Digital Experience platform Contentsquare has acquired Israel-based experience analytics company Clicktale, creating a combined entity serving 600 enterprise clients globally.
Contentsquare is used by UK retail brands including Dreams, Clarks, and Moss Bros, while Clicktale has clients such as Dell, RBS and T-Mobile, and the new partnership means they now serve 30 percent of the Fortune Global 100.
The acquisition follows another by Contentsquare just last week when they purchased price optimisation and merchandising solution Pricing Assistant.
Jonathan Cherki (pictured), founder and CEO of Contentsquare, said: “The combination of Clicktale and Contentsquare heralds an unprecedented goldmine of digital data that enables companies to interpret and predict the impact of any digital element – including user experience, content, price, reviews and product – on visitor behaviour.
“Increasingly, this unique data can be used to activate custom digital experiences in the moment via an ecosystem of over 50 martech partners. With a global community of customers and partners, we are accelerating the interpretation of human behaviour online and shaping a future of addictive customer experiences.”
Shlomi Hagai, CEO of Clicktale, added: “Contentsquare and Clicktale are exceptionally compatible. By combining our resources, we unlock the next level of digital experience success for our customers.”
The current conditions for UK high street retailers are far from favourable.
Not only are they battling market pressure and challenges from ecommerce competitors, but also increasing rents and tough trading conditions. To ensure survival, retailers today must keep their finger on the pulse of all the latest technological advancements.
What businesses must remember is that as technology advances, so do customer shopping behaviours and expectations. We are already starting to see more and more businesses implement chatbots, artificial intelligence, and messaging apps to keep up with demand. We are in a time where consumers have never been more vocal on their wants, and this is highlighted with the results of our research.
Our data showed that in order to satisfy customer needs organisations have to offer a variety of channels in which to engage with – 81 percent of respondents demanded this. Consumers not only want choice but also, a seamless, integrated experience across all of them. Taking this one step further, many consumers are wanting Augmented Reality (AR), Virtual Reality (VR) dressing rooms and even drone delivery, to be a possibility.
Termed as “technologies of the future”, large, online and in-store retailers are already reaping the benefits of AR and VR in an attempt to make the customer journey more immersive and engaging. For instance, IKEA, has introduced Amazon’s AR view to help customers visualise how furniture will look in their home before making a purchase.
For customers who prefer ‘ease of use’, these new technologies couldn’t be more perfect as they allow consumers a chance to ‘try’ before they buy. As well as convenience, AR and VR are helping stores to stand apart from the traditional retailer. L’Oreal Paris, for example, guarantees loyal customers with an in-store virtual makeover tool that enables you to try make-up and certain looks before buying. On paper, it has never been so simple for retailers to deliver a more engaging and convenient approach to Customer Experience.
However, AR and VR are not the only new inventions transforming the CX landscape. Increasingly, we are seeing chatbots being used as a more convenient way for customers to interact with brands, specifically when they require assistance. In fact, 87 percent of businesses say self-service customer enquiries are a current priority of theirs.
Apart from the obvious benefits like saving businesses money, self-service chatbots are improving CX and satisfaction. It’s fair to say we have all had our share of agonising waits and frustrating calls with agents and can therefore, understand the appeal of having access to instant help and real-time information.
In the age of GDPR and data sensitivity, customers are very particular about who they give their personal data to. With this in mind, retailers must remember to be upfront about who or what they’re speaking to. Giving customers the option to self-serve will only succeed if you’re as transparent as possible.
Ultimately, although traditionally we associate a human touch with CX, retailers that do not adopt the latest technologies and integrate them into the customer offering jeopardise losing the loyalty of existing customers as well as potential new ones.
However, before businesses embark on this digital transformation, they must remember not to run before they can walk. Implementing chatbot technology initially can be just as effective as implementing technologies which are grabbing the headlines, such as AR and VR.
Consumers these days expect a hyper-personalised Digital Experience, from cosmetics and fashion brands to consumer goods, online marketplaces, and even video streaming services.
Personalisation has become a focal point for user experience design and, when executed smartly, can be a differentiator for a brand’s Customer Experience. Personalised user experiences can build brand loyalty and drive sales, as well as producing extremely insightful data for brands to evaluate and re-imagine their UX design. A smart personalised experience should allow users to complete tasks in a faster, easier, and more enjoyable way.
However, creating a personalised user experience can be complicated. A combination of data, research, and technological knowhow is needed, plus the vision and creativity to create something that engages and delights users. Here are a few things to consider when starting out with personalisation or re-imagining an existing user experience.
Users today are digital-savvy and constantly connected, across a plethora of devices. To succeed in providing a consistently pleasing user experience, businesses have to improve the interactions they offer via every channel. This is the way to provide a more intuitive, sophisticated, and personalised relationship with their customers.
Digital consumers expect real-time responses and transactions with minimal effort, and access to compelling experiences that have been personalised for them specifically, and the only way to generate these interactions is through utilising data. Brands need to create data-driven strategies to target their audience with relevant, timely content to generate conversion and interest. But data is only useful if it is interpreted the right way.
In theory, every brand that sells directly to consumers has the potential to access the same data as their competitors. Where brands can differentiate is by creatively connecting the dots that this data provides. This is how the ‘magic’ is created. It’s a blend of logic, imagination, and brand values, and connecting the dots to find the story.
Quantitative data is a starting point, then it takes a bit of intuition via qualitative data, human behaviour, brainstorming, and creativity to create the magic and lay out the storytelling needed to make the journey happen.
Research firstly helps you understand if your brand actually needs personalisation. If yes, where should it be applied? And how much is enough? User research helps comprehend what matters to your users, what are their limits in terms of over-use, and if what you are doing and creating is relevant to the variety of your brand’s audiences.
Essentially, personalisation is not the silver bullet for every brand, every audience, or every interaction. User research will help divulge where and how it can be applied most effectively.
Test and repeat. This is as critical as the research step and is the only way to understand if your personalisation application is ready to drive sales and brand engagement – by testing. It needs to feel seamless.
Practically, this means it is simple to use on their device of preference, and clear what the objective is. An experience is ruined if users spend a time feeling confused, frustrated, or consider another option. Any type of personalisation will take you a step towards providing a frictionless experience. Hyper-personalisation should be almost unnoticeable.
Despite the fact consumers are becoming more accepting of organisations using data in a positive way, brands still need to be prepared demonstrate to users how they are obtaining and using their data. It’s a two-way street. In exchange for data sharing, brands are exploring innovative ways to deliver personalised, valuable moments across various touchpoints to customers that will make their experiences easier and more fun.
And to develop these experiences, brands need to understand how customers view the brand across all touchpoints. This understanding will allow a platform for brands to connect with their customers on an emotional level consistently across various touchpoints. Because of the explosion of customer interaction points, across channels and devices, the key for brands is to manage the entire journey, not simply individual touchpoints. And the secret is delivering a consistent experience across all channels.
6. Don’t be creepy
Personalisation is about context. It’s effective if brands serve up the right content at the right time for the right person, and creating a contextualised and personalised experience consists of knowing why personalisation is important and how it can help your users. In short, if a user is given a positive, timely, helpful experience, it shouldn’t feel creepy.
Imagine you’re walking past your favourite shoe shop. You get a push-notification that the sneaker you checked out online last week is available in-store at a discount for a limited time only, and available in your size. That’s peak personalisation – and it’s a positive experience.
Now personalisation is more commonplace, users are educated and so more accepting of personalisation. Brands need to be able to gather contextual data and segment users into target areas. Every user is different, and what some people may find uncomfortable, others may think is helpful or fun. For positive personalisation, knowing and segmenting your users is the key.
7. The future
8. Who’s doing it well?
Amazon is an obvious choice; it would be hard to write about personalisation without mentioning Amazon, as its use of personalisation is widespread around their site (recent orders, previously watched videos, recommended items based on previous purchases, etc). Research indicates that Amazon drives 35 percent of its revenues through its personalised product recommendations.
Another example is Thread, which built its brand around personalisation, delivering hyper-personalised recommendations at scale. Thread’s free ‘personal stylist’ takes visitors through a survey to understand body type, colourings, tastes, and budget. The stylist then provides ‘hand-picked’ recommendations, delivered through personalised emails – usually a link to a curated list of items alongside a personal message.
Despite providing ‘hand-picked’ recommendations for over 650,000 customers, Thread actually employs fewer than 10 stylists. Obviously, personalisation algorithms are hard at work behind the scenes. Recommendations are generated via user data analysis, and emails are segmented by location, or what the weather is like, to resonate with customers. A handful of ‘stylists’ are used to face up the front end, making the experience feel super-personal.
The vast majority of CIOs find integrating new communications with legacy systems a challenge.
That is among the findings in research carried out by global cloud communications software provider, IMImobile, which discovered that 92 percent of CIOs faced this issue. This comes at a time when almost all (98 percent) CIOs feel under pressure to deliver the Customer Experience expected by both customers and the wider business world.
Businesses are increasingly expected to respond with the same level of speed and consistency whether using email, SMS, Facebook Messenger, or new channels such as WhatsApp Business. However, more than half (52 percent) of CIOs admit they are unable to provide a truly connected and integrated customer communications experience across all channels and business systems.
Asked to consider the major barriers they face when it comes to delivering frictionless CX, CIOs cited legacy IT systems (51 percent), data being spread across multiple systems (51 percent), and budget constraints (42 percent), as the top three blockers to progress.
Aseem Sadana, EVP at IMImobile, said: “It is widely known that the ability to innovate and improve customer communications can make or break a business. Worryingly, the research lays bare the gap between the experience customers now expect, and what businesses are currently able to provide.
“The challenge is that delivering great Customer Experience is easier said than done. This is especially the case for large consumer facing enterprises, where fragmented, legacy IT environments make integrating new communications channels and processes very complex. Many of them also have data that is spread across multiple systems, with programmes and processes varying from department to department. CIOs must consider a centralised platform approach to orchestrate and automate communications across existing business systems and communications channels.”
A new study shows that Brits are quick to complain online following a bad ecommerce encounter.
The survey of 2,000 UK customers by retail operations platform Brightpearl found that almost a third of shoppers have left a negative review online, with nearly seven in 10 having done so in the last year. Seventy-six percent of those surveyed will also share a negative retail experience with someone else they know to warn them off a particular brand.
In the digital age, consumers are quicker to take to social media or online review sites to share their anger or dissatisfaction, but even those who don’t vent wish they had.
Fifty-five percent of Brits are yet to leave a negative review of a company online, but the same percentage regret missing out on the opportunity to air their grievances with the brand or retailer when they’ve had a poor shopping experience.
Derek O’Carroll, CEO of Brightpearl, said: “Brits are famously awkward and averse to confrontation and complaining, but, with the rise of so many avenues for customer feedback, from online forms to social media, those habits appear to be changing. Consumers have started exercising their right to have a moan when they receive sub-par service – and brands need to start paying closer attention.”
The research reveals that online consumers are becoming more reliant on the feedback of other shoppers to support their decision making.
Forty-six percent of respondents regularly check star ratings for online retailers before buying from them, and two-in-five consumers have been put off a brand or a retailer they might have shopped with – by a single unfavourable review.
Thirty percent of shoppers do look more favourably on retailers who actively respond to negative reviews posted about their services online.
Meanwhile, 55 percent admit they would also be likely to spend more money with an online outlet which had ‘excellent’ reviews or star ratings. Brits believe they would be willing to spend as much as 22 percent more with a brand or retailer which has received mostly ‘excellent’ reviews than one which has been reviewed less favourably.
However, on average, UK customers want a brand or retailer to have a whopping 30 positive online reviews before they’d trust it enough to part with their cash, and anything rated below four out of five stars is generally considered negative by discerning consumers – with shoppers becoming highly dubious about shopping with any brand that has more than five negative reviews.
“From our research, it is clear that a positive review – or 30 – can make a huge difference in the choices consumers make when it comes to selecting a brand or retailer,” Derek continued.
“It is also important for retailers to be aware of the wide-ranging impact a negative review can have on their business, as well as understanding where those problems are coming from – whether it’s items not arriving on time or at all, to lack of delivery updates or cancelled purchases. Customers pay attention to middling and lower reviews, resulting in lost sales opportunities and potentially damaged reputation. The best approach to negative reviews is to identify and fix the issues that can lead to unhappy shopping experiences.”
Have you been the victim of chatbot incompetence recently?
It typically starts with a specific query that you need help with. You don’t have the time to listen to the contact centre’s hold music, so you turn to the company’s much vaunted chatbot.
It seems fairly straightforward. You type in your question and press enter. The chatbot comes back with a list of completely unrelated content links, and asks if any of these solve your problem. ‘No’ you say.
You retype your question, hoping this time it’s a little clearer. Again the chatbot cheerfully responds with a new list of possible ‘helpful’ articles and FAQ links, and mentions that it is busy learning and is grateful for your help. It will get more accurate the more people engage with it.
Oh, so your diabolical customer experience is all for a good cause – to train their chatbot! The cheek of it.
After a third attempt, you notice a link that may be relevant. You click on the link and are taken to a three-page document providing generic product information. The assumption is that you will take the time to read this document and then work out the answer yourself. With raised blood pressure, you click on the ‘Connect me to an agent’ link and hope that possibly they may have the knowledge needed to solve your query. Sometimes they do, sometimes they don’t. That’s how it goes with so many omnichannel customer journeys these days.
I must confess I expected more. I envisaged that by now we could engage with chatbots that are capable of diagnosing my specific issue, and then offering me a relevant response that results in a relevant action. In other words, a chatbot that is not simply an over-hyped digital assistant that can execute basic instructions or offer me links to possible content matches. I had in mind an digital advisor that could operate at the level of an expert – one whose intelligence is defined as much by the relevance of the questions it asks as the answers it finally offers.
If you talk to most AI companies, their chatbots already perform like digital experts. They will refer to their amazing natural language understanding and incredibly intelligent algorithms that are powered by ‘machine learning’, ‘deep learning’, and ‘neural nets’. They will give you the sense that all you need to do is point their technology in the direction of your knowledge base and the digital advisor will magically onboard all your product, policy and procedural expertise. Then, with just a little bit of guidance, you can soon have trained your chatbot into a digital Einstein that can change your customer service offering forever.
When you ask them to show you a working example, they will probably show you one of their canned demo’s – built off a scenario where the source data is in rich supply, the use case is clearly defined, and the user script can be carefully followed. As a result, their chatbot’s conversation will feel so intelligent, so human-like, that you will feel you simply have to have one.
Just don’t ask them mid-way to type in something unscripted and to upset their crafted storyline! I am certain that you will be quickly informed that they have not managed to train this chatbot to cover all contexts, and that this is simply used for illustration purposes.
The real reason is that it is all really a digital mirage. It looks so achievable until you shift your eyes down to your current position, and suddenly the mirage vanishes. There are a number of reasons for this:
Companies seldom have the quality of data needed to accurately train a customer facing chatbot
Most companies operate in a world of legacy systems, limited integrations, poor quality data, and poorly documented internal policies and procedures – the very things that cognitive systems depend on to build their engagement accuracy.
A customer support chatbot is powered more by prescriptive than predictive logic
To understand the difference, ask Siri or Alexa for an answer based on available information, and they can usually give it to you. For example, if you ask: “What is the weather looking like tomorrow in London?”, you will be amazed how accurate the answer is. That is because the information exists, and thousands of people have already asked the same or a similar question. The patterns are thus established and the correct answer can be predicted.
However, try ask a question that requires more context before answering. Say: “What is the best home loan for me?”. You will probably notice that the response will be to offer you possible links to companies offering loans. It won’t begin by understanding your needs. This is because a financial need analysis is driven off a diagnostic set of prescribed logic. There is no answer yet – the problem still needs to be understood.
In regulated environments, you need to be able to prove your chatbot asked the right questions and offered the right advice
Where a chatbot is powered by predictive logic – the logic you need to train and that keeps ‘learning’ based on multiple engagements – you will find it will struggle in a regulated environment. This is because the logic is designed to change and adapt, based on user engagement. It is also hard to prove how a decision was reached, as each recommendation is made in what is often referred to as a ‘black box’. This is hugely problematic when you are offering customers advisory support in a regulated environment, such as banking and finance.
Context matters, and the way most companies capture prescriptive logic lacks context
Prescriptive logic is typically captured using documents (knowledge bases) or decision trees (process flows). It’s how we have trained employees brains for decades and it’s how we are trying to train our chatbots. So just like giving staff exercises to learn how to apply the formula to different situations, we get teams to train the chatbot, telling them when they are right and when they are wrong. The problem is that documents and decision trees are not able to capture all the possible scenarios. They can only describe a few. And as a result, the more variables you need to consider in order to offer a customer accurate, relevant advice, the harder it becomes to achieve.
The good news is that there are now digital platforms available that allow you to achieve the holy grail – a chatbot capable of asking me context relevant questions that then lead to relevant answers and actions. These platforms have been built off data-powered, prescriptive logic that can ensure your customers are offered a consistent, compliant and context-relevant digital engagement, one that leads to a successful customer service outcome every time.
These platforms have acknowledged that not all logic should be predicted, and that for customer support chatbots the foundation of the logic has to prescribed. The trick is ensuring it is also contextual, and these platforms have now managed to do this in a way that can be maintained effectively.
The dawn of chatbots capable of offering customers consistent, compliant and yet highly context-relevant customer engagements is upon us. And it’s about time, too.
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.”
New business models for public transport in the UK will result from a digital revolution in the mobility industry, a new report has predicted.
Global digital transformation firm Atos has launched its Digital Vision for Mobility report, which sets out how digital technology has transformed the UK’s transport sector and considers the role of AI, automation, and blockchain in determining the mobility solutions of tomorrow for road and rail, broader public transport, and logistics.
Contributions from ITS-UK, Google, Siemens, KPMG, Worldline, TfL, MyTaxi, and TechUK explain how data is being used as a driver for intelligent infrastructure and how developments such as IoT can be strategically deployed to create more reliable services and more convenient access for transport customers.
The report’s release was marked with a keynote address by Atos UK & Ireland SVP for Strategy & Communications and former Transport Advisor to the Mayor of London, Kulveer Ranger, to an audience at University College London.
“Increasingly with population growth and denser metropolitan conurbations, we see the need to support the mass movement of people and goods with efficient, effective and integrated multi-modal public and personal transport systems,” he told attendees.
“Transport operators are beginning to rely heavily on data: harvested both from within their own networks and systems and from the personal mobile devices of individuals. To realise a vision of truly personal mobility, vast amounts of data will need to be aggregated. This will be a huge technological feat for innovative integrators and digital architects.”
Speaking of the launch of the report, Adrian Gregory, Atos Senior Executive Vice President and CEO, UK & Ireland, said: “More change is now underway across the transport and logistics industry than at any time since the invention of the combustion engine. Vastly increased computing power and hyper-connectivity are helping to transform the operation and maintenance of vehicles and national infrastructure.”
Retailers are being warned that a lack of preparedness for new EU regulations to prevent online fraud could be costly.
The Strong Customer Authentication (SCA) rules will come into force in September as part of the Second Payment Services Directive (PSD2). They will affect online purchases of €30 or more, and will require retailers, banks and payments providers to authenticate customers through something they “have”, “are”, and “know”.
While banks are largely ready for the changes, retailers have been warned that they face trouble ahead, as a recent survey by analysts at 451 Research and Stripe found that less than half of businesses polled expected to be ready by the autumn deadline.
Uncertainty over the UK’s future in the European Union is also adding to pressure on retailers facing major legislative changes while simultaneously being told to expect Brexit on October 31.
Among those urging retailers to address the issue is digital solutions firm Mitek, whose EMEA MD Rene Hendrikse said: “Sooner rather than later, retailers must recognise the need to invest in anti-fraud technologies. With the new anti-fraud rules, every customer will have to be authenticated by at least two of the following criteria: something they have, something they are, and something only they know.
“Come September, this will be necessary for every online transaction. This could include an ID document, a biometric identifier, and a security question, going beyond simply your card details as is the current standard. This introduces an additional layer of security to defend against the threat of fraud from online transactions – but it also presents a challenge for organisations to implement with only months to go.
“Within the next few months, investing in the right technologies and implementing them quickly and efficiently should be top of the agenda for retailers and e-commerce groups. If not, they will find themselves in serious trouble.”
Nearly three quarters of marketers and CX professionals (74 percent) are investing in Digital Experience (DX) in an effort to foster long-term loyalty and build better relationships with their customers.
Research from experience analytics company Clicktale, which surveyed 200 marketing and CX professionals across the US and UK, found customer loyalty to be the number one priority for those building a DX strategy. This was followed by a need to understand customer behaviour (67 percent) and a desire to create a clearer Customer Experience vision (67 percent).
For those at a managerial level (CX and marketing managers) improving customer lifetime value was also identified as an important driver of DX strategy.
Speaking of the findings in Clicktale’s Defining Digital Experience report, the firm’s CEO, Sara Richter, said: “As ever more customer interactions are completed via digital channels, marketers find themselves faced with a ‘switching economy’ – in which consumers regularly flit between different brands when they’re dissatisfied with a particular experience. Given this fact, is it any wonder that so many marketers are looking to secure long-term customer loyalty through their Digital Experience approach?
“To achieve such loyalty, however, we as marketers need to think about what it is that our customers need, and to do that requires a strong understanding of customer behaviours. This is where the other key objectives come into play. In order to drive loyalty, marketers must improve their digital experiences. But to do that, they must have a clear vision and the behavioural data needed to back it up. None of these factors can exist in isolation – they must all form part of a single, unified DX strategy and be supported with the right behavioural technologies.”