Recruitment has never been an easy task, regardless of which industry is facing the challenge.
Difficulties in finding the right people, at the right time, with the right skills, is something all organisations encounter. One such industry is contact centres. Outsourced contact centres are extremely people-focused, meaning that it’s imperative to get the recruitment process right from the offset and meet the challenges faced head-on.
In a contact centre environment, there is a need for recruiters to not only meet seasonal demand, but to be able to find the right person for each position, focusing on retaining employees that are skilled, motivated and committed to the role. A successful contact centre will find, train and retain staff that can meet customer expectations and work to make sure teams have the right attributes to properly represent the organisation they work for.
However, there are numerous outsourced contact centres getting recruitment right, and by following a few simple steps, recruiters can build a successful recruitment strategy that gets it right every time.
Staff on demand
Numerous industries are known to face issues with peaks and troughs of demand, but one that certainly suffers the most is retail. With huge seasonal spikes throughout the year – Black Friday, Christmas, Valentine’s Day, Easter – this industry understands what it’s like to see a huge rush of customers that can vanish as quickly as they appear.
To cope with these hectic periods, it’s essential for organisations to be confident that the recruitment channels being used will reach the right people, quickly and effectively. Advertising locally on buses and billboards, for example, can be more targeted and help to enhance brand recognition for an organisation looking to seek local Customer Service Advisors, as an addition to online.
Additionally, contact centre organisations need to prepare for these peaks by working closely with their customers to understand when the demand might rise and fall, and what levels of staff will be needed accordingly. By reflecting on busy periods of the past, recruitment teams can work in harmony with marketing teams to figure out what works, what could change and then put a plan in place for the next peak time.
Talking the talk
Contact centres have undoubtedly evolved. Just look at the name; what was once referred to as a call centre has grown to become much more. The omnichannel world that consumers now live in means they expect to receive the same customer experience, regardless of which channel they use – whether it’s social media, a phone call, email, online chat, or through instant messaging. They expect answers instantly, and they want their queries answered or issues resolved in as few steps as possible.
Because of this, the skill sets required of Customer Service Advisors has also changed. Advisors now need to be proficient in communicating across a variety of channels, utilising strong written and verbal communication skills to make the experience as seamless as possible for the customer. This eclectic way of working means that Advisors need to be flexible, adaptable, and able to multi-task, providing the same, exceptional experience with each customer interaction. A coherent selection process will ensure that recruitment teams are finding the right people for the job.
Capturing brand personality
When it comes to the selection process, this not only needs to be tailored for each job role, but also for each brand – this is the very nature of an outsourced contact centre. Each organisation that is represented by the contact centre will require something different, and this shouldn’t just come through when the Customer Service Advisors are answering queries; it should start at the beginning of the recruitment journey.
Recruitment teams should actively work with the client to build the job description, which should then underpin the selection process. Recruitment strategies should also be tailored for each brand to find the most suitable people; who are the organisation’s target market? How do they communicate? Can brand advocates be chosen to ensure the Customer Service Advisor has a genuine interest in the brand? This ensures the brand’s personality can be captured in each customer interaction, through style, tone of voice and language used.
The recruitment journey
Developing a CX strategy starts with recruitment. With the end customer in mind, a recruitment strategy can be developed that ensures the right team is sourced and trained in line with the organisation’s requirements. Recruitment doesn’t have to be a challenge; a clear understanding of the organisation’s values from the outset is a simple way to get the journey heading in the right direction and, coupled with the right approach to customer service, means that contact centres can commit to delivering an exceptional CX, every time.
Today’s consumers want it all – freedom to research purchases using any device (66 percent), the ability to visit stores if the internet doesn’t meet their needs (49 percent), and personalised advertising offers (26 percent) – all as part of a seamless, integrated experience.
Businesses recognise these rising demands; globally, almost two-fifths (34 percent) plan to adopt an omnichannel model in the next year. Yet meeting this goal can be challenging. Ensuring consistency, convenience, and relevance requires a comprehensive view of individual journeys: insight that isn’t easy to obtain when shopping activity is highly fragmented.
With CX rivalling price and product as a factor that matters most to customers, it’s crucial for retailers to understand the always-connected consumer by adjusting their measurement approach.
The troubled status quo
Most retailers are already striving to keep up with convoluted consumer journeys: using siloed, channel-specific tools and metrics to assess the impact of online and offline marketing efforts. And these silos are only getting deeper, especially when cookies are becoming less effective, privacy regulations are imposing stricter requirements on data, and walled gardens are preventing meaningful insights into the consumer journey altogether.
As a result, retail marketers are left with fragments of insight they must attempt to piece together, making it increasingly difficult to gain a complete view of how individuals connect with their brand across touchpoints. Little wonder only seven percent of firms have successfully implemented an omnichannel approach. Clearly, measurement must evolve to match modern consumer habits. If marketers want a precise picture of where purchase paths flow, how their initiatives perform and what form strategy should take, they need the right measurement solutions at their disposal.
Making the right measurement choice
Modern marketing measurement approaches can pave the way to better customer engagement; giving retailers the means to analyse interactions across every channel and device, evaluate the impact of each touchpoint on sales, and power smarter future decisions. But different measurement models serve different needs, which means retail marketers must select the approach that matches their data, channels and goals.
For example, marketing mix modelling harnesses summary level data to provide a holistic understanding of what’s driving sales, including online, offline and external factors that can affect product demand. It looks at the historical relationships between marketing spend and business results, and is most valuable for retailers who want to inform their strategic and periodic planning on an annual, half-yearly, or quarterly basis.
In contrast, methods such as multi-touch attribution offer more frequent, granular analysis. Leveraging household and person-level data from addressable channels, it measures the influence that each touchpoint – from ad creatives and offers to placement, keyword, recency and so forth – has on consumer actions in near real-time. For retailers looking to make tactical optimisations to live campaigns, multi-touch attribution is likely to be the best option.
Comprehensive media coverage matters
It goes without saying that marketing measurement relies on a steady and comprehensive supply of data. The more complete the coverage, the more accurate the analysis will be. But amid the growing emphasis on data security, media coverage gaps are increasingly common.
Measurement providers must therefore be chosen as carefully as the models, and maximum coverage should be a top priority. Finding a partner that has strong relationships with large media platforms, ways to track data despite cookie limitations, and methods to cross-check the accuracy of data sources is key for getting as much visibility into the omni-channel consumer journey as possible. Only then can retailers dissect the complex web of factors that affect consumer decisions and make smarter, more impactful decisions.
The value of preparation
One final and often overlooked aspect of successful measurement is preparing for the future. In the wake of the General Data Protection Regulation (GDPR) and an increasing focus on digital security, the utility of cookies has significantly diminished – and with the e-Privacy Regulation (ePR) due to be enforced in 2020, its value is only set to fade further.
This makes it critical to choose a provider with the resources and ability to adjust to the ever-changing marketing landscape. Declaring intent to plan for a cookie-less world isn’t enough; providers should also be proactively demonstrating their commitment to future proofing marketers’ measurement success.
As consumer preferences for multichannel shopping grow, it’s becoming increasingly difficult for retailers to make sense of the fragmented data they leave behind and understand true marketing effectiveness. Instead of siloed tools that are at odds with the needs of always-connected consumers, retail marketers need a modern measurement approach so they can drive performance to the maximum and put their marketing investment where it matters most to their businesses.
When it comes to Customer Experience, “omnichannel” has grown to be one of those inescapable buzzwords.
So, what does the term mean, exactly?
HubSpot’s definition states: “Omnichannel experience is a multi-channel approach to marketing, selling, and serving customers in a way that creates an integrated and cohesive customer experience no matter how or where a customer reaches out.”
The “integrated and cohesive” aspect is probably the most crucial element of the definition. Another major point is the fact that the experience must be the same “no matter how or where a customer reaches out”.
You might say: “Great! My customers can buy my product or service on different channels and my marketing team sends out communications in more than one way. I’ve already mastered the omni-channel approach.”
Not so fast.
OmniChannel vs Multi-channel
Omni and multi-channel are two entirely separate approaches.
Multi-channel involves reaching customers in a variety of ways, be it in-person, online via websites and social media, or on the phone. This approach is designed to unify sales and marketing processes. In other words, you’re providing customers with many opportunities to engage. It’s not necessarily about aligning all the different channels; it’s simply making them available.
Omnichannel, on the other hand, takes the “multi-channel” approach one step further. Both digital and physical channels are merged to create a single, cohesive, and seamless brand experience. The distinctions and separations between different channels disappear. Think of it as the more “customer-centric” option out of the two formats.
A customer might begin communicating with a brand representative via live chat like Facebook Messenger or an on-site chat platform. Once the conversation evolves to a more advanced stage, it can then move to direct email or even phone conversations, retaining all the context of former conversations.
Beyond that, experiences a customer has with a brand in-store or on-site are preserved and then carried on to other digital channels. Social media reps communicating through DM, for instance, might be able to see that the customer they’re talking to has visited a local store. In an omnichannel system, complete customer histories are easily accessible. During the brand “conversation”, the customer should never have to repeat themselves.
This kind of cross-platform strategy can also be referred to as an experiential marketing campaign. You’re building an entire conversation around the experience itself, which spans not just multiple platforms but multiple talking points, as well as digital and physical interactions.
Why are omnichannel experiences so important?
Back in 2014, Gartner predicted that over the next two years (by 2016), 89 percent of companies had expectations to compete mostly on the basis of Customer Experience. That prediction was for three years ago. CX is now a differentiating factor.
When it comes to CX, without a solid understanding of omni and multi-channel concepts, business leaders are setting themselves up for disappointment.
Since an omnichannel approach is customer-focused, it means that the mindset has to be developed foundationally, starting with company culture and radiating outwards. Executives and management should set the example, with support trickling down to the service reps on the front line.
Omnichannel should be the main goal of a business’ entire digital strategy. In fact, it is one of the most crucial elements of modern digitisation, or the company’s digital transformation.
Creating a brand hub
Of course, an omnichannel approach isn’t possible unless the company brand has consistency. The message, voice, and overall user experience must feel part of the same “conversation”.
Many organisations are taking notice, consolidating their digital presence by building “communities”. Eight-one percent of companies already have an online support community in which customers can ask other customers for technical help and troubleshooting. Online communities that offer mobile and desktop experiences, shopping, social networking, learning, and even entertainment such as games are becoming the go-to brand destination. Consider that 77 percent of companies believe that an online community significantly improves brand exposure, awareness, and credibility.
Now that you understand the difference between omni and multi-channel experiences, and why they matter, it’s important to spread the message within your organisation. You simply cannot afford to put off adopting these customer-centric approaches. Find a way to incorporate them in your current processes and strategies, or else you’ll find your organisation is unable to compete.
In today’s increasingly tech-driven society, customer expectations on the speed and convenience of interactions with businesses have never been higher.
In every sector, companies are undergoing a process of digital transformation to ensure they deliver seamless experiences to the consumer. Often, the key to success lies in powerful use of data to simplify, personalise and transform customer journeys.
The value of simplification
By reducing the time and effort of interactions, organisations enjoy higher engagement, while meeting customer expectations and driving their own efficiency. According to the Aberdeen Group, 51 percent of firms use at least eight channels to interact with customers, highlighting the importance of delivering the same message seamlessly across all touchpoints to create a truly omnichannel experience.
Data-driven technologies facilitate this process by sending the right content via the right channels in a quick and automatic way. In insurance, simplification efforts have included replacing lengthy quotation forms with ‘No Questions Asked’ propositions, challenging perceptions of an industry laden with complexities.
Personalisation is key
Once a “nice to have”, tailored offerings have become imperative to business success. Nowhere is this more relevant than the insurance sector, where a survey by Accenture found 80 percent of customers are looking for personalised offerings from their car, home, or life insurance providers.
As vast amounts of data become readily available, organisations are using personalisation on a granular scale never seen before. Customer profiling is a powerful tool to gain competitive advantage in this area; by integrating data from a range of sources, whether demographic information or past purchasing behaviour, firms are able to serve up relevant content at the right time. By making the customer feel valued, businesses are driving loyalty and, it is hoped, repeat custom.
The power of digital transformation
The advent of new technologies such as voice, chatbots, and artificial intelligence, has empowered organisations to expand their service offerings and enhance the customer journey. The voice revolution in particular is gathering momentum and has opened up the possibility of bots replacing people to provide customer service 24/7, particularly to deal with routine queries and transactions.
According to Vxchnge, 20.4 billion devices will be connected to the Internet of Things (IoT) by next year, with consumer demand showing no signs of slowing down. As a result, firms are able to gather an increasing amount of data on Customer Experience, enabling them to make constant improvements to their products and services. For insurance, this has led to the development of proactive propositions, such as mobile phone apps that use image recognition, and Wi-Fi network scanning to generate a quote with minimal consumer input.
The commercial benefits
A recent study by PwC found 65 percent of people believe Customer Experience is important when choosing between buying options, highlighting the significance of investing in this area. As this figure rises, data will become increasingly relied upon to deliver effective modern strategies – Gartner predict over 40 percent of all data analytics projects will focus on Customer Experience by 2020. If done successfully, firms themselves will experience a plethora of benefits, including greater insights, improved conversion and increased revenues.
Whichever sector you’re operating in, it’s clear that those who recognise the value in providing customers with an excellent experience will do well. Make sure you’re one of them.
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.
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.
In theory, it has never been easier for consumers to communicate with your business…but are the choices suitable and easy to access?
Today’s consumers demand instant, fast, on-the-go interaction with companies, which is why web chats, texts, and social media have fast become many people’s preferred way of ‘talking’ with a brand. We live in a multi-channel landscape where real time responses are the norm and public conversations on social media can make or break a brand and its reputation.
Multi-channel contact centre solutions enable companies to manage different forms of communication by routing them via a single engine and delivering them to a correctly skilled customer service agent in the shortest possible time. Such advances in communication technology are to be welcomed as they enable contact centres to manage the flow of information and prioritise those interactions that require an urgent response.
The very nature of multimedia contact centres means employees are required to deal with a number of forms of communication, enabling a smooth and consistent customer experience to be delivered.
As the ‘face’ of the business, agents can make or break a customer relationship. Adaptability has become a key quality so they can demonstrate the values of their business regardless of the channel being used. The ability to write appropriately and clearly for different channels is vital.
Modern agents are multitaskers who can handle more than one customer interaction at a time – without causing delays to responses. Historically they have been hindered by multiple applications running on separate systems. Today it is possible to use one user interface to manage multiple mediums of communication.
A modern, reliable solution coupled with thorough training means consumers are now able to interact with an agent who is not flustered and can stay in control of multiple interactions. Regular monitoring of the interaction volumes and quality of consumer experience for each channel should ensure that the training requirements are identified and provided.
This measurement – including recording and reporting across all interactions – enables businesses to develop and improve their Customer Experience. In addition, multichannel contact centres can deliver cost benefits such as dealing with social media alongside voice, emails, web chats and text.
Standing still is not an option. The emergence of robots and automated messaging is reducing the burden on contact centres by responding to routine enquiries. Research shows there is growing interest among organisations in Robotic Process Automation (RPA) tools which can help businesses improve the efficiency and effectiveness of their operations.
Deloitte says that multiple robots can be seen as a “virtual workforce – a back office processing centre but without the human resources”.
Other researchers argue that RPA actually frees up employees to deliver skilled and creative work, suggesting that robots and humans are most effective when working together.
Slow service is enough for more than half of British customers to ditch a brand, according to a new survey.
A poll of 2,000 UK consumers revealed that 56 percent would stop shopping with a brand that forced them to endure slow customer service. The survey by contact centre cloud solutions provider 8×8 also found that almost two-thirds (64 percent) of people have been frustrated at the length of time it has taken a customer service team at a company to solve a problem.
The time it took to get through to someone is the most common reason people lose patience with a customer service team (36 percent), followed by having to wait to get their query resolved (30 percent). Quick and easy access to contact information is also a key factor, as a quarter (25 percent) have lost patience by having to wade through too many screening questions in order to access contact information.
When asked about the types of businesses they are most likely to lose patience with, customers named utilities and telecom firms in the top spot (33 percent), followed by retail (24 percent), and local government (21 percent). This suggests that organisations in these sectors are at the greatest risk of losing customers to slow service.
To help them get an answer in the quickest and easiest way possible, 78 percent of Brits expect companies to provide multiple channels to contact their customer service team on, such as phone, email, web chat, and social media. Despite this, over half (58 percent) of businesses still only offer one communication channel to contact customer service teams – an experience 52 percent of Brits find frustrating.
Mary Ellen Genovese, MD of European Operations, 8×8, said: “We all expect companies to deliver a fast and joined-up response to our queries regardless of their nature. Our research reveals speed is everything – consumers have little patience for slow service and, when frustrated, won’t hesitate to take their business elsewhere.
“Businesses that don’t meet customer expectations risk losing out to faster competitors, not just over established channels such as phone and email, but across web chat and social media too.”
The research also reveals that customers expect traditional channels to deliver a faster response rate. When asked which customer service platforms they lose patience with the most, 37 percent said phone, compared to just 12 percent for email and 10 percent for live chat.
We often hear about customer service being increasingly used as a business differentiator, but what does this really mean?
After all, customer service comes in many guises and means different things to different people. Some people simply want fast service at the right price while eBay devotees revel in the thrill of the auction without speaking to another human being. In general, speed and efficiency are all that matters, together with regular text or email updates of delivery dates and guarantees that credit card details are secure at all times.
On the other hand, consumers looking for support with complex, confidential, or emotionally sensitive matters would soon lose faith or be truly offended if they were treated as just another transaction on an endless conveyor belt of products. Adding agility to improve service levels is nothing new, but how often do we hear about businesses creating a kinder Customer Experience to stand out from the crowd?
Ombudsman: Bringing kindness to customer interactions in the real world
A kinder Customer Experience is a concept that Puzzel customer Ombudsman Services, the leading private dispute and resolution service, understands intuitively and shared at our Get Connected conference last year. Since the beginning of 2018, Ombudsman has practically re-invented its QA framework by deploying speech analytics in the contact centre to record 252,000 calls across all sectors. The organisation has successfully used voice recognition technology to capture 80 different phrases sorted into 12 categories. This established that nearly 30 percent of calls relate to dealing with someone in a vulnerable position, for example coping with mental health issues, losing their health or jobs, or just trying to stay warm.
The technology provides valuable insight into each call and caller, and strategically spots trends that identify the top issues facing all UK customers today. These powerful insights are essential to helping agents truly understand real-life consumer situations and as a result, respond with empathy and kindness as well as offer practical advice.
3 ways to create a kind Customer Experience
With a few simple strategies, every organisation is capable of winning customers over through efficient, yet kind, conversations. Here are three ways to get you started:
1. Have the right team on your side
Kindness starts from within and it starts from the top. Hire leaders who show dedication to building positive contact centres where agents care for each other as well as for their customers. Look for agents who combine passion with compassion. These are the ones who intuitively understand a customer’s emotional state then use this knowledge to solve customer problems in a highly personalised and meaningful way.
2. Overcome the fear of new technology
Introducing new technology can be an exercise of winning over hearts and minds, especially when people have faith in their traditional ways of working. What’s more, by its very nature speech analytics has a strong element of ‘big brother’ and can strike fear into the most confident employees. Overcome resistance to change by highlighting the undoubted benefits of automation. For example, accurate recording of calls that liberates language and empowers agents to engage more effectively with customers while providing high levels of transparency to build trust with each other and with customers.
3. Use knowledge to build a circle of continuous kindness
Understanding your customers’ requirements now and in the past is the first step towards treating them with kindness. Combine traditional resources of FAQs on websites with the use of chatbots to grow knowledge bases by feeding back useful information based on customer enquiry patterns. Add predictive analytics to tap into past resolutions, to support similar scenarios in the future and pre-empt issues before they become real problems. Then combine with speech analytics to highlight proactive opportunities for kindness.
The latest cloud-based omnichannel contact centres integrate seamlessly with speech analytics technology to analyse and search 100 percent of recorded customer calls in real-time, helping them to glean valuable intelligence from thousands – even millions – of customer calls quickly and efficiently.
Highly sophisticated, today’s technology can even identify dialects, regional accents, and slang in addition to detecting the usual keywords and phrases over multiple time periods. Innovative ‘TellMeWhy’ features also help organisations quickly identify potential underlying root causes for specific calls. This all-important data should be added to the knowledge base as part of a vital circle of continuous improvement and shared learning.
In today’s retail world we are emerging into a new era where technology and commerce are joining together and revolutionising Customer Experience.
Retailers are increasingly continuing to implement new technologies which help to improve processes. Alongside this they are also finding innovative and new applications of existing technologies which help to optimise daily operations. This can be due to the rise of online and mobile shopping, which has further led to increasing competition within the retail sector. With over 2,400 stores disappearing on the high street in 2018 alone, meaning a 40 percent rise in store closures from 2017, it is clear that this could be causing major panic amongst various retailers.
With item-level RFID technology rapidly gaining adoption in the retail industry, retailers have seen their inventory management improve significantly. Nowadays, retailers are looking at additional ways to leverage investments they put into RFID, especially once the initial investment and returns have been established. As a result of this, retailers are mostly focusing on the changing process of customer engagement at Point of Sale (POS) moving to an automated and human-free checkout.
Reduced shrink and reduced out of stocks
Item-level RFID technology can enable retailers to carry out stock counts within their stores once a week in an average duration of one hour, using only a few handhelds. Through this, retailers can gain 98 percent inventory accuracy. Having an enhanced view of inventory accuracy will naturally lead to a reduction in shrink, which is often a result of theft or lost items throughout the supply chain. An average amount of shrink percentage in retail is around two percent of sales. This can create significant cost implications for retailers. According to the British Retail Consortium’s (BRC) annual Retail Crime Survey, the total direct financial cost of retail crime, resulting in shrinkage has risen to around £700m.
Retailers can utilise item-level RFID to prevent shrink throughout all aspects of the supply chain, it can also identify whether an item went missing either from transit or from the distribution centre. Item-level RFID can greatly reduce out stocks for retailers, which in turn can also help to improve customer satisfaction and services. This is a result of the retailer having products available for customers, as and when they want them.
Enhancing the check-out process for customers
Many retailers are adopting item-level RFID for a variety of reasons, including technology giving retailers the ability to speed up the check-out process for customers. This can be seen as part of a ‘technology rebrand’ effort for retailers whilst also acting as a loss prevention tool by helping to reduce human factor-based errors at the checkout.
Overall, this can help to improve the accuracy of a purchase, reduce lengthy checkout queues and streamline the technology experience during the POS process.
Benefits of accurate inventory management for Customer Experience
RFID is helping retailers reach a new level of operational excellence in inventory management. There have been many rollouts of the technology on a global basis, which have demonstrated rapid ROI based on sales lift, inventory reduction and omnichannel fulfilment advantages. It is without a doubt that item-level RFID has become the fundamental tool in opening the door to this new era of retailing.
Evidently, if a customer is looking to purchase an item they want and it is out of stock, they are going to be disappointed. For retailers, this can result in the customer feeling unsatisfied with the service, and therefore choosing not to return to the store in the future. To prevent this and to ensure good levels of customer service, retailers need to have a correct and accurate view of their inventory, meaning they know exactly which products need ordering for new stock and those that don’t.
Overall, it is clear that with item-level RFID allows retailers to gain levels of 98 percent accuracy, with quicker stock counts, customers are evidently going to be more satisfied with their overall experience of shorter queuing times, getting the stock they want, and when they want it. As a result, this creates a greater shopping experience for customers overall.