Recognition

My 2019 Roundup

I’ve had a awesome crazy amazing 2019, and I wanted to share a few highlights, personal and professional, that have made my year!

Finished my Masters degree in Professional Education & Training

This degree saw me become a part-time hermit, read so many research papers that I thought my brain would explode, and cry on more than one occasion.

More than anything though it gave me an appreciation for how much of a journey professional learning is. How much learning is irrevocably linked to our egos, identities, and preconceptions. How much we box up and pigeonhole learning into professions and tight areas when really it’s learning along the boundaries between them that’s full of the most tenacious issues. How much learning is vulnerable, and messy, and if you’re doing it properly, it can sometimes make you feel really crappy.

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Customer Experience, Technology, Work

Getting Your Customer Service Team Ready for the Holiday Shopping (and Returns, and Shipping, and Problems) Season

Holiday shopping season isn’t easy. Even for the most well-organized customer service functions, seeing query volumes and queues rise into the red can be a hair-raising and difficult experience to handle.

When it comes to holidays some things don’t change, like presents under the tree, turkey at Thanksgiving, and even customers’ expectations of service. A difficult shopping experience during the holidays can deter them from coming back and leave businesses with less than favorable reviews, and the resulting impact can be felt all year round.

64% of retailers are preparing internally to meet customer expectations this holiday season by transforming processes to become more agile and customer-focused. Prioritizing the customer experience when getting your customer service team ready for the season can help mitigate this and remove friction from customer interactions.

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Customer Experience, Learning & Training, Work

So You’re a New CX Leader? 5 Tips to Succeed in Your Role

We’ve all been there. It’s your first day on a new job and you’re trying to figure out how things work. There’s lots to be done – relationships to be built, goals to be set and plans to be drafted. You’re learning how to work in a new environment, and trying to battle the exhaustion that comes with that while remembering everyone’s names and figuring out what your priorities should be.

Nearly every type of job contains a similar pathway through your first days and weeks, while you try to get to grips with the new reality of your working world. But Customer Experience (CX) specifically holds some challenges that many new leaders can take weeks or months to grasp.

Here are a few tips to try and demystify those challenges upfront, to make your initial transition easier:

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Customer Experience, Learning & Training, Work

How to drive customer experience through effective agent training

Picture this. 

You’re managing a contact center where your agent team has received all of the information they need to serve customers perfectly. New starter training helps your agents start taking queries at precisely the point they feel confident to, armed with the skills and knowledge needed to serve customers efficiently. Training on new products or services is completely effective, and afterward, agents immediately start delivering the right information to customers. As a result, your first contact resolution (FCR) stands at 100%, as agents are always sure to give out complete, correct, and concise information to your customers so they can get their issues solved on the first try, with no hassle.

If that sounds like a dream to you, that’s because achieving this standard of service is almost impossible.

The joy of customer experiences delivered by people is that those experiences can be full of wisdom, empathy, and the human touch that makes customer relationships feel really special.

On the flip-side, though, humans are complicated. We all have our own lenses and ways of interpreting the world, and we’re all individuals with different preferences.

In the example above, that means it’s just not possible for every agent to react the same way to the information that you give them during training. Whether your contact center is onboarding new starters or updating existing staff on upcoming changes, the learning that agents need to undertake is almost always a more complicated process than passively soaking up information and perfectly parroting it back to customers. 

effective contact center training

I’ve spent my career trying to understand what makes for really great learning, and there aren’t any simple answers. Learning is complicated and is influenced by our emotions, our culture, our environment, and a myriad of other factors. 

We can, however, look to some established theories on what makes for great learning, and compare them with what we often see in contact center training. In doing so, we can see where the gaps are and how we can fix them.

I can’t promise you 100% FCR. But I can guarantee that by augmenting what you do currently with what we know makes for effective learning, you can improve information retention, training quality, and ultimately, create better customer experiences.

What makes for effective learning?

Let’s take a brief look at some of the main theories on how people learn well and compare them with how learning in contact centers works.

Learning should happen in the environment in which the knowledge gets used

We’ve all been there. You attend a training course and hear some excellent ideas that you feel sure will change the way you work for the better.

Then you get back to your desk, and those good intentions fade. Those ideas might have sounded great in the training room. But faced with the reality of day-to-day work, the frustrations and barriers that prevent you from applying your new learning are all too apparent and difficult to conquer.

Training programs around the world suffer from this problem – that learning received in an environment away from the workplace is often difficult to apply when back at your desk. 
The idea that learning should happen in the environment the knowledge gets used in makes sense when you apply it to hands-on skills. Imagine trying to learn to play the guitar by merely reading a book, and never actually playing a guitar. 

However, in agent training, our goal is generally for agents to change their behavior when interacting with customers. The environment is then one they interact with customers in – at their desks, on the phone, or taking live chats. The problem with this, though, is we can’t easily simulate this environment in a training context. 

Many agent training programs recognize this and build in other training methods to try and shift learning into an environment that better mirrors an agent’s work. Role plays are one way to do this. But role plays can make many agents want to die from embarrassment. The anxiety can interfere with effective learning, either burning a negative experience into the agent’s mind or causing them to want to forget about the activity entirely. 

How to fix this: I’m excited about the potential for Virtual Reality to simulate an agent’s environment in a training setting. But this technology isn’t exactly widespread or achievable for most.

Instead, focus on how you can bring real-life elements into your agent training program. Shadowing is a great way to do this. Pair up newer agents with more experienced ones so that newbies can learn in context. This allows them to see how more experienced staff members react to the customer curveballs that don’t often get covered in theory-focused training. You can also have agents listen to old phone calls or analyze live chats, and encourage discussion about the nuances of each case.

Learners should receive reinforcement

If you’ve ever owned and trained a dog, you’ll have used reinforcement theory to help your dog learn what behaviors are desirable and undesirable. When your dog sits on command, you give them a treat. The treat becomes positive reinforcement for the behavior you want them to learn, increasing the likelihood that they will repeat it. 

Humans also respond to reinforcement in helping us to learn, and words of encouragement or constructive criticism are how that’s done. Feedback serves as validation that a learner has interpreted the information they’ve learned correctly. Or if they haven’t done so well, the input should reinforce what they should do instead. When a person does do well, a healthy dose of validation and encouragement also serves to strengthen the new behavior simply through the feedback feeling nice.

Even the worst of contact centers employ some form of feedback mechanisms that serve as reinforcement for behavior. More specifically, you tend to see that when a customer complains about something an agent has done, that feedback will get relayed to the agent, and they’re told to buck up.

But there’s a world of difference between that kind of feedback and truly useful feedback that effectively reinforces both good and bad behavior.

How to fix this: Quality assurance is an excellent way to get started with reinforcing agent behavior. Ensure that agents are given specific and timely feedback, on both the good and the bad, to allow them to keep improving their skills. But a better way to do this is by building a feedback culture that lets your entire team learn and create best practices together. You can get started by sharing when things have gone well, and (anonymously) discussing the cases where things haven’t gone right. Whichever way you choose to give feedback, involving your team in the process ensures that feedback feels like something that’s for them – not done to them.

Learning should be social

Since the dawn of time, humans have learned new skills from other people. Rarely are we struck with inspiration that comes from nowhere. Figuring out an elegant and effective solution to a problem is often best done by talking to someone who has had similar experiences.

And the very nature of customer experience means that it can often take a team effort to change things up at a touchpoint in ways that enhance the entire journey. CX is subjective, so it can take more than one person to come up with great solutions.

It’s also important to recognize that learning doesn’t always occur in ways that are neat and formalized. Learning happens in conversation all the time. By the water cooler, chatting with your desk neighbor, and in meetings where education isn’t the intended outcome at all, learning still occurs. 

But the very nature of contact center targets means that learning from others is often a luxury. It’s usually tough to take an entire agent team away from the queues to be able to attend a training session together. Their days are on a timer, and if your entire team took extended breaks to talk about the finer points of customer service, you’d have a problem.

Contact center work can be isolating. If you’ve experienced life as an agent, you know that sometimes you might spend your entire day talking to customers but barely speak to your colleagues. 

That setup might be great for productivity, but it’s rarely good for quality. For the trickiest cases, it can take a range of ideas and perspectives to decide what makes for the best customer outcomes. As the adage goes, two heads are better than one – so relying on individual agents to have all the answers rarely results in quality outcomes.

How to fix this: Build opportunities for your team to learn together in both formal and informal settings. Part of that should come through a workforce management (WFM) strategy that provides agents with down-time to learn. And don’t forget to give them the ability to learn from other teams. Another tactic is to improve resource opportunities by implementing AI, whether on the agent side in the form of agent assistance tools, or on the customer side in the form of chatbots. Both tools hold the potential to cut the time that agents spend responding to routine queries – allowing you to double down on quality and boost your training time provision.

Agent training shouldn’t come at a cost

If you’re a manager looking to implement more effective agent training strategies, it’s tempting to think of those interventions as coming at a cost.

That’s a dangerous perspective, for a couple of reasons. Training can take many forms that don’t have to drain resource levels – from implementing tech solutions that make learning on the job easier, to simply improving the processes you have. 

This perspective also assumes that a lack of training results in outcomes that are just fine. But when agents haven’t received effective training, you’ll pay the price in repeat contacts and low customer satisfaction.

Looking at the frequency with which customers have to repeatedly contact companies to try and get the correct information or satisfactory resolutions, research suggests that around 30% of customers have to call or chat more than once. That means that there’s a lot of room for contact centers give their agents more of the training they need to deliver the right information, the first time.

Of course, great customer experiences aren’t about dispensing the right information. They’re also about responding with an appropriate tone, sensitivity, and tact. Training should focus on these more emotional aspects of customer service, too.

Finally, investing in training is an investment in your agent experience, especially if your agent team sits in a younger demographic. Gallup recently found that 60% of millennial employees say that the opportunity to learn on the job is extremely important. There is a  growing expectation for companies to offer not just a job, but a job with the potential for skill growth and improvement.

Improving CSat, reducing repeat contacts, while also making agents happier are goals that can all be met with agent training. And in 2019, the possibilities for technology and cleverer processes to make a difference (even for resource-pressed contact centers) are more tangible than ever.

Customer Experience, Technology, Work

[Webinar] Building Strategy and Confidence in Contact Center AI

If you liked mine and Matt’s article for ICMI on building Chatbot trainers in the contact centre, you’ll like our webinar too.

You’ll also like this webinar if you believe in Knowledge Management as a preface for great customer experience!

Click through to access the recording, and here’s a rundown of what we cover…

“As a contact center leader, you’ve worked hard to grow your service quality and efficiency to where it is today. Now, with AI on your mind, new challenges are emerging.

Register for our webinar to learn implementation strategies that provide a practical path to AI adoption for all kinds of businesses – regardless of your size or industry.

You’ll learn:

  • What types of contact center AI technology are available to you today
  • How to identify low-risk entry points to AI technology
  • How to mitigate your roadblocks to AI adoption
  • New strategic opportunities for contact centers post-AI adoption”

Access the webinar recording via the Comm100 website.

Learning & Training, Technology, Work

Intelligent Assistants (+7 Insights on How Agent-Facing AI Can Accelerate Training and Onboarding)

How does your contact center handle new starter training and onboarding?

Most businesses fall into three camps:

  1. Trial by fire: give agents a manual to read, then throw them on customer queries and hope for the best.
  2. Outsource to colleagues: make training another agent’s responsibility, ask the new starter to shadow them, and expect the new hire to be ready in a week or so.
  3. Actual training: devoting resources (not just e-learning!) to coaching each employee to success, measuring and providing feedback along the way.

Option three is by far the best to develop happy, engaged staff, giving them what they need to become successful and confident before they get anywhere near customers. This investment in employee experience (EX) can be found at the foundation of all great customer experiences.

But great training or onboarding comes at a cost. Research suggests that for centers who invest in training, onboarding a new employee can cost upward of $14,000, with a new hire’s break even point for ROI not kicking in until week 22.

That’s a significant amount of time, resource and expense, and smaller businesses especially will know how tricky it can be to secure buy-in for these efforts. It’s still vastly better than trial by fire, where savings on training cost are dashed by poor quality customer interactions leading to dives in customer satisfaction and peaks in churn.

However your center trains your staff, you’ll know that there’s been a lot of talk about how AI can be used to improve customer-facing interactions – but there’s more to AI than meets the eye. The development of new technology means that it is possible for HR and contact center managers to augment traditional training and onboarding processes to help employees learn and access information in better ways than before.

Where does AI fit in the training and onboarding process?

Put yourself in one of your new agent’s shoes for a moment. It’s your first day, you’ve been introduced to your team, signed into your computer for the first time and you’re ready to start learning how to answer customer queries. 

For complex queries, it’ll take you a decent amount of learning to figure out when you’re making the right judgment call – those queries that fall into the gray-area of your organization’s rulebook where a good answer starts with “Well, it depends on…”

But for a lot of other queries, answers are more black and white. When it comes to getting comfortable with basic FAQs and straightforward inquiries, you’re not so much learning them as remembering the right sequence of clicks to get to find information or memorizing answers by rote.

While AI isn’t meant to help employees make tricky judgment calls, it can lighten the load of those straightforward queries when integrated into the systems that agents use in their day-to-day work.

Intelligent Assistants are a form of AI that can do this by integrating customer communication channels with your existing knowledge resources to present answers to agents, at the point they need them.

Equipped with natural language processing (NLP) and machine learning (ML) capabilities, Intelligent Assistants work by scanning text-based customer conversations and providing answer suggestions based on your internal or external knowledge bases, chatbot responses, and other knowledge resources you already have stored in text form.

These systems can even learn from customer interactions within the system, eventually building a response model that’s more robust than your recorded knowledge resources alone.

Just as you have everything you need to drive your car while sitting in the driver’s seat, locating key resources in the agent console has huge benefits – allowing for new starters to start using internal resources confidently and with speed, right in the window where they work. 

What other benefits does AI bring to the onboarding and training process?

We often talk about the necessity of eliminating friction in the customer experience, but we rarely think about what the equivalent might mean for employees.

It’s a reality that for customer-facing employees, getting the right answer to even black-and-white questions might mean fruitlessly consulting a FAQ page, then paper-based manuals, then your online knowledge base, and finally other colleagues, all the while knowing your customer is getting more irate the longer they’re on hold.

The beauty of integrating Intelligent Assistant AI within your communication systems means that you can draw on the combined wisdom of all of these resources and let the AI present you the best answers, no waiting required.

While much of what has been discussed so far is especially relevant to onboarding, Intelligent Assistants can even be helpful to train veteran agents during a new update or product release. 

Many organizations struggle with operationalizing knowledge management and obtaining resources to manage KBs. A lack of solid knowledge resources is a major reason why some companies don’t feel ready to start automating.

But the beauty of internal-facing AI is that you can give it exactly the same resources as you would give any new employee, or what you already present to customers, and start from relatively rough and humble beginnings without that ever impacting on the customer.

Intelligent Assistants only suggest answers that can be edited before sending, so if answers aren’t fully-formed or grammatically correct then they can be built upon by the agent. Agents can also suggest extra answers to the assistant for an administrator to add into the tool, improving its responses over time.

In this way, Intelligent Assistants can help to build stronger internal knowledge tools. They can reinforce a living knowledge management system, where agents interact regularly with a tool that can capture the best of their knowledge and expertise.

If you’ve ever tried to implement KCS or other knowledge management workflows within your centre, you’ll know that encouraging contact center employees to update knowledge resources alongside query handling can be incredibly difficult. There simply isn’t the time in their day to do so. But integrating those knowledge resources in the console where they work means that building robust knowledge resources suddenly becomes a lot easier.

7 insights for smarter onboarding and training

Like any AI investment, it pays to plan well from the inception of the project. The more time you invest in the initial set-up, the better the AI will work, and the more confident you can feel in your new employees with the software guiding them through customer interactions.

The three areas you need to consider the most when deploying Intelligent Assistants are the information it draws on, the deployment process, and a continuity plan. The insights below touch on each of these items, ensuring that quality of information is balanced with speed and cost benefits. 

1. Ensure your knowledge resources are up-to-date

Ask your team to check your existing resources to ensure they are up-to-date and don’t include any glaring errors.

Because Intelligent Assistants are able to draw on your cache of support tickets, previous chat transcripts, and they can learn from agent feedback, it’s not necessary to have a 100% robust knowledge library from the off – the system will become more robust over time.

You should, however, ensure that any information you feed your assistant isn’t outright wrong.

2. Plan the automation process

Be realistic about the types of questions your Intelligent Assistant will be able to handle.

AIs won’t be able to empathize authentically or grow real relationships with your customers – those are the things your agents shine at. Your agents are also best equipped to make the judgment calls on complex queries that really draw on their skills and expertise.

Select relevant queries for your AI to handle from your knowledge resources accordingly.

3. Communicate with your agents

In the same way, let your agents know the strategy and purpose for your Intelligent Assistant. Involve them from the earliest planning stage, secure internal champions, be open and transparent. Including agents from the design stage means that you’ll end up with a tool your team is brought into, and that won’t be perceived with fear or negativity.

You’ll also need to be clear about the types of questions that the tool is best equipped to handle by giving them some example questions so they can see where the boundaries lie. Introduce them to the feedback process within the tool, reward your best contributors, and consider whether you need to reinforce the new process with agent KPIs.

4. Add in knowledge resources and synonyms

Each question will need an answer, and you’ll need to add them into the tool accordingly.

One extra thing you’ll need to account for at this stage are synonyms or business-specific language that your customers and agents use. By adding in a number of alternate word definitions for the same term, for example: customers, clients, and members, your Intelligent Assistant will be able to better handle variations in language that your customers and agents use.

5. Test it, then test it again

Just like you would never want to throw a new employee into any task without making sure they know how to do it right; you never want to deploy any form of technology to your team without making sure it works. Is it fetching the right information? Are the workflows processing the correct information? Most importantly, is the AI helping your agents?

6. Create a maintenance plan

Just like keeping your resources up to date, making sure your AI is up to date is important. While the Intelligent Assistant will learn from customer conversations and agent feedback, any and all product updates, releases, and other new information or links still need to be programmed into the AI.

7. Tune and refine as you go

In the back end of your Intelligent Assistant, you’ll have access to a wealth of information to fine-tune your AI – agent suggestions, stats and statistics on usage, and suggestions from the platform itself. Use this information to keep refining the information your system provides.

The start of an automation journey

Intelligent Assistants are a low-risk way to get started with automation, strengthening your internal knowledge resources to build a customer knowledge model that understands your customers and the way your agents speak to them. Since strong knowledge resources are key to effective chatbots and more, the possibilities for further automation then unfold.

Even if the chatbot route isn’t for you, it’s not just in training and onboarding that Intelligent Assistants can provide benefits. Extended use cases include having the Assistant pull personalized information from a CRM, eliminating the need for agents to put the customer on hold and look up an answer in that system. 

Intelligent Assistants can also be used to automate entire workflows – such as the process of order tracking, password resets or taking payments. Any process which requires multiple, standard steps can be kicked off automatically by agents to gather details, and the agent can then take back control when the customer completes the workflow.

Better onboarding and training with no more trial by fire

Five years ago, nobody would have believed that this degree of automation within contact center training would be here today. Back then, we were barely getting to grips with the concept of omnichannel marketing, yet now it’s a part of standard contact center working.

Technological advancement is happening fast, and Intelligent Assistants are here right now. It’s amazing to be on the forefront of what promises to be change that disrupts our contact centers and training programs for the better.

Humans will always be essential to the customer experience, but we need to better support and develop those humans that serve our customers. AI offers us the opportunity to do that.

The beauty of Intelligent Assistants

When your fledgling agents finally start taking their first queries, even if they’re not 100% confident (and even with months of training, many rarely are), they’ve got an extra safety net to help them out.

While Intelligent Assistants will never be able to coach and mentor, dispense deep wisdom or grow authentic human relationships, it’s possible for them now to take enough of the strain so our teams can have more time to focus on those things.

That’s ultimately the goal of AI adoption. To allow us humans to better exercise our uniquely human skills, and to free us from basic, transactional work – allowing our agents and ourselves more time to focus on the things that truly matter.

Originally published at G2Crowd.