions evaluated: Advanced Technology, Breadth of Functionality, and Customer Base and Support. Celent clients can access the full report here.

We were also awarded ‘Best Conversational AI Solutions’ in the SME News 2022 IT Awards. These awards recognise companies driving for innovation and focusing on client-centricity while also remaining true experts in their industry. Being recognised as the best in conversational AI made our Founder & CEO, Chris Ezekiel, contemplate what makes a virtual agent or chatbot a true conversational AI solution and share his insights in a blog post.

women leaders of conversational AIIn October I was recognised for my contribution to the conversational AI industry by being included in the Women Leaders of Conversational AI, Class of 2023! I’m honoured to have been selected to be a part of this inaugural class and am looking forward to attending the ceremony at the Project Voice Women’s Summit in April. The This Week in Voice podcast host, Bradley Metrock, dedicated an episode to introducing each of the women selected – you can listen anywhere you get your podcasts or check it out on YouTube here.

Age UK, a Creative Virtual customer since 2017, collaborated with us on a new case study exploring the four main goals they are achieving with our V-Person technology: improve discoverability of a large amount of online content; give people more ways to easily interact with and find information; resolve easy-to-answer queries online to reduce Advice Line calls; and be proactive in testing new innovations to better meet the charity’s objectives. Check out the full Age UK success story here.

In May we announced a new partnership with Service Management Group (SMG) to deliver an industry-first dynamic assistance capability. Dynamic assistance integrates V-Person conversational AI with SMG’s digital experience solution to deliver real-time support to users as they encounter issues during their online purchasing journey. Learn more about the partnership and dynamic assistance here.

2022 ALGIM conferenceWe joined our partner Enghouse Interactive in Christchurch, NZ in November for the ALGIM (Association of Local Government Information Management) 2022 Conference. Creative Virtual’s Patrick Gallagher co-presented a well-attended session on creating award-winning chatbots in local government.

Also in November, Mugdha Desai, our Head of India Operations, took part in the Agile Mumbai 2022 Conference. The event theme was ‘Artificial Intelligence for Business Agility’, and Mugdha was a featured panellist for the session titled, ‘Benefits of AI for End User’.

Founder & CEO, Chris shared his conversational AI insights through a variety of articles, podcasts, and interviews this year, including:

The Creative Virtual team continued our tradition of sharing our expertise through our annual Blog Post Celebration for Customer Service Week and CX Day in October. This year’s posts covered multi-lingual digital customer service, the members on a conversational AI team, the battle between humans and technology, and setting customer service projects up for success. You can find the whole 2022 collection here.

We aim to publish interesting and educational posts on our blog throughout the year. This year I’m proud to have two of my blog posts selected as finalists in the 2022 Customer Experience Update MVP Awards: Composable CX: Becoming Agile and Flexible in the CX Strategy category and Can Conversational AI Make Your CX More Human and Empathetic? in the CX Technology category. Voting for the MVPs – most valuable posts! – has ended, and the winners will be announced later this month.

One of the industries in which the Creative Virtual team has extensive experience is the Insurance sector. We collaborated with Insurance Thought Leadership (ITL) to produce a whitepaper exploring how conversational AI is enabling insurance companies to greatly improve their customer experience while also slashing costs. You can get your own copy of ‘The Virtual Insurance Agent’ whitepaper here.

We also put together a short, animated video to explain V-Person for Insurance, our conversational AI solution designed specifically for the insurance industry:

Another area in which we have extensive experience is improving existing chatbot and virtual agent implementations.  We published an eBook – Conversational AI Issues & Solutions: Transforming Ineffective Chatbot & Virtual Agent Projects – that explores six of the most common reasons business leaders have given for being unhappy with their conversational AI projects and ways to overcome those challenges.

2022 has been a busy and productive year for us at Creative Virtual and, as the year comes to an end, we are excitedly looking forward to 2023. We hope you’ll stay connected by subscribing to our Blog on this page and signing up here for our Monthly Newsletter.

Will AI be 2023’s Co-worker of the Year?

By Mandy Reed, Global Head of Marketing

It’s that time of year when business predictions from analysts, experts, and industry insiders start to make an appearance. Not surprisingly, artificial intelligence (AI) is featuring prevalently in predictions for 2023.

For example, the analysts at Forrester are predicting that AI will become an indispensable and trusted enterprise co-worker next year:

“Rapid progress in areas of fundamental AI research, novel applications of existing models, the adoption of AI governance and ethics frameworks and reporting, and many more developments will make AI an intrinsic part of what makes a successful enterprise.”

This prediction is not shocking or out of left field. A Harvard Business Review article published in 2017 referred to AI, particularly machine learning, as ‘the most important general-purpose technology of our era’. Today a majority of enterprises have already made significant investments in AI and are seeing positive results. These successes are laying the groundwork for further investment and expansion across industries, departments, and use cases.

I particularly like the use of the word ‘co-worker’ in this prediction. Just like any other employee, these AI applications will be a part of the team and require human collaboration to be successful. AI is not poised to take over the enterprise. Instead, it is being used to support the organisation’s goals and help its human colleagues perform their jobs better.

Any AI or machine learning tool can only be successful if it has the right human co-workers. Humans are needed to create the application, train the system, monitor the performance, and perform necessary maintenance. Humans are needed to identify which tasks should be automated with this technology and which are better performed by a real person. Humans are needed to make decisions about when the system should be able to ‘learn’ automatically and when it needs a human-in-the-loop to make that judgement.

In return, the human co-workers benefit from having mundane tasks and processes automated so they can focus on more complex work. Human contact centre agents benefit from easy access to information so they can focus on providing compassionate, emotionally intelligent engagements. Human employees have instant access to IT and HR support online so they can easily get help regardless of when or where they are working.

The advancements in AI over the past several years have contributed to a growing list of practical and beneficial use cases. Enterprises are seeing success with AI-backed customer service, employee training, customer onboarding, personalised sales, advertising, content generation, code writing, product performance tracking – the list goes on. And they are seeing success because of the humans involved with creating, optimising, and using these tools.

Are you making AI an indispensable part of your 2023 plans? Will AI become a trusted co-worker for members of your team in the coming year? As with any prediction, it will be interesting to see how this one plays out within organisations next year.

If you’re looking at adding conversational AI to your 2023 strategy, the team at Creative Virtual can help. Our V-Person™ technology puts you in control of the AI so you can better care for your human employees, contact centre agents, and customers with strategically designed automated support. Request your personalised demo with an expert member of our team to learn more.

This Week in Voice: Conversational AI use cases, ethical oversight, & Darth Vader

By Chris Ezekiel, Founder & CEO

As someone who enjoys listening to interesting podcasts, I was excited at my recent invitation to be a guest on This Week in Voice. Now in its seventh season, this podcast is hosted by Bradley Metrock, CEO of Project Voice and covers some of the hottest conversational AI news stories of the week.

I joined the podcast’s panel of experts for Season 7, Episode 3 which was released on 29 September 2022. Bradley led us in a discussion of these four news stories:

Listen to the full episode below (or on YouTube here or wherever you get your podcasts) for my discussion with Bradley, Timo Kunz, and Sean McIlrath. Here are a few thoughts that stuck out for me from our conversation.

In the timeline of human history, voice-first applications like Siri and Alexa are very recent developments. I can’t help but wonder how they will impact the way we interact in the future as younger generations grow up not experiencing a time when they didn’t exist. It will be important as parents, and a society, to consciously balance the use of these technologies with human interactions, like making sure our children are still going to playgroup and engaging with their peers in person.

However, there are great use cases for this type of technology that can benefit our lives, such as alleviating loneliness and helping people find the help or information they need to deal with sensitive situations. They can also better our day-to-day lives with seemingly little things like checking the local weather or setting a timer when our hands are messy while cooking dinner. Yet not all the newest features being added by companies reflect use cases that are likely to become commonly used.

When it comes to discussing the ethical oversight of conversational AI, it’s important to first start with identifying the way it is being implemented. There are still lots of varying ideas around what ‘conversational AI’ is, and without a consensus you can’t identify an overarching ethical code. For example, Creative Virtual’s conversational AI technology uses a hybrid approach to AI in which there is no black box. Having this human-in-the-loop approach takes away many of the ethical concerns of a machine learning-only conversational AI solution.

I’m personally excited that James Earl Jones will continue to be the voice of Darth Vader through the power of AI, but not at all surprised by the capabilities of this technology. Creative Virtual was delivering this type of solution with a specialised voice partner 15-20 years ago for some of our avatars. This story does bring up the ethical oversight question again, though. It would be interesting to get a look at the contract to understand the specifics of how Jones’ voice can be used for the character.

Thanks again to Bradley, Timo, and Sean for the great discussion! Check out the full This Week in Voice episode:

 

Will Your Customer Service Project Sink or Swim?

By Rachel F Freeman, Operations Director

Creating a plan and an overall inspiring vision for which you imagine receiving accolades and awards sounds like a great place to be. However, the key to deciding whether the vision is going to sink or swim is based on the details, the objectives, and the team responsible for delivery.

Quick example: a 90-year-old woman decides that she’d like to make some fitness gains. Whilst she is an avid horseback rider, her thoughts move to jumping out of an airplane. She tells a local newspaper, and you can picture the publicity and the thrill of the activity. The small print is less than ideal: the woman, although fighting fit at first glance, has a recurring problem with blood pressure and dizziness. Altitude could wreak havoc on both of those issues, but she forgets to mention this. The news reporter is so caught up on the potential of the story, that he never asks for more details. The story never goes to print because the woman never jumps and pursues hiking instead on the advice of her doctor. Perhaps not quite as exciting on the surface, hiking is actually the best outcome for her situation and still an impressive achievement. This example ends well but not with the anticipated fanfare.

When applied to business solutions, this scenario can take on much heavier implications. Imagine a chief stakeholder has a vision for a customer service project full of whistles and bells but does not quite understand how to reach that point and leaves the details to the team. The team is so enthralled by the vision and the prospect of a new shiny development, as well as being caught up in the enthusiasm the chief has for the project, that certain basic and very important questions are not asked.

Questions such as: The idea is great, but what is the use case? What are the customer pain points to solve?  What are the measurable objectives? Can we achieve the objectives by doing something less time consuming and complicated if we try another option? And my particular favourite, have you considered the end-to-end journey for the project across all channels?

Failing to take the time to ask and answer these questions doesn’t necessarily mean the project will sink. It can, however, mean lots of wasted time and unnecessary confusion or frustration. The end result may be effective, but it probably won’t be as shiny as the initial vision.

Here is the controversial question: Do shiny things tarnish more quickly than a solid solution that is effective? I work for a software solution company where innovation and shiny, cool things are what we do.  I strongly believe based on my experience that you can have shiny and solid simultaneously when it comes to customer service solutions.

What I do not advocate is applying “shiny” without considering the questions above. For example, a smooth end-to-end digital user journey is a holy grail for online customer service. Yet just because you can help a customer smoothly journey through multiple channels for support doesn’t mean you should always do that. Don’t get caught up in the excitement of showing off all the whistles and bells of different channels. Instead, always ask if there is a real use case or a point beyond it seeming to look impressive.

Customers don’t care if your tools and channels are innovative and shiny if they aren’t getting their questions answered. They don’t care about your inspirational vision if their time is being wasted because you haven’t planned your customer journeys based on the real way your solutions are going to be used.

Likewise, why waste your team’s time by trying to solve all customer problems across multiple channels when, for instance, certain use cases will truly only be used via a mobile device and not on a desktop? If the team is caught up in the hype and overlooking the details, you risk delivering a mediocre project that just floats along instead of maximising on the potential of the initial vision.

Digital customer service awards are given to those projects that showcase shiny developments, but only when they take the customer down the right path at the right time and serve the right information as required.

This Customer Service Week let’s celebrate the people on our teams that pay attention to the details and make sure we answer the important questions. They are the ones that enable even the most ambitious and shiniest visions to become a reality through solid, successful solutions.

I’d much rather swim with the confidence that my project has buoyancy based on the right questions being answered than risk sinking in a sea of bright and unchallenged options – and I’m guessing you would, too! If you’re interested in learning more about how the Creative Virtual team can help you with customer service solutions that are both shiny and solid, contact us here.

Multi-Lingual Digital Customer Service is Easier Than Ever

By Maria Ward, Account Manager & Knowledgebase Engineer

Good day – Guten tag – Buenos días – Bonne journée – Goededag – Buona giornata – There are more than 7,000 known languages spoken in the world today. So, it’s no surprise that language is a common barrier in both personal and business interactions.

Back in 2014, the International Customer Management Institute (ICMI) published a report titled The Growing Need for Multilanguage Customer Support. Their survey of customer service leaders found that 72% said support in a customer’s native language increased their satisfaction with customer support and 58% said it increased loyalty to the brand. Over half acknowledged that offering support in a customer’s native language was a competitive differentiator.

This research is old now, but the desire of customers to have native language support is still very much there. Luckily for businesses, new technologies are making it easier for them to offer multilingual customer service on digital channels than it was in 2014.

One of these technologies is machine translation which has seen huge improvement in recent years. Developments over the past two years have greatly increased the accuracy and reliability of many translation engine applications. This has opened up new possibilities for delivering multilingual customer self-service.

For example, this year I’ve been working on several conversational AI projects with businesses taking advantage of machine translation to provide customer service in multiple languages. One is with an organisation that has used V-Person technology since 2016 on their UK website. They are an international company and became interested in exploring ways they could leverage their successful English-speaking virtual agent in other countries.

Using an automatic translation engine is a great solution for them because it is cheaper, simpler, and easier than creating a whole new virtual agent in a second language. It lets them build on the years of investment they had already made in their English-speaking virtual agent. Now they are using that same knowledgebase to provide self-service on their German website by adding translated versions of their virtual agent answers and integrating with a translation engine.

Here’s how it works: The customer enters their question in German in the virtual agent. A translation engine is utilised to translate that input into English. The translated input is then matched in the knowledgebase to the correct piece of content. The virtual agent selects the German version of the response from the knowledgebase and presents that answer to the customer.

The company started the project by identifying the top FAQs for their German website. They then provided German translations for those pieces of content. The team also worked on making any modifications to the natural language processing (NLP) to accommodate for differences in how a German user might ask those questions or ‘weird’ automatic translations that may be returned by the engine. After a successful launch of the German-speaking virtual agent, work got underway to slowly expand the content.

Another project I’ve been working on recently is for a brand-new virtual agent. One of the reasons Creative Virtual was selected as their conversational AI provider is our ability to integrate with translation engines and manage multiple languages within one knowledgebase. This company is starting their project with seven languages.

The process for this multi-lingual virtual agent has been a little different than my first example because there was no existing knowledgebase at the start. My recommendation for any organisation looking to build a new virtual agent in multiple languages is to start by finalising all content in the main language first. This will save you time with the translation work because changes to an answer typically means having to make updates to that answer across all languages.

Using automatic translation to expand a virtual agent to multiple languages is cost-effective and saves time, but it’s not a perfect solution. You’re likely to encounter content clashes and inputs that aren’t matched with your existing content. This is why you need a virtual agent management platform that has the right functionality to specifically support integration with a translation engine. The projects I’ve been working on are successful because of our V-Portal™ platform.

The right conversational AI platform will support workarounds for the content clashes and customisations for your different languages. It should also use artificial intelligence and machine learning to provide relevant ‘did you mean’ suggestions to users when their input doesn’t match with a specific piece of content. You also have the ability to set the virtual agent to ‘auto-select’ answers. This means that if the NLP fails to match the input directly with the correct answer, it pushes one of the ‘did you mean’ answers automatically as long as that answer meets a specified confidence level.

Maintenance of your multi-lingual virtual agent is also easier when you have a highly functional management platform integrated with a translation engine. When you need to make updates to an answer, you can do that quickly across all languages since all answers are listed under the same intent in the knowledgebase. Also, any changes you make to the NLP in your main language benefits all languages. And as machine translation engines improve, you automatically benefit from the most recent developments without having to do any work on your virtual agent.

The quality of your customer service affects customer loyalty, repeat business, and your brand reputation. Offering native language support can really improve your support experience. Technologies like automatic machine translation are making it easier than ever to give customers multi-lingual customer service options. Contact the experts at Creative Virtual to learn more about how we’re helping companies deliver these solutions.

Are All Members of Your Conversational AI Team Equal?

By Laura Ludmany, Knowledgebase Engineer

There is a question I came across recently which made me think and raises a good discussion for Customer Service Week: Who is the most important participant in the workflow of the development and maintenance of any AI-powered customer service tool?

Let’s imagine we build a virtual assistant from scratch for a large enterprise client where the solution must be scalable, available across multiple channels, and delivering measurable results. There are many out-of-the-box, seemingly quick solutions on the market which catch attention with claims of being up and running with little time and effort. However, these deployments are not often expandable or manageable as the real-life interaction traffic increases. These chatbots often cannot mature at the same pace as the usage, leaving a bitter taste in the users’ mouths and doing more harm than good for the organisation.

To deploy a chatbot just for the sake of having a chatbot, to tick one cool gadget off the list, to appear to be keeping up with the technology trends – none of these are good goals for a conversational AI project. The goal should be a long term one: to leverage the virtual assistant to its full capabilities; to discover new integrations, features, channels and start using it in a proactive way; to listen to your customers’ needs and feedback gathered in conversations; to broadcast news and promote products, offers, and sales to users in a centralised, accessible way.

Building and managing a virtual assistant with the goals described above, requires more people than a reader from outside the industry would probably imagine:

  • We need a salesperson to introduce the technology to the client and translate their business requirements into virtual assistant project specs.
  • We need a project manager who keeps the momentum going between the client and the team, organises the resources, streamlines the workflows, oversees the processes, and really just holds everything together.
  • We need a knowledgebase/AI engineer who designs the user journeys, builds and updates the database of the chatbot, and manages the algorithm that matches the submitted questions with the intent.
  • We need ‘hard techies’, the software engineers and developers who build the user interface, work on the different integrations, design the templates, and ultimately deploy the virtual assistant.
  • We need an analyst to look after the reporting side of the tool, understand the client’s KPIs, implement those indicators to the reporting platforms, and then deliver the required insights and statistics to the desired reporting suites.

Depending on the size and nature of the project, there can be multiple people sharing the same sets of tasks and many times there can be even more experts involved in a launch of a single chatbot.

So, then the question is: Who is the most important part in this workflow? The sales lead as he ‘brings’ the business in and has to pitch the future client? The project manager who deals with both sides and oversees everything? The AI engineers who build and maintain the ‘brain’ of the virtual assistant? The software developers who bring the chatbot to reality by building the user interface? The analytics experts who provide the reports which show the performance and measurable results of the tool?

Hint: there is no right or wrong answer. Everyone has different views and valid arguments about it. We might say very diplomatically that each and every person has equal importance in the process.

I think, based on my experience, the most important participant in a chatbot project is the client. As the conversational AI vendor, we might have the latest integrations, the coolest features on the template and the best performing chatbots ever, but our client needs to be heavily involved in the continuous journey of a conversational AI tool for real success.

There is no sadder thing for us as chatbot professionals, than to build a majestic AI tool which is then no longer looked after as it is supposed to be. There will always be new user trends evolving, new unrecognised user questions to be addressed, and new technology updates becoming available.

Hence each point of contact has a crucial role to play to win the ‘heart’ of the client, to prove and promote the value of the chatbot, to raise interest, show enthusiasm and engage with the stakeholders. Everyone in the team needs to be proactive and showcase the capabilities of the virtual assistant, whether that be through post-sales add-on integrations and launches, regular touch base meetings, analysing and improving user journeys, flagging content gaps, showing the latest technology solutions, or sharing new reporting features. We have to pass on the passion we share within our team to the client who is just starting to discover the endless possibilities and advantages conversational AI has to offer.

So, from my point of view, making the client interested, invested and an advocate for their chatbot will ultimately make them the most important participant in the chatbot workflow. As we celebrate Customer Service Week, we should recognise their crucial role. At Creative Virtual, we celebrate all our clients who are so devoted to keeping their virtual assistants successful and with whom we work hand-in-hand, day-to-day with over years and even decades.