There is ever increasing interest in the role emotions play when managing Customer Experience in the contact centre.
At the same time, there is a drive to introduce technology such as chatbots to make customer service teams more efficient; removing repetitive tasks and providing ‘always on’ customer service. These potentially conflicting trends are happening at a time when the demand for customer service is growing, and organisations are fighting to differentiate themselves through their customer service offering.
A recently commissioned study by Forrester Consulting suggested that 90 percent of customer service leaders agree personalisation is core to the future of automation, and existing chatbot technology is stalling their efforts. The key challenge is to build simple yet personalised experiences for customers.
As Maya Angelou famously said: “People don’t always remember what you say or even what you do, but they always remember how you made them feel.” If your chatbot or AI solution leaves the customer feeling frustrated or angry because they have to put in more effort to get the answer to what they perceive is a routine query or task, all that is being achieved is an increased chance that the customer will look for an alternative supplier who can make this task easier.
In addition, quite often humans want to talk to humans. A study by PwC found that an average 74 percent of non-US consumers want more human interaction in the future and that 59 percent of all consumers feel companies have lost touch with the human element of Customer Experience.
Certainly, there have been strategies employed whereby chatbots are being disguised as humans which can only lead to frustration on behalf of the customer when they find they are being deceived and the bot cannot fulfil their needs for a more emotional or complex issue response. While customer views are constantly evolving, I still think Userlike got it right with their view on avoiding the ‘uncanny valley’.
Organisations need to be up front when a customer engages with them by disclosing that they are talking with a bot, and take advantage of the benefits that can be gained when effectively deploying it for more routine and simple tasks. In addition, they need to give the customer the opportunity to seamlessly switch to a human agent, without the need for the customer to repeat themselves. In short, make it easy, make it simple and, when the customer is speaking to an agent, make it personal.
No one can deny that AI is getting better and better, and chatbots will certainly have their place in our future. A well-designed customer-centric journey will allow the bots to tackle low level tasks, but companies also have to be cautious in blindly launching bots into the contact centre eco-system. When poorly executed the effect upon customers can be detrimental to their overall experience. It’s all too easy to deploy a chatbot that can get stuck in a loop, resulting not only in an increased cost to serve but also a decrease in overall customer satisfaction.
Hockenbury & Hockenbury in Describing Psychology (1997) described emotion as “a complex psychological state that involves three distinct components: a subjective experience, a physiological response, and a behavioural and expressive response”. Delivering customer service for an organisation dealing with often highly emotive subject of money, we have yet to find an AI solution that can effectively replicate the human touch our industry-leading customer service team can deliver. They can handle the simple routine tasks well, but then so can a well-designed FAQ or Help Centre. Until such a time as when chatbots can manage all three psychological states, there will always be a need for humans.
Human agents have a big advantage. They understand compassion, they can demonstrate empathy and they have their own shared experiences of everyday life which continues to become busier and more stressful for us all. In having this unique skill set, the human agent is here to stay and will own the complex matters where a human touch is needed.
The recent Genesys Xperience19 conference in Denver, Colorado, saw some of the most exciting developments in Customer Experience technology showcased to an eager global audience, and in case anyone was under any illusion about the future of CX – it involves AI.
The tech itself is dispassionate, and can appear benevolent to users as it cheerfully helps them along their customer journey. However, decades of pulp sci-fi dystopia has left AI with an image problem – no matter how helpful it may seem, some simply cannot shake the idea that bots might someday pull a Hal 9000 and see humans as inferior and deserving of subjugation…or worse!
Such fears ought to be dispersed when one discusses the details of AI technology with the real intelligence behind it – someone like Olivier Jouve, Executive Vice President of Genesys Purecloud, perhaps the planet’s most popular contact centre platform.
Olivier took on the role of PureCloud EVP in 2017, having spent over three decades honing his craft in pioneering customer sentiment technology development, including through senior positions at IBM.
His impressive resume also reveals a stint as an associate professor in computer science at Leonardo da Vinci University in Paris, and today, with a 150-strong AI team under him, Olivier is one, if not the world’s foremost authority on AI and its ability to make our journeys as customers easier.
He knows, in detail, how much his tech helps us in our lives – often without us realising it – but still the idea that AI will have a negative impact on humanity can cloud the vision and judgement of some sceptics who see it as an evil overlord-in-waiting.
Fresh from a timely Xperience19 breakout session on AI Ethics, Olivier took time out to chat with Customer Experience Magazine about his work, its reputation, and just how much AI is used for the betterment of our lives as consumers.
Speaking of the “creepiness factor” that some associate with AI, its access to personal data, and how it could be used in the wrong hands, he describes why being open and honest with customers, and letting them see the advantages with their own eyes, is the best way to go.
“We want the customer to know that we respect their data, and we need them to see what data we are using, so they are able to opt out if they so wish,” he explains.
“In the way we build our products, we do a lot of design thinking with customers to understand where the limit is. You know, what type of data they are comfortable with.
“And of course, you are being careful not to introduce any bias, which is something that’s very complex – not using any gender, or lifestyle, race…whatever, that could turn your model into something that is going to be targeting a specific minority.
“This wasn’t on the table 15 years ago when we were already scoring contact centres for next best action, cross-selling, up-selling, and so on, and using that data. Now there is much more sensitivity about how you use the data, and I think that’s actually a good thing, as it forces us to be clear from the get-go.”
Olivier highlights that those who are creeped out by an AI’s use of data, to the point where they will walk away from it, are a small minority compared to those who see the benefits and remain loyal to brands brandishing the tech.
“Companies which use AI the right way will enjoy great benefits, by being fair and respecting privacy,” he adds.
A common cause of ‘creepiness’ is the notion that a customer is unaware if they are interacting with a human or a bot on their journey with a brand, but as Olivier sagely states, that uncanny valley effect is being superseded by good old fashioned customer satisfaction when the AI does its job – and does it well.
“Me, personally, I don’t care if it’s a bot, as long as I get what I want, quickly, and with a great experience,” he continues.
“I don’t think customers care as much about the technology they use as much as the experience they have. I do think we should disclose that it’s not a human though – that should be part of the disclaimer. But at the same time, I don’t see that as something that should be discouraging people, who may think ‘oh no I’m not talking to a bot as I won’t get anything from it’.
“That’s also a danger of going to market too quickly with AI tech – some chatbots don’t provide the right experience. There are, however, things chatbots and voicebots can do very well, and I think we should double down on those.”
As Olivier points out, it’s not as if customers aren’t already used to interacting with bots on a less ‘intelligent’ level already.
“When someone asks for the balance of their bank account, they don’t care if it’s a human giving it to them, so people are already used to this sort of automation. We just have to be careful that if we go deeper with more complex things that users don’t get the feeling we are not responsive.
“People like empowerment, and chatbots can be great for that. But there are still some limitations, so we are not yet at the stage where AI is going to replace humans. We have chatbots that are very specialised and do things very well, but we need to find the right moment where you have to hand over to a human.”
Yet will there be a day when there is no human to hand over to? Will we fleshies be redundant in a future where all the work is being done by bots?
“I don’t think it will replace humans, as we are putting humans into something they are really good at, and so I see that more as a collaboration between AI and human – something we call blended AI. We can do sentiment analysis automatically, but it has limitations,” Olivier replies.
So what are these human skills that we can still feel superior to the bots on, and that customers still desire on their journeys? What’s the key difference that currently keeps humans in contact centre customer-facing roles?
“Empathy – we aren’t there yet,” says Olivier.
“Humans are great at it, and we need to think of the overall CX, the CX we want to provide. AI does things a human cannot do because you could not integrate all the different insights you have about a customer, but AI is really good at that.
“However, to take the conversation to the next step, at some point currently you have to hand over to a human. Of course, even humans need to be taught empathy in some cases!
“Perhaps in 10 to 15 years we will be able to train AI better in applying empathy, but for now that’s why we need this combination of human and technology.”
Ok, enough of what humans can do better than bots! It’s time to let Genesys genius shine, as Olivier outlines exactly why today – not years from now – AI is simply superior in most non-emotional ways to humans when it comes to steering customer journeys and earning the desired end result – superior Customer Experience.
“Our products work on finding the best agent for an incoming call or interaction, something we do very very well thanks to machine learning. The AI is understanding what the topic of the interaction is and uses historical data and a sophisticated decision tree to move the interaction forward.
“We want to optimise the customer journey, so we have a solution called predictive engagement. We can look at what a user is going to do on a website, view their navigation, and see at which moment he or she might need some help, and decide what the best outcome is for this customer.
“Once you have this interaction you can develop additional models which could be for retention or selling – more things we do very very well that a human couldn’t match.
“When you do next-best action and you have a customer calling who is ready to leave, our tech knows if you go for a specific action, there’s an 85 percent chance that this person is going to remain as a customer, for example.
“That’s from crunching a lot of data, gained through similar situations, and handling so much data – well that’s not something a human can do.”
Other than the aforementioned empathy, does Olivier feel his AI is lacking in any other areas that might be beneficial to overall CX?
“I think what AI does not do very well yet is go deeper into the conversation,” he tells me.
“We see breakthroughs when we look at things like Google Duplex, where, you can find yourself questioning if you are interacting with a real human or not, but an AI able to handle 100 percent of complex interactions? I don’t think we are there yet, though we are making a lot of progress.”
Despite my impatience as a customer to know when exactly this will be possible, Olivier sensibly refuses to give a date.
“I don’t like giving predictions, but I see how fast we are moving forward. I think Duplex was really a breakthrough – suddenly you see something and you think ‘wow’ – the voice, the type of interactions…it’s all very human.
“I don’t think it’s about developing the technology now – it’s about the right data and making it accessible. All of that is moving at an exponential speed. What’s really accelerating AI is that everything is in the cloud. Every single interaction from the employee or customer’s side – all that is feeding our AI platform. The more data we have, the more we are going to be able to power the customer journey.”
In the midst of such dazzling tech capabilities, it can easy to forget any regulation necessities to protect data and ensure AI is used for the good of humanity.
“It’s our responsibility to propose how we want to be regulated. It’s the right time to do the right thing,” adds Olivier
“Over 30 years I’ve been through a few AI ‘winters’, where AI had been at peak hype, but then died. I don’t want this one to die because some people are not responsible, so I will do whatever I can to make sure we are doing the right thing.
“There remains a fragility to this whole sphere, caused by the actions of Cambridge Analytica for example, which rocked people’s confidence in AI and data use, but I believe what we are developing at Genesys is promising, and beautiful, in a way that will not kill the hype this time around.”
Artificial Intelligence (AI) plays an important role in Customer Experience, marketing, and personalisation; It has the power to generate predictions about what goods and services customers are likely to want, when the demand will arise or propensity to switch will occur, and which platforms they are most likely to purchase on.
As a result, AI has become critical for brands wanting to improve their capabilities to offer personalised experiences, offers and recommendations. What’s more, marketers should not overlook the importance and the business case for investing in AI technology to deliver high-quality personalisation at scale.
Personalisation is key to customer loyalty, customer experience and increasing sales, with Accenture recently finding that 91 percent of European and American consumers are more likely to shop with brands which provide relevant offers and recommendations. Clearly, enhancing a brands ability to engage with customers on an individual basis is critical for brand success.
However, investment alone is not enough – in order for AI to provide effective personalisation, it must be implemented and used in the right way.
Organisations need to develop more sophisticated AI capabilities which can collect and analyse data in real timeto offer tailored services and products. This capability must be advanced enough to work for customers as they move through an omnichannel journey which often spans across websites, apps, email and high-street stores, for example.
While it is true that AI has the potential to bring about this ‘new era’ of personalisation, the technology alone cannot guarantee quality personalisation. For that, business leaders must appreciate the value of AI, develop a clear strategy for implementation and ensure that it is monitored and improved by experts who truly understand it.
Make the business case for investment
One common barrier to the adoption of sophisticated AI and machine learning technology is business leaders being deterred by the cost of the initial adoption process. While it’s true that AI can remove the manual, time consuming, and often overwhelming challenge of managing and understanding vast amounts of data, just like any new technology, the initial set-up process can be expensive and labour intensive.
Also, the skills required to implement this level of technology mean that organisations may face the added time and expense of employing dedicated data scientists, and adjusting towards a culture where marketers and technologists must work closely together As a result, organisations may feel that there is not a viable business case to invest.
To counter this point of view, take a step back and consider the long-term benefits of the initial investment. If AI is implemented strategically, the future pay-off will be enhanced capabilities for personalisation, improved Customer Experience, and increased sales.
Even as far back as 2014, McKinsey found that maximising customer satisfaction, which today largely comes from offering personalised experiences, would result in a 15 percent increase in a brands revenue. More recently, research from Econsultancyfound that 93 percent of companies see an uplift in conversion rates from personalisation. Together with a well implemented AI strategy, brands can personalise even more effectively and potentially see even greater conversion rates.
Develop a clear strategy first
It is important to understand that simply having AI and machine learning capabilities does not guarantee that a brand can offer a higher quality of Customer Experience. In order to see significant improvements, organisations must first decide what CX problem they are aiming to solve, which data sets they need to collect and monitor, and how they are going to use the data to remove the particular pain-points that customers face.
Whether a brand wants to convert more website views to purchases, increase the number of customers returning to the site, offer a smoother transition across different touchpoints, or improve online self-service, these priorities must be decided from the outset. Then, the right data can be collected and harnessed to address the issue.
With an overwhelming amount of data being generated and collected by companies today, this is an effective way to streamline efforts and ensure the most important issues are dealt with first.
Shoe retailer Footasylum provides a great example of the benefits of strategic AI implementation. It focused first on the specific pain-point of friction in the customer journey between stores and the web by using AI to link in-store purchases with online systems such as loyalty schemes, to create a single customer view. The brand can now predict which customers are most likely to purchase particular products and when. As a result, it has seen an 8,400 percent return on ad spend. Footasylum’s next mission is to breathe life back into the high-street by using AI to enable the web to automatically share valuable customer information with brick and mortar stores.
Lay the foundations for advanced AI
In order to get a good understanding of which CX problems to address first, brands should undertake background research with marketers identifying which personalisation processes are currently creating the most conversions online, and which are less successful.
Another important foundation is to ensure that all data sets are integrated and consolidated. In order to offer recommendations in real time, brands must be able to predict consumer needs and use data to meet them at the right moment, on the right platform. AI can be used to accurately forecast where the customer will be in their decision making. Without access to all of the data about any given customer, there will always be a limit to how successful these predictions can be.
In conclusion, it is key to remember that although AI has great potential to offer tailored experiences for customers in real time, the initial investment does not automatically guarantee quality personalisation and a return on investment. For that, a solid foundation must be put in place by understanding where customer experience can be improved, deciding on a clear strategy for implementation and removing data from silos.
Then, AI has the power to offer personalised experiences which offer true value to customers and meet, or even exceed, their expectations.
Genesys hasintroduced new orchestration capabilities powered by AI that connect native and third-party technologies to enable the most comprehensive customer journey management available today.
Currently, businesses are adopting an increasing number of artificial intelligence (AI) point solutions to solve specific challenges. However, businesses are failing to realise AI’s full potential to improve customer and employee journeys because data remains fragmented across the end-to-end experience. As a result, AI’s ability to impact business outcomes remains limited.
New orchestration capabilities from UK Customer Experience Awards sponsor Genesys make it possible for multiple AI applications to work together harmoniously in real-time from marketing to sales to service. By leveraging all relevant data throughout the customer’s entire journey, Genesys AI can orchestrate, measure and optimise processes at every touchpoint. This enables businesses to tailor automation, communication channels and marketing and sales offers for individual customers, introducing new levels of personalisation.
AI innovation at your fingertips
Genesys makes it easier for businesses to flawlessly connect and manage native and third-party AI across voice and digital channels. With its simple centralised orchestration, Genesys AI enables customers to map complex business logic, perform various back-end system integrations and swap AI providers.Businesses can move their AI technologies into production quicker by building once and deploying across all channels, leveraging microapps to reduce development time by 90 percent and improving analytics, resulting in 40-60 percent faster time to value. This enables businesses to leverage existing AI investments and buy a future-proof solution.
Both on-premises and cloud customers around the world are realising additional advantages. An example is Entel, one of the largest telecommunications companies in Chile. In just six months, Entel has increased revenue by five percent, decreased costs and improved customer satisfaction by using Genesys AI to orchestrate all customer interactions with technology from Google Cloud and IBM Watson.
Other Genesys customers, such as DNB, are achieving additional benefits including improved accuracy leading to better predictions and faster responses to customer inquiries. In speaking about the benefits of this advanced orchestration capability, DNB Head of Technical Operations and Customer Solutions, Anders Braten said: “Genesys sews everything together to make the perfect customer journey.”
Breaking down AI silos to realise value
“In customer service alone, on average, nine out of 10 enterprises deploy AI for six distinct uses, such as automated self-service, chatbots in instant messaging and IVR support,” said Peter Graf, Genesys Chief Product Officer.
“Genesys AI is an elegant solution that masterfully links underlying technologies and synchronizes data and event streams as needed. These AI capabilities are delivered by Genesys Cloud, the company’s high-velocity innovation platform that provides new ways to optimise customer and employee journeys.”
With hundreds of technology applications integrated with its Customer Experience platform today, Genesys is the only company in the industry able to orchestrate any AI for self and assisted service. This includes Kate, the customer and employee virtual assistant powered by Genesys AI, as well as third-party AI solutions such as Amazon Lex, Google Cloud Contact Center AI, Nuance and IBM Watson.
Dan Miller, lead analyst at Opus Research, said: “Genesys has stepped up to provide a framework for enterprises to support conversational engagements that helps businesses leverage existing investments in AI resources more fully. Genesys AI enables them to integrate natively developed elements of AI along with offerings from recognized, leading third parties.”
How Genesys AI orchestrates the cest Customer and Employee Experience
Genesys AI provides the common data framework for all AI integrations so systems are not working in silos. It captures, processes and analyzes third-party data in the same way as its own AI applications, such as Genesys Predictive Routing, Altocloud Predictive Engagement, and Automated Forecasting and Scheduling. In addition to delivering advanced orchestration, Genesys AI enables real-time predictions, speech and text analytics, self-service automation and more.
An example is the coordination between Genesys AI and chat and voice bots. When a customer begins an engagement with a bot, Genesys AI can detect if escalation is needed. It can then use Predictive Routing to identify the employee deemed the best match and pass the inquiry to that individual with full context for resolution.
Advanced AI orchestration kicks off summer innovations
The company announced its new orchestration capabilities at Xperience19, its signature event taking place this week in Denver. Genesys is also introducing a new analytics dashboard, enabling businesses to better understand customer intent, visualize containment rates and optimize bot usage in a single view.
The new dashboard and Genesys AI’s advanced orchestration capabilities are available now among a broader collection of the company’s Summer Innovations.The Innovations are comprised of multiple feature enhancements across the GenesysPureCloud®, PureConnect™ and PureEngage™ solutions and delivered via Genesys Cloud.
The ability of artificial intelligence (AI) to grasp morality and empathy are among concerns expressed by customers when it comes to interacting digitally with brands.
The lack of trust in AI has been revealed by Pegasystems Inc. and research firm Savanta, who surveyed 5,000 consumers across the globe. They found that many don’t understand the extent to which AI can make their interactions with businesses better and more efficient, while one-in-ten said they believed AI cannot tell the difference between good and evil.
The suspicions on morality seeped into customers’ overall opinions on brands, with 68 percent believing organisations have an obligation to do what is morally right for the customer, beyond what is legally required.
Sixty-five percent don’t trust that companies have their best interests at heart, raising significant questions about how much trust they have in the technology businesses use to interact with them. Less than half (40 percent) of respondents agreed that AI has the potential to improve the customer service of businesses they interact with, while less than one third (30 percent) felt comfortable with businesses using AI to interact with them.
Just nine percent said they were “very comfortable” with the idea. At the same time, one-third of all respondents said they were concerned about machines taking their jobs, with more than one quarter (27 percent) also citing the “rise of the robots and enslavement of humanity” as a concern.
Over half (53 percent) said it’s possible for AI to show bias in the way it makes decisions, and 53 percent also felt that AI will always make decisions based on the biases of the person who created its initial instructions, regardless of how much time has passed.
Meanwhile, just 12 percent of consumers agreed that AI can tell the difference between good and evil, while over half (56 percent) of customers don’t believe it is possible to develop machines that behave morally. Just 12 percent believe they have ever interacted with a machine that has shown empathy.
The results of the survey coincide with plans by Pega to “improve empathy in AI systems”, and speaking of the poll results, the firm’s VP of Decisioning and Analytics, Dr Rob Walker, said: “Our study found that only 25 percent of consumers would trust a decision made by an AI system over that of a person regarding their qualification for a bank loan. Consumers likely prefer speaking to people because they have a greater degree of trust in them and believe it’s possible to influence the decision, when that’s far from the case.
“What’s needed is the ability for AI systems to help companies make ethical decisions. To use the same example, in addition to a bank following regulatory processes before making an offer of a loan to an individual, it should also be able to determine whether or not it’s the right thing to do ethically.”
He continued: “An important part of the evolution of artificial intelligence will be the addition of guidelines that put ethical considerations on top of machine learning. This will allow decisions to be made by AI systems within the context of customer engagement that would be seen as empathetic if made by a person. AI shouldn’t be the sole arbiter of empathy in any organisation and it’s not going to help customers to trust organisations overnight. However, by building a culture of empathy within a business, AI can be used as a powerful tool to help differentiate companies from their competition.”
The Barbican’s newest exhibition, AI: More than Human, is an artistic exploration of the possibilities thatmodern technology presents, examining the diverse potential of artificial intelligence (AI).
A particularly striking installation is MakrShakr, a robotic bartender which can mix cocktails for customers via an online pre-order system.While undoubtedly a fun gimmick, the introduction of AI into a traditional service role raises important questions about the future of our restaurants, cafés, and bars.
The food and drink industry is no stranger to new technologies, and the latest developments are an evolution of sector staples like the sushi belt and fast food self-service machines.However, the gradual move towards AI presents unique new challenges.Principally, to what extent can automation really reflect Customer Experience value generated by humans in what is an intrinsically personal sector?While few would argue that real employees can ever fully be replaced, increased automation should come with a few health warnings.
Choosing the right persona
Finding the right persona for an AI system is the first step to ensuring customers actually enjoy using it.It’s important to have a welcoming interface, but this can be quickly undermined if the technology doesn’t work as it should.Successful AI personalities like Alexa and Siri are approachable and lighthearted when the situation dictates, but they’re primarily programmed to be as helpful as possible so people can find what they want quickly.
In the service sector, making the interface fun and playful is especially important, but there also needs to be a level of emotional intelligence present for when things go wrong.Investment in self and situational awareness so that customers feel their needs (and frustrations) are understood goes a long way.For voice services this means ensuring bots recognise emotion and intonation when customers speak.And where the technology isn’t voice based, a simple on screen message – for example an apology in the case of slow service – makes technology feel as attentive as humans would be in that situation.
This isn’t to suggest AI can ever replicate the value ofexisting employees, who will always be the major drivers of high quality CX.Instead, AI should complement staff, freeing them up from administrative or procedural tasks and allowing them more time to engage qualitatively with customers and build brand loyalty and retention.
Upselling is a major part of successful service businesses – everything from ‘do you want fries with that?’ to making sure diners have dessert and coffee at the end of a meal.For AI, this represents both a challenge and an opportunity.Making these transactions appear conversational and informed is key; just think of the persuasiveness of a genuine recommendation from a well-read employee at Waterstones compared with the ‘frequently bought with…’ pop-ups seen online.
Like finding the right persona, successful upselling relies on engaging customers, showing awareness, and demonstrating genuine knowledge.Recommendations should be presented as being bespoke to specific customers, not just based on the habits of other people.
Keep it fresh
Multiple conversations with the same person do not feel like the same experience over and over again – and interactions with automated services should be just as refreshing.Where an AI uses voice, this might mean mixing up the repertoire and programming varied responses to common questions.For others, different aspects can be kept fresh.In the case of our robot barman, making sure the menu is regularly updated to encourage people to come back for more will engender regular customers.
At the time of writing, the Barbican’s robot barman has already temporarily closed because of technical issues – proving that the museum exhibition is a long way from the reality of frontline customer service. It is inevitable that automation will become more widespread, we just need to make sure that the consumer, not the technology, remains king.
Ask the leadership of any reasonably-sized company what technology they’re looking to implement and they’ll almost invariably mention artificial intelligence (AI).
In theory, that’s great, because AI has the potential to fundamentally change the way a businesses operates and creates a great Customer Experience. The longer the business uses an AI application, the better the experience should get. Given enough time, the system can collect enough data on each individual customer to provide meaningful, hyper-personalised experiences.
Implemented badly, however, AI can be a total disaster. Rather than feeling like the business they’re dealing with cares about them, they’re left with the impression that customer service has been handed over to a bunch of dimwitted machines.
Let’s talk about chatbots
The easiest way to illustrate how varied the AI experience can be is to look at chatbots. They’re the kind of front-facing AI that more companies are using and which an increasingly large body of customers are familiar with. Trouble is, most companies are terrible at implementing chatbots.
Apart from a few forward-thinking exceptions, companies tend to put a chatbot on their website in the hope that that it will learn from each interaction it has with a customer and that its answers will become more nuanced over time. They also operate in the belief that customers will tell the chatbot when it’s wrong, helping to train it further (hands up if you’ve ever done this willingly).
That would be great…if the chatbot was actually equipped to do so. However, for the most part, chatbots are simply going through the company’s existing knowledge bases and serving you with a document (or, in the worst cases, multiple documents) to try and help. It’s essentially a slightly smarter form of search.
As anyone who’s tried to use the search function on a corporate website will tell you – that’s not particularly helpful, especially when you’ve got a specific query. Let’s say that I want to know if I can insure my sunglasses. I don’t want to have to scour through insurance agency documents to try and figure out the answer. I just want the answer.
Contextual, hyper-personalised, relevant
As long as chatbots rely on a flawed architecture that depends on the existence of relevant documents containing the needed information, they won’t be able to provide that answer.
If you’re going to use AI to improve CX, you need to take a different approach. If you want to operate in the digital era and want to drive logic through data then you need to start it in data. That means looking beyond your existing documentation and CX architecture and integrating insight into customer behaviour across digital and offline channels.
This approach will, ultimately, allow you to offer customer support that is hyper-personalised, relevant, and compliant.
A chatbot built on this kind of framework understands what you’re asking and can answer specific questions according to what you actually need. While that’s just one small part of CX, anyone who’s cursed a company for failing to provide useful information, will know how important it is.
The aim of AI
That said, this approach shouldn’t be limited to chatbots. Consistency – in style, tone, and content – is one of the most important factors in successful CX.
It’s therefore imperative that any organisation turning to AI to improve CX apply a data-first architecture across every customer-facing channel. So, whether I make a query using a chatbot, the search function on a website, or a call centre, I should get the same – relevant – answer.
However, if this is going to happen, businesses need to stop trying to bolt AI onto their existing architectures and take an approach that allows it to reach its full potential.
Large majorities of British consumers prefer dealing with humans over automated services for everything from querying a bill (85 percent) and changing account details (62 percent), to making a complaint (84 percent), buying a product or service for the first time (77 percent), chasing an order (73 percent), or dealing with a fault (78 percent).
These are the findings of an online YouGov survey of more than 2,000 British adults commissioned by CX firm Webhelp.
Nearly half of respondents (45 percent) said they had never used any type of AI, but amongst those who had there was widespread dissatisfaction around its efficacy and perceived value. Nearly half (44 percent) also believe that AI will not positively impact their lives in any way over the next five years.
Just over a quarter of respondents said they had used a customer service chatbot (27 percent), interactive voice response or IVR (27 percent), or smart home speaker such as Amazon Alexa or Google Home (26 percent).
Whilst over a third of those who had used these types of AI were dissatisfied with the chatbots (35 percent) and IVR (38 percent), smart home speakers proved more popular – possibly because these are chosen rather than encountered by chance. Fewer than half (45 percent) of those who had experienced a customer service chatbot were satisfied with it and 38 percent were either fairly or very dissatisfied with IVR. In contrast, 77 percent claimed to be satisfied with smart home speakers.
Looking ahead five years, over a quarter of respondents (26percent) felt that increased use of AI-driven Customer Experience tools would make interacting with companies “much worse” compared to only 19 percent who felt the impact would be positive. Other negative perceptions include fear that AI will make dealing with brands/companies more impersonal (52 percent), increased threats to privacy and security (46 percent), and detrimental impact to human-to-human interactions (43 percent).
Webhelp CEO David Turner said: “We know from anecdotal evidence that human-to human contact is important, but this study goes even further, highlighting the degree to which people favour it over AI-powered customer service tools and are negative about AI’s potential future impact.
“As exposure to AI increases in day-to-day life, people are likely to become more receptive, but this research confirms the importance of striking the right balance between the advanced technology services we offer and the incredible human talent of our local teams of agents, advisors and planners. Our approach will always be customer experience driven, so this window into consumer perception is extremely valuable for helping our clients implement AI solutions which offer clear end-user value.”
New research among British businesses examining employees’ attitudes toward digital transformation, innovation, and cutting-edge technologies such as Artificial Intelligence, reveals confusion about the true meaning of ‘digital transformation’ and a high degree of scepticism about their employers’ appetite for digital innovation.
The research, conducted by YouGov amongst employees at 500 businesses with 50 or more employees, on behalf of Cherwell Software, reveals that 57 percent of employees don’t know the correct meaning of ‘digital transformation’: 20 percent of respondents could not hazard a guess at its meaning, and 12 percent thought it meant moving to a paperless office.
This research focuses on the view from the workforce itself and its findings go a long way to explain why the 2018 Dell Digital Transformation Index placed the UK in 17th place in its adoption of digital transformation, lagging way behind emerging countries like India, Brazil, and Thailand.
In a further blow to the image of UK businesses, the survey highlights a reluctance to adopt cutting edge technology. According to the survey, just nine percent of businesses are viewed by their workforce as being digital innovators, whilst 64 percent of employers only take on new technology after it has become widely available.
“It’s obvious that not enough time is being devoted to communicating with employees to develop their understanding and involvement in the process of digital transformation,” said Oliver Krebs, Vice President of EMEA sales for Cherwell.
“Unless business leaders bring their teams along with them on this journey British organisations are likely to fail and our ability to compete in the global market place will be severely compromised.”
Mixed reaction to Artificial Intelligence
Meanwhile, reactions to adoption of AI in the workplace were mixed: 34 percent of employees were confused (five percent), threatened (21 percent), or saddened ( eight percent); 20 percent were optimistic (16 percent) or excited (four percent); and 30 percent were intrigued – suggesting once again that leadership teams have not effectively communicated and engaged their team in the adoption of new technology.
Central to the success of most digital transformation projects is ensuring a consistent and integrated approach to the use of processes and data across all departments. Yet the survey reveals that just six percent of businesses’ data and processes are very well integrated across all departments, and 42 percent have not integrated inter-departmental data and processes well.
Andre Cuenin, Chief Revenue Officer at Cherwell said: “The research demonstrates that UK businesses still have a lot to learn in terms of planning and implementing digital transformation and their adoption of new technologies like artificial intelligence if they want to shed their image of digital innovation followers. The deep level of confusion and miscommunication amongst employees must be addressed by industry leaders.
“This may be due to the fact that digital transformation is frequently pigeon-holed as an IT issue, whereas in reality it should be seen as an initiative that involves everyone across the business, from the board, down to the most junior employee.”
Artificial intelligence (AI) systems spending will reach $5.2 billion (£3.9b) in Europe this year – a 49 percent increase over 2018, according to International Data Corporation’s (IDC) Worldwide Semiannual Artificial Intelligence Systems Spending Guide.
AI solution adoption and spending are both growing at a fast pace in Europe, where companies are moving beyond experimentation to the actual implementation of use cases. In fact, 34 percent of European companies have already adopted or will have adopted AI by the end of this year across a wide variety of use cases, according to IDC’s European Vertical Markets Survey 2018–2019. By 2022, European spending in AI will reach $13.5 billion, reflecting fast-growing interest in AI technologies.
Andrea Minonne, Senior Research Analyst at IDC Customer Insight & Analysis in Europe, said: “Many European retailers, such as Sephora, ASOS, and Zara, as well as banks such as NatWest and HSBC, are already experiencing the benefits of AI – including increased store visits, higher revenues, reduced costs, and more pleasant and personalised customer journeys. Industry-specific use cases related to automation of processes are becoming mainstream and the focus is set to shift toward next-generation use of AI for personalisation or predictive purposes.”
Matt Hooper, SVP at customer communications specialist IMImobile, added: “It’s encouraging to see automation and Customer Experience driving increased investment in AI. Automation is key to achieving significant operational efficiencies and delivering proactive, end-to-end customer communication – yet most companies are only touching the tip of the iceberg. Currently, very few companies are truly automating customer communications end-to-end, as a result of data being spread across different business systems and the complexities of integrating NLP and AI capabilities.
“In many cases, at some stage in their journey, customers are either required to change communications channels, interact with a different department, or simply wait days for a transaction or interaction to be completed. For companies to fully realise the benefits of automation and AI, they need to build and have visibility into the end-to-end customer journey. Only then can they drive proactive two-way customer communication.”