Category: Blog

In a rapidly shifting landscape driven by digital transformation and omnichannel experiences, the challenge of understanding and exceeding customer expectations has taken on a new level of intricacy.

Recently, a customer survey, ‘Exceeding UK-customer-expectations-2023-24’ conducted in collaboration with ContactBabel and Contexta360, brought insights that shine a spotlight on these complexities. While the familiar metrics such as first-contact resolution and queue times still matter, the survey reveals something more profound. It hints at a bigger picture, one where different customer segments reveal unique aspects of their interactions, influenced by age and goals.

The implications are substantial, offering a glimpse into the intricate dance of surpassing customer expectations. It’s a journey filled with variables – individual preferences, channel dynamics, and strengths and weaknesses that intertwine. But the revelations shared here are just a fragment of the entire puzzle.

The UK contact centre landscape faces a convergence of challenges. Queue lengths are growing, call durations extending, and agent salaries soaring – all creating an environment where cost and performance pressures collide. While the call of self-service and call deflection is strong, the demand for empathetic and effective phone service makes a powerful resurgence, echoing the changing tides of the business world.

The report also reveals a captivating subplot that sees younger customers, the digital natives, gravitate toward self-service and digital channels as their preferred route. Yet, intriguingly, their loyalty to businesses appears more transient compared to their older counterparts. It’s a tale of contrasts, a narrative that unveils hidden layers. But remember, this is just a glimpse of this fascinating report.

The status quo faces challenge, prompting businesses to adopt a holistic view. The era of one-size-fits-all solutions is waning, replaced by the need for strategies tailored to diverse customer preferences. Each segment, driven by age and goals, demands a custom approach, a dance aligned with their unique values.

And here lies the crux – a strategic approach calls for a balance between innovation and tradition. Embracing cutting-edge technologies is vital, acknowledging the evolving inclinations of the younger generation. Amid this landscape of innovation, the report points to the timeless significance of telephone interactions. The phone channel, with its human touch, its authentic connection, transcends trends and time.

In conclusion, the customer survey presented here is just the prelude to a comprehensive narrative of customer expectations in the UK contact centre domain. It’s a story that unveils the multifaceted dimensions of diverse customer segments, nudging businesses to tailor strategies that bridge generations and objectives. While digital channels summon, the echoes of traditional telephony remind us that a harmonious blend of innovation and timeless values serves as the compass to navigate these ever-changing waters.

In an era marked by transformation, success hinges on orchestration – a fusion of advanced technologies and enduring customer-centric principles.

If you’re aiming to not just meet, but totally blow-away your customer service goals, then you’ve got to get extremely comfortable with your service levels and objectives. But it’s not just about knowing them; you need to dig deeper and measure the time and sweat you’re pouring into maintaining those levels. And don’t forget about where the roadblocks are popping up. Is it a knowledge thing? Maybe your processes are tripping you up. It could even be the whole customer journey or just not-so-easy access to information.

No wonder Customer Service Excellence is such a minefield for many organisations.

But here’s the good part, you can totally turn things around.
Start by setting some ground rules – both the minimum you’ll accept and the maximum you’ll strive for. Then take a good look at whether these rules line up with the customer service game plan you agreed on. Can you realistically hit those marks and deliver the goods? If you fall short somewhere, own it and work out what’s up. Sometimes, aiming for the stars is inspiring but there are times when it’s just not on the cards, no matter how hard you try.

The real good news is that you’ve got an ace up your sleeve, data-powered transformation.

Your journey starts simply by:

Knowing Your Objectives Inside Out. Start by immersing yourself in your customer service levels and targeted goals. Familiarity isn’t enough – you need an in-depth understanding of what you’re aiming for.

Measuring Time and Effort Invested. Quantify the hours and energy you’re devoting to maintaining your service levels. This step provides a tangible perspective on your commitment.

Pinpointing Sources of Friction. Identify the areas causing friction in your customer service journey. Whether it’s knowledge gaps, complex processes, or accessibility issues, be specific about what’s hindering seamless interactions.

Setting Clear Minimum and Maximum Levels. Establish both the minimum acceptable level and the aspirational maximum level for your customer service standards. These benchmarks serve as your guideposts.

Alignment Checking. Evaluate whether your established levels align with your agreed-upon customer service standards. Ensure they’re realistic and achievable within your resources.

Addressing Shortfalls. If gaps exist between your standards and actual performance, acknowledge them and investigate the root causes. It’s crucial to understand why certain objectives might be hard to attain.

Defining Your North Star. Articulate your ultimate vision for customer service excellence. Imagine an ideal process where interactions are seamless, efficient, and highly effective.

Deconstructing Customer Interactions. Break down how customers engage with your service centre. Analyse each touchpoint to understand where friction or extra effort might occur.

Identifying Pain Points. Determine how many customers encounter challenges before getting the right answers. Is it a knowledge issue, a process glitch, or something else? Pinpoint the areas that need improvement.

Analysing Interaction Rhythms. Gain insights into the frequency and patterns of customer interactions. This helps you understand the overall health of your customer service ecosystem.

Evaluating Turnaround Times. Assess whether your promised turnaround times align with the expected excellent service. Determine if you’re consistently meeting your commitments.

Embracing Unbiased Insights. Rely on data-driven insights for an impartial and standardized view of your customer service landscape. Avoid the limitations of relying solely on surveys or agent-reported data.

Harnessing AI and Data Insights. Leverage AI-powered tools to gain transformative insights into your service health. These tools provide comprehensive, reliable data to inform your strategies.

Taking Decisive Actions. Armed with comprehensive insights, take actionable steps to enhance your customer service. Address pain points, streamline processes, and improve overall service quality.

Iterating and improve. Continuously monitor your progress and iterate your strategies based on real-time data. Use insights to refine your approach and drive ongoing improvements.

Aiming for Excellence. Strive for customer service excellence by leveraging data-driven insights to elevate your service levels, eliminate friction and create exceptional customer experiences.

So, there you have it, armed with this intelligence, you’re in the driver’s seat. You’ll spot the hotspots, see what’s doable and plot an informed course accordingly. Achieving Customer Excellence is now well within your grasp.

During a recent visit to Contexat360’s headquarters in Amsterdam’s picturesque canal district, I had the opportunity to join a few of our Conversational AI developers for lunch. We engaged in some lively conversation about the ever-evolving field of AI, discussing its challenges, advancements, and potential applications. These developers were truly impressive, with their vast knowledge in various key areas of expertise.

We started by talking about the challenges they faced in this rapidly changing landscape. Staying up to date with the latest advancements was no easy task, but they embraced the excitement that came with it. They highlighted the need for continuous learning and adaptation to new technologies, research advancements, and industry trends to stay relevant in this fast-paced environment.

The topic of ethics naturally came up, and we all agreed on its critical importance. Transparency and responsible AI practices were at the forefront of their development approach, ensuring users were aware of their interactions with AI systems. They emphasised the significance of building trust with users and managing their expectations to avoid any deception.

AI and Diverse Linguistics
The developers also shared fascinating insights about the role of Natural Language Processing (NLP) within the context of Conversational Analytics. They explained how NLP plays a crucial role in enabling Conversational AI systems to understand and process human language, making it possible to have meaningful and contextually relevant interactions.

One of the challenges they discussed was handling multiple languages. Since Conversational AI interacts with users from diverse linguistic backgrounds, it requires robust NLP capabilities to comprehend and respond appropriately. The developers emphasised the importance of developing multilingual NLP models that can seamlessly switch between languages, ensuring a smooth user experience regardless of linguistic variations.

Also, they highlighted the significance of continuous improvement and refinement of NLP models. Training NLP models with high-quality data that covers a wide range of conversational contexts is essential to enhance accuracy and contextual understanding. Additionally, the developers mentioned the importance of fine-tuning the NLP models to specific domains and use cases, as this results in more tailored and effective conversational experiences for users.

Overall, the integration of NLP within Conversational AI is a pivotal factor in creating sophisticated and user-friendly systems. The developers’ dedication to staying at the forefront of NLP advancements and delivering unparalleled solutions to transform customer conversations was evident.

Recent Advancements in Conversational AI
As we enjoyed our lunch, we delved deeper into the recent advancements in Conversational AI that had caught their attention. They were particularly familiar with Generative AI models, which had the ability to create human-like responses and revolutionise conversational experiences. Additionally, they shared their excitement about the multimodal capabilities of AI, allowing it to process various modes of input, such as text and images. This breakthrough enabled more seamless and natural communication, greatly enhancing user experiences in customer support and other applications.

The conversation then turned to the potential impact of Conversational AI on different industries. They elaborated on its transformative role in healthcare and finance. In healthcare, personalised virtual assistants could provide support and guidance to individuals with physically limiting health conditions, offering not only logistical assistance but also emotional support. In finance, Conversational AI had already revolutionised customer service, providing personalised financial advice and automating various tasks, all while maintaining a human touch.

The Collaborative Future of AI and Humans
During our engaging conversation, the developers couldn’t contain their excitement about the potential of Conversational AI-human relationships. They painted a compelling vision of a collaborative future where humans and AI seamlessly coexist, leveraging their respective strengths. With AI’s remarkable ability to process massive amounts of data and identify patterns, it would enhance human decision-making, freeing us to concentrate on more complex cognitive tasks. The synergy between humans and AI promised a future of unprecedented possibilities and productivity.

Unleashing the Potential of Conversational AI
As we wrapped up our lunch, I felt confident that the powerful and transformative technology that is ‘Conversational AI’, will exponentially evolve and revolutionise the way we interact with machines. The developers’ passion for their work and their commitment to ethical practices left a lasting impression.

In conclusion, the journey of Conversational AI is unfolding with immense possibilities. With a dynamic team of developers at the forefront of innovation, Contexta360 is set to unleash the full potential of Conversational AI and redefine customer conversations for the better.

Customer experience surveys have long been used by businesses to gauge customer satisfaction and improve their services. However, upon closer examination, we discover inherent biases and limitations that may not fully represent the authentic customer experience. Today, I’d like to take you on a journey to learn about the flaws of traditional surveys and the game-changing potential of Conversational Analytics, the lens to understanding customers through factual insights. We will delve deeper into understanding the customer and gain a broader and more perceptive view of customer service as a group, enabling businesses to thrive in the dynamic world of customer experience.

The Bias in Customer Experience Surveys
Due to the extreme nature of the opinions, only a small percentage of customers respond, resulting in skewed representations of overall sentiments. Recall bias, which is based on customer memory, can lead to inaccuracies caused by recent events or fading memories. The structure of questions, or question framing, may inadvertently guide respondents, jeopardising the objectivity of survey results. Important nuances and context from customer interactions are frequently missed by surveys, limiting our understanding of the true customer experience.

Conversational Analytics, a game-changer in understanding customer experience
Natural language processing and artificial intelligence are at the heart of Conversational Analytics. It changes how businesses gain insights from customer interactions and provides a comprehensive and unbiased picture of the real customer experience by analysing conversations across multiple channels such as calls, emails, and chats.

Conversational Analytics, as opposed to surveys with intermittent responses, provides real-time insights by capturing customer emotions and sentiments as they occur during interactions. Conversational Analytics doesn’t use questionnaires and elicits unfiltered feedback from customers, providing a truly authentic understanding of their experiences. By analysing entire conversations, providing deeper context, revealing factors that influence customer satisfaction. Armed with this technology, companies can map the entire customer journey, identifying pain points and touchpoints for improvement, ushering in a more seamless customer experience.

The Business Benefits
Armed with accurate insights, businesses make data-driven decisions that improve customer service while also fostering higher satisfaction and loyalty. With real-time issue identification, companies can address problems as they arise, avoiding potential churn and negative word-of-mouth. Adopting Conversational Analytics provides a competitive advantage, allowing organisations to remain at the forefront of customer experience excellence.

Conclusion
Traditional customer experience surveys are extremely valuable with the right and meaningful data, but they also have limitations and bias. Conversational analytics is a game changer, providing genuine and real-time insights into customer experiences. Businesses can improve customer service, cultivate loyalty, and gain comprehensive insights into their customers by leveraging this technology. With Conversational Analytics, a customer-centric future awaits, in which businesses thrive by intently listening, understanding, and responding to the voice of the customer.

Hello, fellow tech enthusiasts! It’s Tessel Wisman here, and I couldn’t be more thrilled to share my journey as a Junior Developer at Contexta360 with you. Over the past three weeks, I’ve had the opportunity to delve into the intricacies of Conversational AI, learning and growing as I navigate this exciting domain.

My journey into the world of Conversational Analytics AI development has been shaped by my diverse range of interests, from biology and chemistry to language and technology. During my time at university, I studied Interdisciplinary Sciences and discovered my deep fascination for AI.

Language has always captivated me, and the application of AI to process and comprehend natural language stood out as one of the most enthralling uses of this technology. Consequently, during my master’s degree, I specialised in natural language processing, text mining, and automatic speech recognition, which solidified my passion for this field. This ultimately led me to embark on a career in NLP/AI development.

My attraction to Contexta360 and the role
After completing my degree, I actively sought opportunities at start-ups, craving the fast-paced environment they offer. I wanted to explore a range of responsibilities and discover my professional strengths. Contexta360 caught my attention while I was searching for start-ups in and around Amsterdam that worked on NLP-related products. Their array of NLP solutions, both existing and upcoming, resonated with my interests. Intrigued, I reached out to the company, and the rest, as they say, is history.

Key responsibilities, challenges, and approaches
From the moment I had my first interview at Contexta360, I knew that I had found a work environment that aligned with my aspirations. The company has a flat organisational structure, fostering a great team dynamic and atmosphere. I’m excited to work on a wide range of projects and expand my skill set. I’m particularly pleased with the diversity of the team, with members hailing from different nationalities. It’s refreshing to be part of a software development team where women are very well represented—a welcome change indeed!

My primary responsibility at Contexta360 is to develop NLP-related features. My initial project involves researching an enhanced version of unsupervised topic modelling, a fascinating task. Although it was a new NLP implementation for me, my broad knowledge has been instrumental in overcoming challenges and making progress. The past few weeks have been focused on becoming familiar with the company’s code base and gaining practical software development experience. As a newcomer to the IT industry, I am gradually building confidence in various tools used in the software development pipeline. Fortunately, my co-workers have been incredibly supportive, always ready to lend a helping hand when needed.

Support from the team
I am grateful for the support that I have received from my colleagues at Contexta360. They have been not only helpful but also a source of valuable advice. I have never hesitated to reach out to them whenever I needed assistance.

Memorable experiences and achievements at Contexta360 so far
During my initial three weeks at Contexta360, I had the opportunity to work on improving one of the features of our AI-fuelled conversational analytics platform Contexta360 CORE using new NLP techniques. So far, I’m pleased with the progress made, and my research has unveiled fresh insights and ideas for the future. Being involved in strategic decisions at such an early stage is incredibly motivating and encourages me to make the most of the time I have for this project.

New skills and techniques as a Junior Developer
I am focused on developing my practical software development skills. This involves gaining familiarity with the DevOps pipeline and transforming ideas into tangible business implementations. While my academic background equipped me with theoretical knowledge and research skills, implementing NLP models and applications in a real-world product presents new challenges. Time and resources are often limited, necessitating pragmatic decision-making to meet deadlines. I am already learning to make practical choices within specific time frames. Also, I have the privilege of learning from my colleagues about software development in general, as well as NLP techniques and speech recognition.

Strengths in Contexta360’s approach to Conversational Analytics AI
Contexta360’s approach to Conversational Analytics AI is far reaching. The field of Conversational Analytics is continuously evolving, and our current product offerings are already invaluable to clients. However, it is the myriad of ideas and forthcoming releases that truly excite me, there is so much untapped potential waiting to be harnessed.

Expectations and aspirations in the coming months
Looking ahead, I am eager to continue working on various NLP implementations at Contexta360. In the next few months, I anticipate focusing on areas such as topic modelling and summarisation, among others. While Contexta360 offers compelling software solutions, they are pushing the boundaries of natural language processing techniques to further enhance customer analysis and the customer experience. The possibilities are endless, and I can’t wait to explore them.

Reflecting on my first three weeks as a Junior Conversational AI Developer, I can confidently say that I have found my passion. The fusion of AI and human communication is a thrilling frontier that holds tremendous potential in transforming how we interact with technology. Every day brings new discoveries and challenges, fuelling my desire to learn and to innovate.

As I continue this journey, I look forward to deepening my understanding of advanced NLP techniques, exploring multi-modal interactions, and contributing to cutting-edge research in Conversational AI. I am grateful for the supportive environment at Contexta360, where I can grow both personally and professionally alongside a team that shares my enthusiasm for this transformative field.

In conclusion, my initial weeks as a Junior Developer have been a whirlwind of learning, growth, and excitement. I am privileged to be part of a team that encourages curiosity and empowers me to make a meaningful impact. With each passing day, I am more motivated to push the boundaries of Conversational AI, bringing intelligent and empathetic interactions to the forefront of human-computer interfaces. The journey ahead is bound to be challenging, but I am ready to embrace it wholeheartedly.

Contact centre business transformation is a complex process that involves significant changes to technology, processes and people. It is not surprising that implementation is taking longer than expected. While many factors contribute to delays, some of the most common pitfalls include a lack of alignment, insufficient resources, resistance to change and a failure to understand customers’ true needs.

One of the primary challenges that business organisations face when attempting to implement a digital-first business transformation strategy is lack of a clear strategy. It is easy to get caught up in day-to-day activities and lose sight of the big picture if you don’t have a solid plan in place. As a result, organisations may not fully comprehend the scope of the required transformation or have a roadmap to guide them through the process.

Another pitfall is failing to invest in appropriate technology. Many businesses make the mistake of investing in technology that is unsuitable for their needs. Therefore, they waste time and resources on solutions that do not produce the desired results. Businesses must select technology that is aligned with their goals and that supports their long-term vision.

When attempting business transformation in the contact centre, agent resistance to change is a common challenge. They may be resistant to change for a variety of reasons, including apprehension about the unknown, concerns about job security or a misunderstanding of the benefits of the transformation. These concerns can lead to implementation delays, a lack of buy-in and a failure to achieve the desired results.

Understanding the advantages of the changes being implemented is key. Employees may not be motivated to support the transformation if they do not understand how the changes will improve the customer experience or make their jobs easier.

To overcome these challenges, it is critical to involve agents and include clear communication about the benefits of the changes, as well as ongoing training and support, and digital transformation success milestones.

Many businesses are implementing digital-first business transformation strategies successfully by using a variety of approaches, including agile methodologies, cross-functional teams and a focus on customer experience. By putting the customer at the centre of their transformation efforts, these companies can align their technology, processes and people to deliver a seamless and personalised customer experience.

Finally, successful contact centre business transformation necessitates a combination of strategic planning, investment in the appropriate technology and an openness to change. Businesses can position themselves for success in today’s rapidly evolving digital landscape by avoiding the common difficulties listed above and focusing on the customer.

The bad ones stay and the good ones leave. Funny, that isn’t it?

It is not unique to the contact centre, but staff recruitment, development and retention is the number one issue I hear about in my day-to-day interactions with customers, prospects and partners. This is particularly amplified, it seems, in larger contact centres with more than 500 staff.

Money (salary) is obviously a big driver, but not one that we can do much about. There is an economic model we all must fit within and, if this is a prime driver, I am sure you will react to it as best you can. But I find money has two sides to its coin. The obvious side is: I need to pay the bills. The less obvious side: how much do I need on top to put up with this? And it is the latter that really drives the exit of good players, not the former. So, what can we do about it?

Well, first let us categorise the employee stages. You will have staff that are:

Consciously Incompetent: they know they don’t know what they are doing. There are two subcategories within this group: newbies and problem people. Therefore, keep the former and lose the latter.

Unconsciously Competent: they don’t know that they know what they are doing.

Consciously Competent: they know their stuff.

There is also a category of Unconsciously Incompetent and you should get rid of these people fast.

You are left with newbies, potentials and rock stars. Now you need a strategy to keep and motivate all these guys outside of the obvious $$$£££€€€.

Each category needs different drivers and I have mapped out more than 20 for each, but that would make for a very boring blog, so here are the top three per category.

To start, my model is aligned to personality types that can be simplified into staff that want:

1. A career path
2. A better me
3. A better company
4. To help/develop others.

All of these are clearly interrelated.

The Newbies
These people typically have more bias towards career path and a better me.

The number one frustration of this category is lack of visibility of a clear and granular career path programme. This is not simply role based, for example agent to senior agent to supervisor to QM leader and so on. Although this is valid and important, it is more about the experience and education-based activities you can map out within the current role. Think of it as dot releases of software. They come in at 1.0, and you offer 1.1, 1.2. 1.3 sub-elements before they are ready for 2.0, also followed by a series of dot releases. This way the career structure becomes substantive and structured.

This category typically wants to do better, learn and improve their resume, so having a platform to facilitate this is fundamental. They are typically motivated, keen and bright, and learning from others and from systems is key. Speech analytics platforms and agent real-time assist platforms not only drive the development of these staff, but they also directly impact the customer satisfaction and experience and have a meaningful impact on FRC and ACHT.

I am Invisible.
This category also wants to shine bright and impress. But many are not given the stage. We have seen a phenomenal impact by placing excellent call examples, whether sales, service, complaint, objection handling, sincerity, condolence, and so on, into an indexed excellence library. They become the star, and other newbies learn.

The Potentials
These people are critical to you, and they probably make up most of your staff complement and therefore deal with the bulk of the volume. There are lots of subgroups, but at a high level there are those who just want to do the job (hopefully better), and those who want to move up the ladder to leadership of people and process. So, this category is either focused on ‘better me’ or ‘career path’ with added ‘help others’ (people management) and/or ‘better company’ (back-office processes, analysis, knowledge and data).

The drivers of frustration come from several areas, but two big drivers for staff who want to move up are: mundane tasks and the perception of higher value. This means they are frustrated as they think they know the answers to the business problems but do not have the mechanism to substantiate them or impact change.

These are rising stars, but not quite stars. As a leader, you may find yourself in a tough spot as you need troops and not more officers.

The answer is to give some degree of systems access and allocate authorised time to prove their theories and reward them. I have seen incredible responses to giving seasoned agents and junior team leaders access to intuitive conversational analytics tools to investigate why customers calling and where there are broken processes, missing knowledge and friction points.

Back-office teams do this in isolation. Front-office staff do this from knowing, because they feel the customer pain in the calls, chats and emails they handle. We extended our conversational analytics query builder from ten back-office staff at a major telco provider, to more than 200 agents and team leaders, and the impact on staff was very positive, as were the subsequent findings.

The Rock Stars.
Again, these people may be happy with their lot or want to progress up the ladder. They are seasoned and highly knowledgeable, not only about the company’s products and services, but all the nuances in process.

The big frustration for them is needless processes and broken processes. Many rock stars are still subject to relatively pointless QA/QM sessions and must fill out copious forms and reports post call/chat/email. In addition, there is significant frustration that comes from broken company processes.

Automating these activities is a major release valve for the employee experience and dramatically impacts staff retention.

In summary, organisations may wish to consider automating call summary workload and the QA/QM process, not only to directly impact staff wellbeing and performance, but also to save a small fortune in the process. They could also consider using AI to automate the detection of unknown topics that drive failure demand and process issues.

I hope this helps. It is just the tip of the iceberg.

 

Having worked in the customer interaction space for many years, I have witnessed the advancement of technology aimed at improving customer service or reducing supplier costs.

The industry has moved from advanced routing and call control to the first IVR revolution, multi-channel and omnichannel, WFO/E/M XY and Z, and now the AI-powered world of automation, augmentation and BOTism.

Post Covid-19 hibernation, with people starting to reconnect with friends and family in bars, restaurants, clubs and sporting venues, the inevitable “How’s Work?“ question always comes up. This is a question I find somewhat difficult to answer, because my company operates in a highly specialised field.

I work with some of the brightest PhD-level minds to solve extremely complex business problems. As a result, converting this capability and the technologies we have developed into a snapshot update is difficult. The elevator pitch is clear, but many recipients’ eyes glaze over when I discuss NLU and NLP large language model, generative AI speech augmentation, real-time automation and analytics powered by conversation intelligence. Therefore, I frame my response as a question: “When was the last time you were DELIGHTED with an automated or self-service interaction with a company?”

The response is always the same: negative, and it resonates with them on a personal level. Many of these people describe their latest interaction with a company that they believed in and expected better customer service from.

It is then very easy for me to describe how my company creates software that solves this problem. Indeed, our solution determines why someone called in the first place, corrects any root-cause issues, and ensures that the customer experience, journey and response are highly optimised, lowering costs and increasing C-Sat and revenue.

Today, we are witnessing a resurgence of concern for the customer rather than a covert desire to save money. Simply automating has not worked and customers have clearly voted with their feet. (Or, these days, a finger). Click.

A genuine customer-first perspective, which focuses on business and customer challenges rather than technology, is emerging. I refer to this as Intelligent Business Transformation, in which the old phrase  “people, process and technology” is adorned with a fourth area of knowledge.

In short, it is critical to understand how these capabilities are coordinated, harnessed and optimised. People (customers) converse with people (agents). People (customers) converse with technology (bots). Both interaction systems must be optimised, and this is where process and knowledge come into play.

Intelligent Business Transformation will improve our people, augment our humans and allow automation to function.

 

In a previous blog we talked at length about how robots are infiltrating our world and supposedly solving customer problems, queries and reducing operational costs.

In my humble opinion, most of today’s customer automation is frustratingly poor.

Admittedly, there are scenarios where self-service plays a role in 100 per cent-productised customer journeys, but as soon as there is any complexity, nuance, or anomaly to the request that is outside of the standard operating procedure, things go wrong.

It must be said that humans are amazing. Our ability to listen, assimilate multi-threaded and dependency questions, ascertain emotional dynamics and, ultimately, comprehend is phenomenal. We are a way off seeing a digital service that can fully compete with a human.

Today, there is a new wave of Artificial Intelligence (AI) – a shining new lightsaber for agents; the Force that gives businesses an overwhelming financial advantage. We are now entering the world of the Jedi agent, the agent with AI-powered augmented assistance that transforms compliance, first-call resolution (FCR), sales, CX and C-SAT.

What is this Force and how do I get Jedi agents?
The dichotomy for customer service, sales and contact centre OPS professionals for the past five years has been automating customer interaction versus utilising the human service. Finding a balance that delivers on cost, skill, resource, knowledge, customer value, brand and more has been a challenge.

Now enter the trichotomy.

1.  Automate the customer interaction
2.  Automate (Jedi) agent assistance
3.  Pure unassisted human

Number 2 is new, powerful and easy to deploy and truly transformational to service and cost.

Rather than start with what it is, let us consider the use cases and outcomes. We break these down into three areas:

• Agent workload and cost reduction
• FCR, CX and C-SAT optimisation
• Compliance optimisation

By automating two minutes of post-call wrap-up across 500 agents taking 40 calls each per day, a business could save approximately £3.7 million a year.

If all agents have real-time prompts and advice, FCR can increase by 20 per cent, CX and C-SAT will improve more than 30 per cent. By pre-briefing agents via automated call summary, actions and sentiment from any previous interaction, there will be no non-compliant calls.

How can you achieve this? Well, nothing needs to change. This new technology easily and simply complements the incumbent system, whether that is Genesys, Avaya, Mitel, 8×8, Five9, AWS-Connect.

In short, Agent Assist technology will acquire your customer interactions from your switch, Session Boarder Controller (SBC), chat server or video server, in real time. It will transcribe in high definition so that all brand terms and unique product or service names are captured accurately. Then, it will process the conversations for intent, quality and action and propose real-time prompts or content to the agent who is assisting in the transaction. Auto summarisation will remove work for the agent, distilling a perfect brief for the next interaction. Agent Assist will also track compliance requirements within the call or chat session so that no call is left before the appropriate steps are taken.

It is estimated that more than 70 per cent of automated journeys end up back at the agent. Today’s robot is a glorified music-on-hold, pretending to add value and reduce cost, but negatively impacting CX and C-SAT.

Business justifications for investments of £1 million in older bot technology were that they would save £4 million in staff costs. Realistically, they save £1 million maximum. Breaking even is a long way off and ruined by added customer frustration and eroding service metrics.

Isn’t it time you tried the lightsaber? Available in red, blue or green.

Part 1 of Robot vs humans can be found here.

For more information, please contact contexta360.com

 

Call centre customer engagements tend to follow a set path and process. This runs along the lines of a recommended workflow, opening, discovery, suggestions, summarisation and a customer satisfaction survey.

While some contact centres are adopting Artificial Intelligence (AI) to help them to unify their processes and assist in call handling, there are still many that are plodding along without AI.

Without AI, these contact centres can completely miss interactions of concern that affect an agent’s well-being. These are the types of interactions where the amount of negative sentiment and cross talk, and the number of cancellation risks, are above average.

If we consider that a medium-sized contact centre has potentially more than 3,000 unsatisfied engagements every month, that is more than 3,000 interactions that are difficult to deal with and more than 3,000 potential calls where agents will need to remain calm and communicate in a friendly and positive manner with highly irate customers. This is an extremely challenging situation for agents, who are having to empathise with and educate the customer while trying to elicit positive sentiment and a good resolution.

1. Empathy is the pathway to trustworthiness

Contact centres use escalation protocols that provide guidelines on managing dissatisfied customers. These are conversational guides to direct and steer agents to better understand the needs of the customer. They also provide handling guidance to help agents to identify needs, resolutions and mea culpa (whose fault).

So, what is missing? Many of these processes are essential and are focused on the annoyance level of customers’ complaints and escalations. Pressure is placed on the agent to recover difficult situations, and this often results in agents working outside of company protocol. These incidents can result in the customer taking to social media with a not-so-factually-accurate post, in a blatant attempt to shame the organisation into giving the customer what they want. Again, unpicking this situation takes human intervention to resolve it to everyone’s satisfaction and can be emotionally draining, particularly if the agent does not feel they are being assisted or protected by company protocol.

The importance of an agent’s holistic wellness is well-documented and impacts their overall health, their outlook and attitude, job satisfaction, motivation and enthusiasm. Therefore, emotional well-being levels should be measured regularly. Knowing and understanding the emotional state of your agents is critical to the health of your business and ensures that your customer-satisfaction levels remain above average. This will ensure your customers trust your organisation.

2. Onboarding is not an operational instruction manual

Taking care of agent’s emotional well-being really matters. Emotionally healthy agents are able to manage a good work-life balance. They can work within a range of emotions, without losing control, while they operate and interact with all customer types and engage in a positive, friendly and patient manner. This is essential to achieving a great customer experience and NLP Score.

Post lockdown, agents are dealing with customers who are vocalising more-intense negative emotions. This places agents under pressure to satisfy customers’ needs. To protect agents, organisations need to put measures in place to capture the emotional well-being of their agents more quickly. This will protect their human resource investment, keeping agents onside and raising their morale. Many organisations still prioritise the onboarding of new agents over the emotional well-being of incumbent agents. Such organisations have a high agent attrition rate and low NPS score. This practice is counterproductive as the cost of continuously recruiting and onboarding new employees far outweighs the cost of adding agent sentiment analysis to the mix and retaining more of their existing agents.

3. Engagement well-being is a two-way street

Demanding customer engagements leave negative footprints. Many organisations fall back on measuring sentiment, satisfaction and NPS surveys to rate experience and behaviour  rather than looking at product, processes and people. In many cases, friction or conversation control behaviour can be detected much earlier than post-call surveys. Automated well-being insights measure and monitor agent health via employee insights, fast talk, cross talk, sentiment and frustration. Every agent engagement can be analysed and flagged immediately, which helps agents who need support to deal with the most demanding customers and maintain control of the call.

With AI-driven insights, a customer experience (CX) and employee experience (EX) improvement culture, which focuses on proactively managing all customer and employee experiences, is possible. It efficiently links 100 per cent of customer contacts to service success. This assists leaders to rapidly and effectively anticipate the needs of the customers or agents who express dissatisfaction or experience excessive friction and effort. This, in turn, contributes to an organisation’s CX strategy and change management success programmes.

For more information, please contact contexta360.com