Tag Archive for: chatbot

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.

Building a Cohesive Virtual Agent and Live Chat Solution

By Mandy Reed, Global Head of Marketing

Virtual agents. Live chat. Some of you may remember the days when companies wanting to implement customer support on their website believed they had to make a decision: either a virtual agent or live chat; either automated self-service or human-assisted web chat.

This was the common thinking a decade ago when Creative Virtual integrated their virtual agent deployment for a leading telecommunication’s company in the UK with live chat, creating a seamless handover for users within the same template. Around the same time, an online financial services company in the US collaborated with Creative Virtual to add a virtual agent in front of their existing live chat offering to reduce repetitive questions being handled by live agents. Both of these companies were very forward-thinking in their approach to combining these technologies.

Now in 2022, virtual agents and live chat are seen as complementary tools instead of rival solutions. In fact, it’s become best practice to integrate the two in order to improve digital customer support. In the recent webinar ‘Deploy Chatbots to Meet Self-Service Demands’, Gartner analysts talked about the importance of seamlessly escalating customers from virtual agent to live chat agent to create positive, cohesive service experiences.

Instead of a conversation about which of the two technology options to implement, organisations are having discussions about how to incorporate both into their digital customer experience (CX) strategies. Companies that have already done so are seeing a variety of benefits to both their customer and agent experiences, including:

  • Customers are always supported with 24/7 access to self-service even outside of live chat hours or when all live agents are busy.
  • The most common questions are answered by the virtual agent, reducing the overall number of live chat contacts and the need for agents to answer simple, repetitive questions.
  • Virtual agents do the discovery work and pass a complete history of the customer’s conversation to the chat agent, creating a seamless experience for both user and agent.

Adding a virtual agent to an existing live chat deployment

If you already have live chat available to customers and are ready to add a virtual agent, you can jumpstart the project with transcripts from those conversations. By analysing your live chat transcripts, the virtual agent vendor can identify which questions can be answered without human involvement. This analysis can also identify the percentage of live chats that can be deflected with successful automation. It can assist you with identifying key metrics and help build your business case.

Many traditional live chat providers are now offering virtual agents and chatbots as an add-on solution. Unfortunately, often these vendors maintain their focus on driving usage of live agent support. Because of this, the functionality of their virtual agent tools is limited. It’s also not unusual for them to use a pricing structure for self-service that’s similar to their live chat, such as charging by transaction. This makes the virtual agent both poor performing and expensive.

Self-service tools from virtual agent-first vendors deliver better user experiences and more reasonable pricing models. A sophisticated conversational AI platform will support integration with a variety of different live chat providers. This means you can deploy a highly functional virtual agent with seamless handover to your existing live chat solution, providing both successful self-service and easy escalation to human-assisted support.

Adding live chat to an existing virtual agent deployment

If you already have a virtual agent available to customers and want to add handover to live chat, you should start by talking with your virtual agent vendor about your options. Confirm that your existing conversational AI platform supports integration with live chat to handover users within the same template and pass a full conversation history to the live agent. If it doesn’t, then it’s time to find a better virtual agent solution.

Ideally, you’ll already have both a virtual agent platform with flexible integration options and a vendor you trust with expert insights. If they offer their own live chat product, explore that option first. Ask them about their integration experiences with different live chat providers and how their joint solution is better. Ask them for live examples of other similar deployments and for existing client references to get additional insights.

You can use your virtual agent transcripts and metrics to assist with setting up custom rules and triggers for users to be escalated from self-service to live chat. How users have engaged with your virtual agent should inform the set-up of live chat to ensure you are adding it in a way that will deliver the best experience possible for your customers.

Adding both a virtual agent and live chat or changing providers

If you need both virtual agent and live chat technologies, begin your selection process with the virtual agent. Customer engagements will start with your virtual agent, so you want to ensure you are delivering a positive self-service experience even if escalation to a live agent is necessary. A ‘bad’ virtual agent frustrates users and makes the job of your live chat agents even more difficult.

Use the advice shared above and in this Guide to Selecting a Virtual Agent or Chatbot Vendor for selecting a virtual agent platform. If you have an existing virtual agent, either live or in-progress but never deployed, be sure to ask how a new vendor can reuse it so you don’t lose that investment. If you have live chat or contact centre transcripts, also ask about using an analysis of those to jumpstart a new virtual agent.

Then once you have found the conversational AI platform that best fits your organisation and goals, explore the live chat technologies that integrate well with your virtual agent choice. Use the expertise of the virtual agent vendor to help with your selection. They will know from experience which live chat systems deliver the greatest results for your industry, use case, etc. when integrated with their self-service tools. Test some existing joint deployments and talk to other companies using both technologies about their experiences.

Developments in conversational AI over the past decade have enabled a more seamless integration of automated self-service and human-assisted support. With the right technologies, organisations can take advantage of these advancement to deliver improved end-to-end experiences for both customers and agents. Cohesive, convenient customer service is key to building brand loyalty and reducing customer churn. It can provide real business value today and give you a solid foundation for the future.

Resolve to Make Your Conversational AI Project Healthier this Year

By Mandy Reed, Global Head of Marketing

The new year is here and that means it is time for New Year’s resolutions. The most common personal resolutions are focused on being healthier – exercising more, eating better, improving fitness, losing weight, stopping smoking. People join the gym, sign up for weight loss programmes, and download meditation apps.

But what about your conversational AI project? Does it need a New Year’s resolution to be healthier in the new year, too?

If your organisation already has a conversational AI project, then you don’t need me to wax on about the importance of digital customer support. You get it. However, if you’re concerned that your current conversational AI tool isn’t up to the task of improving your digital support experience in 2022, then it’s time to make a resolution for change.

Even the best laid plans sometimes take a wrong turn or need to be tweaked as customer expectations and your organisation change. The start of a new year is the perfect time to take a step back and re-evaluate your conversational AI project and strategy. If this review leaves you dissatisfied with what you find, you’re not alone. Here are some common reasons other organisations have given for being unhappy with their conversational AI projects:

  • I can’t expand my solution to support my growing business and customer base.
  • I have limited integration options to create a seamless and personalised experience.
  • I started my project with an inexperienced start-up that isn’t able to provide the technology updates and support I need from my conversational AI vendor.
  • I am struggling to manage multiple chatbots across different business divisions or departments.
  • I am unable to staff my chatbot project with internal resources with the necessary knowledge and experience.
  • I don’t own the user interface or training data with my current chatbot provider.

The good news is that none of these common issues are dealbreakers that mean you must scrap your current virtual agent or chatbot project and start over. Like any New Year’s resolution to be healthier, you just need a plan that starts where you are and takes you to your goal of creating a successful, valuable, and healthy solution.

Your first step should be to download the new ebook Conversational AI Issues & Solutions: Transforming Ineffective Chatbot & Virtual Agent Projects. It takes an individual look at each of the common issues listed above, explaining how they can negatively impact your conversational AI project and exploring ways they can be solved.

When you’re ready to work out the details of your plan for a healthier chatbot or virtual agent and put it into action, the Creative Virtual team is ready to be your personal trainer and coach. Contact the team here to learn more about the expert consultation and technology that’s helping brands around the world deliver reliable and valuable conversational AI solutions.

This new year, resolve to transform your conversational AI project into a healthier, more effective customer service solution. Make 2022 the year your customers, employees, and company experience the full benefits of a successful chatbot or virtual agent.

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

By Mandy Reed, Global Head of Marketing

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Conversational AI Data and Powerful Customer Insights

By Mandy Reed, Global Head of Marketing

These days it can be easy to feel like we’re in a constant state of information overload. The 24-hour news cycle combined with social media and the ability to Google anything always at our fingertips makes it difficult to escape the relentless barrage of information. This can also make it difficult to discern what information is genuinely important and worthy of our time.

The same is true when it comes to your organisation’s customer experience (CX). There is information floating around everywhere on customer behaviours, preferences, and sentiments. However, it can be a struggle to gather and identify the customer insights that are meaningful and most important for your CX strategy.

In fact, Gartner analyst Augie Ray identified ‘looking in the wrong places for customer insight’ as one of the key mistakes that kill CX programmes in their infancy. He points out that you can’t expect customer-centric results from a strategy that is not based on real customer insight and understanding. Likewise, you won’t be able to measure the impact of your programme if you aren’t gathering and analysing customer feedback, sentiment, and experiences.

Conversational AI is growing in popularity among businesses and their customers because of the positive self-service experience high-quality virtual agents and chatbots are delivering. However, organisations should never overlook the added benefits they gain by analysing the conversational data these tools can collect.

In a chatbot vendor selection guide, conversational AI expert Ridhi Mathur explains:

“In this era of data, a sophisticated virtual agent can play a very significant role for many businesses. The conversational data collected is very rich. It can be analysed and mined to understand your customers’ views, identify developing trends and make informed predictions, which can in turn contribute to areas such as product or service innovations and marketing.”

As you are developing your CX programme and selecting tools, be sure to keep this in mind. You want to implement a conversational AI solution that is not only built based on a deep understanding of your customers but will enable you to gather valuable customer data as well. You also want to ensure that you are properly analysing that data to assist with ongoing improvements to your CX and inform other areas of your business, such as product development and marketing programmes.

The customer insights that can be provided by chatbots and virtual agents are too beneficial to overlook when you are selecting a technology to implement. Consider this as you are reviewing conversational AI pricing options. Purchasing a chatbot without the right tools for data collection and reporting functionality never pays off, no matter how much money you might think you are saving. It is also key to work with a provider that has the expertise to assist you with mining and analysing the conversational data to maximise your benefit.

If you need some help cutting through the information overload when it comes to selecting a conversational AI vendor, check out the ISG Provider Lens™ Intelligent Automation – Solutions & Services. This report provides an independent, market-driven evaluation of the industry and comparison of 19 conversational AI providers.

Combining Chatbots and Voice for Omnichannel Experiences

By Liam Ryan, Sales Director

Last week Creative Virtual joined our partner Spitch as co-sponsors of The European Chatbot & Conversational AI Summit. The event was 100% virtual this year and featured two afternoons of various presentations, workshops, and panel debates. While being virtual is never quite the same as talking with someone face-to-face, it was great to see so many thought-provoking exchanges on the Discussion board and interesting questions asked by attendees during the sessions.

I teamed up with Gary Williams from Spitch to present on Day 1 of the Summit. Our session, The Omnichannel Solution: Chatbots + Voice, explored combining natural language chatbots with speech recognition capabilities to create powerful voicebot solutions. We shared some industry research from ContactBabel that showed 85% of CX professionals identified creating omnichannel/connected journeys as very or somewhat important to their strategies in the next two years (download the full report here). It’s no secret that customers want and expect an omnichannel support experience.

The tight integration of chatbots and voice creates a seamless journey as users switch between channels to help you deliver that connected experience. Gary and I shared two example voicebot use cases, one for customer support and one for employee support, that showed how the user could start a process on one channel and complete it on another in a smooth, seamless way.

For those interested in getting started with their own voicebot project, we ended our session with three important tips:

  1. Work with experienced vendors – Today’s market is crowded with new start-ups and inexperienced providers. You want to work with vendors that already have proven experience with both deploying and maintaining these solutions in your industry or sector. By partnering with experts, you immediately benefit from their experience. They can help you avoid common pitfalls, guide you on best practices, and ensure compliance with industry requirements and regulations.
  2. Select reliable technologies – This is why Creative Virtual and Spitch have partnered on voicebot solutions. We both bring years of expertise and documented results for each of our respective technologies. Be cautious about vendors that have attempted to tack on their own poorly developed chatbot or voice technologies to their main solution just so they can shout ‘Me too!’ You want technologies that are secure, can scale to current and future requirements, offer the hosting options you need, and will give you reliable results.
  3. Understand the integration options – When it comes to integrations, you need to first make sure there is a deep, seamless integration of the chatbot and speech technology to have a successful voicebot. Then consider what other integrations you are going to need to create a personalised user experience. You want a solution that can easily integrate with any existing content sources, backend systems, CRMs, other communication channels, etc. so that you can create a custom experience and connected journey.

If you’re interested in learning more about voicebots, schedule a demo to see these solutions in action and discuss possible use cases. You can also read more about the Creative Virtual and Spitch collaboration in our integration overview.

Thanks to Gary and Spitch for their event partnership and to The European Chatbot & Conversational AI Summit organisers and attendees for two days of great virtual content!

How Much Does it Cost to Make a Chatbot that Actually Works?

By Paulo Barrett, Chief Operating Officer

Ask any seller of a highly complex and customizable chatbot or virtual agent system about cost and you’re likely to get an evasive answer. ‘There’s no one-size fits all.’ ‘I’d need to talk to you on the phone to give you an accurate quote.’ Increasingly, in this ever-saturating market, it’s easy to find elements of chatbot pricing (i.e., API request fees) or flat monthly subscription costs for low-end systems, but who is giving the educated bot buyer a clear, top to bottom view of what it costs to build a system that will really work?

By ‘really work,’ I mean one that will materially contribute to cost savings, improve customer satisfaction, and maybe even generate new revenue. In other words, how much is it realistically going to cost to build a bot your customers will actually want to use.

The truth is, building a successful chatbot is not purely a question of technology. Whether you are buying a platform to BYOB, getting something cheap and cheerful off the shelf, or looking for a bot consultancy to support your internal efforts, your work is really just beginning once you have the system configured and deployed. The ongoing work to improve the chatbot’s performance and to get the best out of self-service in your unique deployment is what makes the difference.

It can be difficult to predict exactly what actions your customers will want to take in the beginning. That means being able to take an informational system and swiftly evolve it as desired customer outcomes become clear is key for success. This is enhanced by using great technology, of course, but ultimately, you need the right experts (internal or external) to separate your deployment from the crowd of others (often failures) which are flooding the support world.

Think of it like buying an instrument. No matter how expensive or special it is, either you learn to play it, or you get someone else to play it for you (alternatively, it ends up gathering dust and doing absolutely nothing for anyone). One way or another, this expert training costs time and money. You have to weigh this investment against the return.

Now to the million-dollar question … pun intended. What will a chatbot that your customers actually want to use cost for a large enterprise? While it’s true that most deployments are unique to every client and require some customization, there are some standard pricing building blocks you can expect to see.

The first cost to nail down is the pilot fee. How much am I gonna spend to test this thing out and see if it works for me? The financial risk associated with a pilot should be shared by the customer and the vendor and typically runs around $50,000 (USD). While the client assumes some risk via the initial cost, you should expect this to be credited against the cost of the full production-level deployment if you choose to move forward. This fee will cover all hosting, software deployment, content development, technical consultancy, and transactional fees for the agreed period. Typical pilots run 30-60 days from go live to give you enough time to see material results and make a decision about the ongoing plan.

Once you convert from pilot to full system (we pride ourselves on a +90% conversion rate!), you have some choices to make about how you pay for the tools and ongoing consultancy. Some customers wish to be purely pay-for-performance. Often, they go with a tiered model based on volume with session costs starting at a dollar (i.e., a single interaction with a user, with unlimited question/integration calls in that session). This per session cost may fall based on meeting certain volume thresholds. With any variable pricing model there are pros and risks for both the customer and the vendor.

If you prefer not to have a variable rate in your forecasting, you can purchase a more traditional software/services package. A standard production system should include integration with a live chat platform as well as your CRM. This will ensure your customers get personalized answers to their questions and are able to complete transactions with the bot online, rather than just receiving flat, informational content. The cost to provide the software and ongoing consultancy, along with an adequate knowledgebase of 100-200 solutions, will generally cost somewhere between $150,000 and $250,000 (USD) per annum, depending on the number of sessions.

While this may seem like quite the investment, you have to ask yourself: What is the cost of deploying a support tool that my customers don’t want to use and delivers a negative, frustrating experience?

Ready to learn more? Our team is always on hand to arrange a personalized demo with you and answer any questions you may have about getting started with your pilot.

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.

Harnessing Human and Machine During the Pandemic

By Rachel F Freeman, Operations Director

A direct quote of the explanatory theme for this Customer Service Week says: “The impact of events affecting the world today have changed the way in which companies and their employees engage with customers.”

Indeed this is true, and all of us in our businesses and in our personal lives can feel the effects of how services of all kinds have altered in ways ranging from barely discernible to completely different (filling out forms, having temperatures taken, tape and measurements of distance being assessed amidst a lot of Perspex dividers). A main thing that became apparent in call centre scenarios was that call wait times for an array of customer services were much longer and users still are advised in recorded messages that “due to Covid-19” call wait time may be impacted.

I can testify that I’ve never had to wait 25-30 minutes to speak to a representative for whatever service I needed before Spring 2020 but experienced that exact scenario at least four times in the past few months. Speaker phones have never been so handy so that one can do other tasks whilst being on hold for extended periods of time!

Cue the virtual agents, chatbots and virtual assistants. Now more than ever before it is a no brainer that online self-help tools that are available 24/7 should come into their own in this period of uncertainty and continued delays blamed on Covid. Self-help tools need not be subject to the same rules of quarantine which makes them more reliable when it is impossible to predict when humans will be available to handle and field queries based on who is in the office and who is self-isolating.

Now more than ever, in the spirit of seamless customer experience, let’s let the self-help tools do what they are designed to do. Let’s let them share the burden of the increasing pressure on call centre agents and take advantage of them working to their fullest potential. Let’s give the machines space to help, freedom to work whilst the humans that are healthy can spend time not only speaking to customers who truly need a human but also to check in from time to time on the accuracy of the responses of the virtual agent. A smart combination of self-help and human guidance creates confidence that the job will get done with the right tools.

We’re all being told to stay safe and be alert – so let’s work in parallel with the tools to help make that happen. We can enable more efficient customer service interactions whilst at the same time prioritising the health and well-being of both customers and employees.

Check out the Neutrino release of V-Person™ to learn how Creative Virtual is delivering some of the most up-to-date and seamless self-help tools available. Also download the ‘Conversational AI Trends 2020’ ebook from AI Time Journal for virtual agent success stories during the pandemic.

The way companies and their employees are engaging with customers may have changed significantly this year, but with the right tools a positive, seamless experience is possible. This Customer Service Week let’s celebrate both the people and the technology that are delivering safe and seamless customer support in this period of uncertainty.

Satisfy Your Curiosity About Deploying AI Virtual Agents and Chatbots

By Mandy Reed, Global Head of Marketing

Do you have a chatbot or virtual agent on your roadmap? Do you need to upgrade a poor performing self-service tool? Are you curious about successful use cases for AI-enhanced virtual agents?

If so, you’ll want to reserve your spot now to join Creative Virtual and Engage Customer for their upcoming webinar, Tips for Deploying AI Chatbots & Virtual Agents.

On Thursday, 4 June 2020 Chris Ezekiel, Founder & CEO of Creative Virtual, will join Steve Hurst, Editorial Director at Engage Business Media, for this live webcast. Through a series of live demonstrations, they’ll explore:

  • Best practices for deploying and optimising conversational self-service
  • Questions to ask when selecting a chatbot or virtual agent solution
  • Tips for using AI and machine learning to improve performance
  • Guidelines for implementing seamless handover to live chat
  • Current live use cases and results from organisations around the world

Advancements in chatbot, virtual agent and conversational AI technologies have made them a go-to solution for providing easy-to-use and cost-effective customer support on digital channels. Customers are becoming more comfortable with using self-service options and appreciate being able to get help instantly at any time of the day or night. Companies benefit from reducing demand on contact centre agents and improving their customer experience.

The realities of the ongoing global pandemic have placed an increased pressure on organisations’ digital channels, including their existing virtual agent solutions. For many companies, the flexibility and robustness of their digital strategy is going to play a key role in how they maintain and build customer loyalty during this time and in the future. Offering reliable self-service is an important piece of that strategy.

Register now for the webinar Tips for Deploying AI Chatbots & Virtual Agents to learn more. Can’t attend the live event? Don’t worry, a recording will be sent to all registrants after the webinar.

You can also request a personalised demo to see how Creative Virtual’s technology can help you deliver seamless, consistent self-service and improve customer loyalty.