Tag Archive for: artificial intelligence

​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.

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.

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.

Customer Service Week Musings: How does a machine know if it’s wrong?

By Laura Ludmany, Knowledgebase Engineer

There are many comparisons dealing with the main differences between humans and machines. One of the recurring points is while humans have consciousness and morals, machines can only know what they are programmed to, hence they are not able to distinguish right from wrong unless they are provided data to make decisions based on that information. There have been many discussions on the self-awareness of robots, which is a topic as old as Artificial Intelligence, starting from Isaac Asimov’s three laws of robotics, continuing to the Turing test and nowadays AI ethics organisations.

One thing is commonly agreed – bots need to be ‘taught’ morals, and to achieve this there could be two approaches, both having their advantages and disadvantages. The first one contains a loose set of rules, but plenty of space for flexibility; this system could always reply to questions. However, it could also result in many false positives cases and could go wrong on many levels. The other would mean more rules and a narrower approach. The system could answer a limited number of queries, however, with very few or non-false judgements.

What does this mean from the customer service and customer experience (CX) view and for virtual agents answering real time customer queries? If we narrow down our conditions, bots would deliver the right answers at most times. However, they could not recognise many simple questions, making users frustrated. The same can happen with the loose set of conditions: the assistant would easily deliver answers but could misinterpret inputs, resulting again in annoyance.

To solve this problem, we must use a hybrid approach: an AI tool can only be trained appropriately with real-life user inputs. While we can add our well-established set of rules based on previous data and set a vague network of conditions, the bot will learn day-by-day by discovering new ways of referring to the same products or queries through user interactions. Half of a virtual assistant’s strength is its database, containing these sets of rules. The other half lies within its analytics, which is an often-overlooked feature. What else could be better training for a CX tool than the customers leaving feedback at the very time an answer was delivered? Conversation surveys are not only important to measure the performance of the tool. They are also crucial for our virtual assistants to be able to learn what is wrong and what is right.

Our approach at Creative Virtual to reporting is to follow the trends of ever-changing user behaviour. We offer traditional surveys, which measure if a specific answer was classified as helpful or not by the user and if it saved a call. Sometimes, the specific required action or transaction cannot be performed through self-service options and the customer must make a call, or else, the answer has been slightly overlooked and needs to be updated – for these cases there is a designated comment section, so users can express themselves freely.

We all know from personal experience, that we can’t always be bothered to fill out long or detailed surveys – we are on the go and just want to find the information we were looking for without spending extra time to leave feedback. This is typical user behaviour, and for this we came up with different options for our clients such as star ratings and thumbs up and down, keeping the free text box, to make the rating simpler for users. The solutions deployed are always dependent on the requirements and preferences of our clients, which are in line with the nature of their business and their website design. For example, financial organisations usually go with the traditional options for their customer-facing self-service tools, but internal deployments often have more creative user feedback options.

What if, during a conversation, a virtual assistant delivered the correct answer to five questions, but two answers advised the user to call the customer contact centre and one answer was slightly outdated? Does this rate as an unsuccessful conversation, due to three unhelpful answers? To solve this dilemma, we have End of Conversation Surveys, which ask customers to rate the whole conversation, on a scale to 1-10 and choose what they would have had done without the virtual assistant. As always, there is a free text box for further communication from the customer to the organisation. These surveys show high satisfaction levels as they measure the overall success of the conversation, which can have some flaws (just as in human-to-human interactions), but still can be rated pleasant and helpful.

Let’s take a step further – how can the virtual assistant learn if it was right or wrong if none of these surveys have been taken up by the user? Is this valuable data lost? Our Creative (Virtual) analytics team have levelled up their game and came up with a solution! During voice interactions, such as incoming calls to customer contact centres, there is a straightforward way to understand if the conversation wasn’t successful, even if it wasn’t stated explicitly, as the tone might change or the same questions might be repeated. But how can we rate a written communication with our customer? There has been a specific platform developed, which sits on the top of our previously described survey layers. This platform classifies the whole conversation, with a carefully weighed several-factor-system, which can be tailored to our client’s needs, containing factors such as if there has been more than one transaction, whether the last customer input was recognised by the virtual assistant, if there have been negative user responses recorded, etc.. The primary ‘hard’ indicators remain the user-filled surveys, so this is just a nice icing on the cake, as our mature deployments show over 80% of successful conversation rates.

With our proactive approach and multi-layer analytics tool sets, we can be sure that our virtual assistants will learn more and more about what is right and wrong, to increase the customer satisfaction level continuously. However, I think no machine will ever be able to answer all questions correctly, as this would mean that deployments have stopped being fed up-to-date real-life data. Our world is changing rapidly as are our user queries. These cannot be fully predicted ahead, just analysed and reacted to appropriately. As long as AI tools serve customer queries, they will always face unknown questions, hence they will never stop learning and rewriting their existing set of rules.

As we celebrate Customer Service Week this year, we need to recognise the role customers play in helping to teach our AI-powered chatbots and virtual assistants right from wrong and the experts that know how to gather, analyse and incorporate that data to help train those tools. Check out our special buyer’s guide that explains why experience matters for using this hybrid approach to create reliable and always learning bots.

Tips for Deploying AI Chatbots & Virtual Agents

By Chris Ezekiel, Founder & CEO

Chatbots, smart help, virtual assistants, virtual agents, conversational AI – there are lots of names for this automated, self-service technology being used today. Regardless of what you call it, the objective for including it as part of your customer service strategy is to deliver quick, easy access to information. How to select and deploy the right technology to do that for your organisation was the focus of the webinar I recently presented with Engage Customer.

In the webinar, Tips for Deploying AI Chatbots & Virtual Agents, I talked about some key questions to keep in mind when adding one of these solutions to your customer experience (CX) strategy. You want to ask: How can I ensure my chatbot or virtual agent is:

  • Providing accurate and personalised information?
  • Creating a positive and seamless experience?
  • Using artificial intelligence (AI) and machine learning in a reliable way?
  • Able to grow and expand with my digital strategy?

Deploying a solution that enables you to integrate with other systems and knowledge repositories is crucial to success. You want a solution that is backed by an orchestration platform that allows you to bring together all of the content sources and manage the natural language processing (NLP), intents and machine learning to keep the conversations flowing in a seamless, personalised way across customer touchpoints. You also want to be learning all the time from these conversations in such a way that the human content owner works alongside the machine learning component to provide the best possible customer experience.

I am a great believer that the best way to really understand the technology and why these questions are so important is to see the technology in action. During the webinar I shared a series of live demonstrations of solutions currently deployed for companies in the telecommunications, financial services and travel sectors. I selected these examples because they showcase how the technology is being used across a variety of customer touchpoints and with various integrations to deliver customised, seamless experiences.

To help companies get started with selecting a new chatbot or virtual agent – or finding a solution to replace a poor performing tool – I ended my presentation with four important tips:

  1. Work with an experienced vendor
  2. Select a reliable technology
  3. Look for flexible integration options
  4. Evaluate the orchestration platform

I went into detail on each of these tips and shared some specific questions to ask during the evaluation process to ensure you are deploying a technology that will work for your specific goals and use cases. It’s important to consider how the solution not only fits with your immediate plans but how it will evolve and grow with your company and strategy.

My thanks to Steve, Katie, Dominic and the entire team at Engage Customer for hosting this webinar! You can watch the webinar recording on-demand to see the demos and find out more about my tips and best practices for deploying AI chabots and virtual agents.

If you want to learn more about Creative Virtual’s experience and technology or are interested in arranging an individual workshop, contact us here. The Creative Virtual team is ready to help you get started on your successful virtual agent strategy.

Simply The Best!

By Chris Ezekiel, Founder & CEO

With chatbot companies springing up on an almost daily basis, how do companies select the right one? Well, now the work has been done for you and there’s a clear choice! Frost & Sullivan have recognised Creative Virtual as the Product Leader! And the full report is available for you to download for free. Frost & Sullivan evaluated companies across two key factors, each with five benchmarking criteria. Creative Virtual was rated as ‘Excellent’, receiving an average score of 9.00/10 across these categories. The second and third place companies came in at 8.50 and 8.25.

Frost & Sullivan Best PracticeAs we celebrate our fifteen year anniversary, I cannot think of a better way to start the year (and the celebrations!). Not least because this is the first detailed independent comparison of combined virtual assistant, chatbot and live chat technology; and especially as the competition are some of the world’s largest technology companies. This comes on the back of our Queen’s Award for Innovation, that we were honoured to receive in 2017, and which is a five-year award. I couldn’t be more proud of what our team, together with our customers and partners, have achieved.

We often get asked how we compare with our competitors, and of course we have a lot to say on the subject! – but now with this independent report, the choice for companies wanting to deliver significant business value as well as superior customer experience, is crystal clear!

As a company that prides itself on continuous innovation, we certainly won’t be resting on our laurels. Right now, in our labs around the world, we are working on even more exciting developments that we look forward to bringing to the market soon.

And in the meantime, we’re very much looking forward to shouting about this amazing achievement from the rooftops!

AI-Enhanced Self-ServiceIt’s an honour to be leading a global company that has been acclaimed as the leader, and I know it will also mean a lot to all our great people, as well as our customers and partners who have put their trust in us and worked hard with us to create amazing solutions – which I know have played a pivotal role in this award. I would like to publicly say a big thanks to all our supporters!

For more on this Frost & Sullivan Best Practice Award and why Creative Virtual was selected as the 2019 AI-Enhanced Customer Self-Service Product Leader:

Fifteen Years & Counting: Navigating the chatbot, virtual agent and AI revolution

By Chris Ezekiel, Founder & CEO

As we celebrate our fifteen year anniversary, I wanted to share with you some of my thoughts on founding and running Creative Virtual.

In those early days, we were focused on winning deals as the plan from the outset was to grow the company organically; although the objective was always to create a global company; so many companies fail or are sold before getting to that point; and it’s a testament to our amazing team, that we have become a global leader. It’s an honour to lead such a great team!

People come and go within organisations of course, and that’s healthy for both the company and the people. However, there becomes a core backbone of people that make up the fabric – the culture – of what Creative Virtual stands for: passion, innovation and quirkiness are at the heart of everything we do. And the people become the DNA and vice-versa.

There’s also ups and downs of course; growing any business isn’t linear! We’ve certainly had our bumps along the way. People often ask me how I make the tough decisions and how I relax. We all have our own ways – for me it’s a recipe of: spending time with friends and loved ones, running, watching West Ham, physics, snowboarding, photography and art.

I took up running about five years ago, and really enjoy the energy it gives me; I find that being in good shape physically makes a big difference mentally. It also allows me to contemplate and to think about things differently. I find doing completely different things – like painting, which I’m absolutely useless at! – really helps one to switch-off from business. And speaking of DNA…West Ham is in my DNA…so there’s no escape from that as any football supporter will know! It’s another great way, for 90+ minutes, to switch-off from everything else! Spending time with friends and loved ones helps me to put things into perspective – as does my love of physics! Snowboarding gives me my adrenalin rush!

I also love travelling around the world and spending time with our people, customers and partners. It’s an absolute joy working with our great people and some of the world’s leading organisations.

We have been fortunate over the years to win many awards, and it’s so delightful when our customers win awards too. Our customer, Transport for New South Wales, won an impressive three awards for their RITA chatbot during 2018! In 2017 we were honoured with The Queen’s Awards for Enterprise: Innovation. I couldn’t be more proud of what our team has achieved, and it was beyond what I had dreamt for Creative Virtual. Going to the Palace and meeting the Queen, Prince Philip and other members of the Royal Family was incredible. And being a five-year award, we celebrate our fifteen year anniversary in its continuing glow.

Having been a leading company in the establishment of the virtual agent market – and developing best practices in terms how virtual agents, live chat, artificial intelligence (AI) and knowledge management work together to create world-class customer experiences – there is still much more to do as organisations transition from the centralised contact centre model to one where the customer is at the centre of the universe. Helping organisations navigate through this has as much to do with the expertise of our people as the actual technology; and with such an experienced and dedicated team I know we are on the right path to remain at the forefront of the chatbot/AI/contact centre revolution!

Being an optimist by nature, my way of keeping my feet on the ground is to keep in mind the words of the late Nobel Prize-winning physicist Richard Feynman, “The first principle is that you must not fool yourself and you are the easiest person to fool.”

Here’s to the next fifteen years and the new challenges that lie ahead!

Employee Engagement Remains a Top Priority Alongside Customer Engagement for 2019

By Liam Ryan, Sales Director

Welcoming a new year often goes along with an ‘out with the old, in with the new’ mindset, but two things that are staying hot on companies’ 2019 agendas are customer engagement and employee engagement. This was glaringly obvious at the recent AI & Robotics Directors’ Forum: AI Enhancing Customer & Employee Engagement. From the delicious smoked salmon and cheese bagels served for breakfast to the final moments of the drinks reception at the end of the day, the event highlighted companies’ increased focus on improving engagement across the board.

Customer experience and engagement has been a top priority for most organisations for years, but improving employee engagement is a more recent addition to agendas. Organisations are coming to understand the benefits of providing better and easier support for employees. They are also coming to understand that many of the same digital tools, such as chatbots and virtual agents, that they are utilising to improve their customer experience can also be leveraged to improve their employee experience.

The event agenda featured presentations and panel discussions focused around practical uses of artificial intelligence (AI) in the customer and employee engagement spaces. I was joined at the event by Chris Ezekiel, Founder & CEO, who presented a morning session titled ‘Taking Engagement to the Next Level: Conversational AI for customers & employees’. He shared some insights into the expectations of customers and employees and then took an in-depth look at how organisations can bring everything together to centrally control a consistent, convenient and efficient experience for both customers and employees.

Using a single orchestration platform enables you to deliver consistent information and support across touchpoints and allows you to more easily engage users on the devices, channels and apps they are already using in their everyday lives through chatbots, virtual agents and live chat. For conversational AI to be effective, it must use a hybrid approach of machine learning and human input. The orchestration platform you put in place must allow you to manage that combination of humans and AI so you can deliver the best experience to users and maximise on your investments.

During his session, Chris shared a few live demonstrations to illustrate industry best practices. The best way to really understand how this all comes together is to see it in action, so if you weren’t at the event I encourage you to request a demo. Our team is always happy to arrange a time that works with your schedule so you can experience the ways conversational AI can help you improve your customer and employee engagement.

Our thanks to the AI & Robotics Directors’ Forum organisers for inviting Creative Virtual to take part in your last event of the year!

The Numbers Don’t Lie: An interesting evening with the Tech Track 100

By Rachel Freeman, Operations Director

Creative Virtual has been receiving a lot of accolades in the past few years and the challenge for a blog post is what to say to make each new title or award stand alone and special. We never want to be complacent, but our readers may be a little tired of hearing all the good news – or not?!

Making it onto The Sunday Times Hiscox Tech Track 100 list at 72 was an honour simply because the numbers don’t lie and there is no judging panel doing the placements. The league table ranks Britain’s 100 private technology companies with the fastest-growing sales over their latest three years.

The Sunday Times Hiscox Tech Track 100The 2018 Tech Track list was published in September – read our official announcement here – but attending the awards ceremony was an added wow factor. The event was hosted at The Brewery in London on 6th November and had 294 guests in attendance from the 100 featured companies and sponsors.

Myself, Chris Ezekiel (Founder & CEO) and Peter Behrend (CTO) were in attendance together, but once the canapes were scoffed and a group photo of us taken, we were seated at separate tables with the objective to get all attendees to mingle and learn more about the 100 companies on the list by sitting and speaking to different representatives.

People at my table represented various sectors including trucking, AI (that would be us!), HR incentive packages, insurance, bill paying and venture capitalists. The mood at the event was tingling with drive and achievement and it was a buzz to sit amongst such a varied group of companies – ranging from the altruistic helping people with diabetes to devising ways to make hair removal simpler!

The speakers were interesting and luckily didn’t drag on; the food was noticeably absent of rubber chicken which meant that dinner was quite tasty. Advice from the speakers was offered including: always listen to your customer, ask probing questions, put in the hard graft, don’t give up on your idea and be prepared for the unexpected. The Founder of Candy Crush (a former Tech Track list member before going public) was amongst the speakers, and I found it interesting to hear how unprepared they were for the success that came to them after several years of being on the brink of closure.

Had there been time to sit amongst all 32 tables in the room, I’ve no doubt there would be a cartful of stories and advice and impressive tales of success. The time that we did have was fruitful and dare I say a bit fun if not definitively interesting. It’s a recognition that differs from the others in that the numbers put us on the list and we are then given the opportunity to shine and explain our story… our story is also a great one and whilst three of us were there at the event, we were representing the strong team behind us across the globe.