Customer Experience, Technology, Work

Report: Customer Satisfaction With Live Chat Is On The Rise

Another Forbes mention! 😊

Dan Gingiss did a great write-up of Comm100’s Live Chat Benchmark Report and drew out a number of interesting findings – including that live chat customer satisfaction is on the rise.

This benchmark report is a big effort by all of us at Comm100 every year, and I’ve been involved since our 2016 report.

It’s an original piece of research that’s based on all of our customer’s chats, so there are a ton of insights in there for anyone looking to start or grow their live chat operation.

We’re lucky to have insights from friends and experts around the CX world included too. Thanks to them and to Dan for writing such a great article!

Read Dan’s Forbes article here.

Download the 2019 Live Chat Benchmark Report here.

Customer Experience, Learning & Training, Technology, Work

How to nail complex query resolution with internal knowledge bases

It’s 2019, and our contact centers are changing fast. The proliferation of new channels over recent years means that now, some 67% of customers prefer using self-service options instead of speaking with an agent.

If you started your career as an agent and remember trying hard to treat every call like it was your first despite having already heard that query ten times that day, this stat will likely have you breathing a sigh of relief. Apart from the decrease in repetition being a good thing, being there for customers on the channels that they choose is a great CX strategy. But a downside of this is that the queries which end up in our contact centers will normally be more complex.

How can we help agents better answer these complex queries? Enter the humble internal knowledge base (KB). A well-designed KB can act as a tool to help employees work better and smarter, drive continuous improvement, improve quality, and increase collaboration. Here’s how.

The right tool for the job

Back when customer queries were solved with single-sentence answers, many of us resorted to memorization, cheat sheets and post-it notes on our computer monitors to remember key pieces of information to help us in our jobs.

But this type of learning doesn’t often work well when we’re aiming to understand and resolve complex query types. The interplay of emotionally-charged interactions and multitudes of gray-area options to choose from can make decision-making a complex exercise, and it’s not always clear what the “right” thing to do is.

In these instances, providing employees with resources they can use in-the-moment to better weigh up each case and strengthen their decision-making is a smart bet. A KB can act as this type of resource, working to lessen the mental information load that employees need to bear and providing this in-the-moment support even for obscure query types.

Having ready resources isn’t just good for quick customer resolutions, but having access to the right tools for the job is central to employee engagement, which impacts productivity, satisfaction, and ultimately, churn.

You might think that a KB is good for only those black-and-white Q&As where there is a set Q and an unambiguous A, but it is possible to set up a KB to support employees in resolving subjective cases through harnessing technological options within KB platforms themselves.

Let tech do the heavy lifting

I didn’t have a KB platform at all when I built my very first internal KB. I took the HTML skills I had learned from building cringe-worthy teenage poetry websites (which, thankfully, died with Geocities), spun up a rudimentary website, got it hosted on our Intranet, embedded a Google search, and launched it with myself as the editor.

About ten years ago that seemed like a reasonable plan, given that our center had repetitive query types and processes which didn’t change much over time. Thankfully, KB platforms have developed to help us run much more robust KBs in more complex environments.

Many KBs are now much easier to maintain, without needing to duplicate information from other sources- for example, by hosting separate customer and agent-facing KBs on the same platform and optionally, updating from each other. They often come with full reporting suites for better visibility into the effectiveness of your KB. It’s even possible to embed AI into your KB so even if a user were to type in a search term that was ambiguous or unclear, the AI could pick up on the intent behind it and deliver the right article regardless.

Importantly, your KB can have multiple editors and methods for adding to it. Your agents can not only draw upon the information in a KB but also add to and comment upon it, whether through inbuilt functionality or integrations with platforms such as Slack . That’s important for complex query resolution for one main reason:

The best customer outcomes are often a collaborative effort

There’s a reason the apprenticeship model of learning has worked beautifully since the dawn of time – we learn well from others in an on-the-job setting, where we can experience and discuss work in context.

But given the nature of much contact center work, it can be difficult to implement collaborative learning processes, which by nature are social. Strictly scheduled environments often don’t allow much employee interaction to occur beyond formalized meetings, scheduled breaks or snatched chats at the water cooler.

That’s a shame, because we can often make the most sense of complex situations at work when we share them with others who have been through similar experiences and can offer different perspectives and ideas. Encouraging employees to discuss complex cases is an exercise ripe for learning, as failures and successes can be shared and learned from without each employee needing to follow the same bumpy path.

The beauty of encouraging collaboration on complex queries through a KB is that employees can interact with it in the course of their everyday work. This allows them to collaborate asynchronously, without a heavy load on agent schedules. Collaboration shouldn’t be limited only to your agent team – other teams can also be set up to view and collaborate upon cross-functional knowledge items.

This kind of process doesn’t need to start off on a formal KB platform, either. On the CX Accelerator community recently, Lauren Volpe shared a great example of collaborative learning via a CX Tracker, where team members share details of tricky cases so others can benefit.

Getting to this point may require some cultural changes to occur too. It’s important to encourage your team to view continuous improvement as a team exercise, which treasures its experts and grows its newbies, and which recognizes that it’s through sharing information (not hoarding it) that we can get our best work done.

Future-proof your contact centre’s knowledge

Let’s go back to those expert staff members for a moment. If your contact center contains a few wise sages who intuitively know the right answer to most queries, you’ll know how valuable they are, and how often they can get called upon to share their knowledge.

But you’ll also know how dangerous this can be. Reliance on a few staff as oracles of knowledge is a dangerous tactic, plunging your team into difficulties if they leave. Not to mention that in a carefully scheduled environment, allowing these seasoned staff members time to walk the floor and be available for answering questions isn’t always ideal, let alone scalable.

Great KBs can become living resources that wean reliance off those wise sages by letting knowledge loose outside of people’s heads. Plus, if you can set up your KB to be added to by everyone as they learn and discuss new queries, the information within them can become greater than anything an individual alone could convey.

KBs are the new training

In the past, most educational models were designed around the fact that information wasn’t easily accessible. To learn something new you needed to go on a training course, consult an expert, or check out a book from the library.

Times have now changed. Mobile devices and internet access mean that we and our employees don’t need to go through an extensive process of information synthesis or training to learn a new thing. Most people are pretty capable of figuring things out for themselves. We just look up information, and get things done.

Despite this, many organizations still rely on formalized training interventions to attempt to help employees to learn. Usually this consists of trainers resorting to information-stuffing strategies – for example taking employees away from their desks, attempting to fill them with as much pure information as possible, and adding in some sort of game or test to help make sure that information isn’t so easily forgotten. We’re now starting to understand how ineffective these types of methods are.

Times are changing and the way we think about contact center learning needs to change too. We need to get better at providing employees with the technology and resources they need to learn from each other and just do their jobs, no information-stuffing required.

Especially given the resource-stretched, turnover-ridden nature of the environments we operate in, many centers could achieve this by better harnessing tools like KBs – providing the conditions to learn better, smarter and quicker, even in increasingly complex environments.

Originally published here.

Customer Experience, Technology, Work

[Webinar] The Future of Live Chat in 2019

This webinar was a blast.

Jeff and I are good buddies, so it’s always fun presenting with him. However, this webinar was especially significant as it aired just before we launched Comm100’s 2019 Benchmark Report, so we got to share some sneak peeks at the stats before it was even live.

As well as discussing the findings from the latest benchmark report, we chatted about the growing pains experienced by different sizes of call centers, and gave some tips for organisations of all kinds to consider in the year ahead.

All of these insights come straight from what we’ve learned from our own customer base, so it’s useful stuff for anyone looking to align their contact center with best practice and trends in 2019.

Have a listen, and I’d love to hear what you think.

Watch the webinar recording here.

Download Comm100’s 2019 Live Chat Benchmark Report here.

Learning & Training, Technology, Work

Five Tips To Successfully Onboard Live Chat Agents

Live chat communications continue to trend upwards in importance. No surprise here. eMarketer predicts that in just one year from now, 80 percent of the world’s smartphone users will use messaging apps. We’re more connected than ever, and that provides challenges for modern sales and service organizations. Today’s online customers want and expect a fast response time to their customer service query, plus a frictionless way to initiate support.

Forrester reports that 55 percent of adults will abandon online purchases if they can’t find a quick answer to a question, with 77 percent stating that good online customer service is the most important thing a company can do for them. It’s clear that in today’s climate of consumer choice, organizations who provide support at point of sale through live chat stand to gain the most in customer loyalty and reduced cart abandonments.

Connecting with website visitors through live chat also takes less time and human resources than phone support to consumers, raising productivity and profitability. As chat agents are expected by their organizations to be valued support partners for customers and prospects, these individuals play a larger role than ever in securing overall customer satisfaction and brand equity.

For new agents, a structured onboarding program is crucial to allow organizations to ensure that they’re getting the satisfaction outcomes they seek. Not only does effective onboarding introduce employees to processes and procedures within their new role, it also builds confidence, trust and engagement at possibly the most crucial stage of their lifecycle in the organization – a stage that largely sets the tone for the rest of their employment and their interactions with customers.

Here are some tips for managers and leaders looking to build an effective live chat agent onboarding process, or refine their existing one.

1. Train to the chat platform

Chat systems tout their ease of use and turnkey nature. However, any technology tool requires time for operators to get familiar. Optimal use of tech by live chat agents is fluid and tacit, and even with the simplest of tools, it still takes time for agents to get to this level of mastery.

Make training hands-on, incorporate real-life exercises, and use training-ready versions of the platform to allow agents to roleplay and test common scenarios. Give agents time to play around on the platform and engage in practice runs before bringing them live. The last thing your agents need while tangling with customer issues is also battling the tech they use, so don’t assume they’ll just “pick it up”.

2. Establish clearly defined goals and relevant metrics

If your agents aren’t clear on what they’re supposed to achieve, they won’t be able to secure the outcomes you need. While this might sound common-sense, failing to clearly communicate expectations is a symptom of the “curse of knowledge” – where we can assume that agents know the ropes when that’s simply not the case.

The concept of “going above and beyond” is one area that’s often neglected in agent onboarding, as many see it as a basic tenet of customer service, or something that should be implicit in an agent’s personality. But it’s a hugely important area which should be explicitly covered in onboarding to be sure that your agents really are on the same page as you. For service organizations, not practicing this philosophy can spell CSat disaster– and for sales organizations, this equals leaving money on the table.

Don’t leave this to chance. Promote this concept and empower your new live chat agent to do more than just answer a visitor’s stated questions. Challenge them to always consider what other help they could provide, or what else could be useful if they were in the customer’s position.

In terms of lead generation, this “one step further” approach is especially vital. Teach agents early on how best to seek out potential lead opportunities. That means more than just pointing the customer to a white paper. They should also offer to pass them to an inside sales person for more in-depth discussions, or to a video that requires registration, for example. Giving customer service agents the authority to foster meaningful dialogue rather than focusing on how quickly chats are completed can support lead generation objectives as well.

3. Integrate them with the entire chat team

Research into learning has shown that development of knowledge in onboarding is inseparably bound to learner activity in a number of different contexts – the physical (work space), the material (tools and tech) and the social (other employees).

Because of this, social aspects of learning and working should be accounted for within effective onboarding programs. Your goal should be to help your new agent learn from other seasoned agents, and empower them to build relationships within the whole team.

Before going solo, new agents should serve time as an understudy to one of the team’s top performers to glean proven tips and tactics to successfully perform the job. Document best practices to disseminate valuable “lessons from the front line” to all agents. Establishing weekly meetings to discuss events that went well, those that didn’t and trends in the field that can turn into great teaching moments for the entire live chat team.

As a bonus, creating this kind of supportive team environment will improve the productivity and success of all agents, not just those who recently joined the company.

4. Educate agents on when to get help

A live chat agent can solve a majority of the customer service issues that come in, but they can’t act as a mouthpiece for every function within your company. Most likely, they can deal effectively with 80 percent to 90 percent of customer queries, with the extra 10 to 20 percent needing further checking, information or consultation with other teams.

That’s not a bad thing. If you try to force agents to deal with things that require too much improvisation or that the agent does not have authority to do, you will trigger negative customer interactions.

Set procedures for agents to quickly get assistance from a supporting team or team leader when issues are beyond the scope of their power or authority to resolve. Recognize that on paper, this sounds simple, but in practice this can be a lot tougher – even the most seasoned agents encounter situations they haven’t seen before, and deciding where the boundaries are isn’t always easy to define.

Focus on building supports to help your agents in their decision making, for example through a robust agent-facing KB, or through having team leaders and floor walkers readily available. Build a culture of communication which encourages agents to speak up when they’re not sure about something and discourages them from “winging it”.

Finally, make sure that whatever supports you use, they’re easy and quick for agents to access. Few things are more frustrating for a customer than spending 15 minutes on a live chat waiting for an answer because the agent doesn’t have the assistance they need at hand.

5. Utilize Technology To Support Agents

Technology is developing rapidly, and for many contact centers, shifting to new tech-focused service models comes with questions and risks. There’s sometimes a view that technology will end up reducing service quality, and some are even concerned that chatbots and AI will end up taking jobs away from humans.

This narrative is shifting as firms begin to recognize the best applications for this technology – and often, that means aiming to complement and enhance the work of human agents, not to replace them.

When used properly chatbots can provide great advantages to a new agent. The ability for bots to take on common customer queries cuts out questions which can be perceived as boring or repetitive, leaving your agents to focus only on the queries that need their help the most. This allows you to effectively upskill your agent pool as your agents develop expertise in longer and more complex queries. Agents enjoy connecting with customers, not answering repetitive questions.

Augmented intelligence is another exciting area through which agents can be provided with data which helps them to make better decisions. Through deep learning, natural language processing and multivariate analysis, companies are able to analyze more variables and more extensive data sets than is humanly possible to help agents perform better at their jobs. The goal of these systems should focus on arming humans with information they can use to engage the customer more effectively.

At RapportBoost and Comm100, we’ve frequently seen that the very best chat agents aren’t the ones who are naturally gifted at charming the customer. They’re the ones who possess superior emotional intelligence, situational awareness, defer to the algorithm in certain circumstances, plus use their instincts and experience to decide when different situations require different tactics.

The combination of human AND machine once again beats either one alone – and this is certainly an exciting prospect for anyone looking to help agents to do the best job that they can, through onboarding and beyond.

Originally published here.

Customer Experience, Technology, Work

RapportBoost.AI Interview Part 3: Live Chat Data Is the Key to QA

Here’s part 3 of my interview with Rapportboost.AI – you can access part 1 here and part 2 here.

This time, we discuss live chat data, quality assurance and how live chat contributes to the sales cycle.

The bounty of live chat data that this channel produces is the perfect tool for tracking the success of optimization. After all, with a sound live chat implementation, what matters most at the end of the day is how customers respond.

In our final installment of our Interview Series with Kaye Chapman, Customer Experience and Training Specialist at Comm100, we got down to the nitty-gritty of QA and chat conversion reporting – the proof that your live chat channel performs.

RB.AI: In instances where you are working with a customer who uses chat and then also has channels that are handled by a different company, how do you handle coming up with data metrics and reports?

KC: We are lucky in that we have a really strong reporting suite, so it can report on so many aspects of chat from the very basic stuff like chat volume to customer satisfaction to more advanced stuff like being able to see how productive agents are, how canned messages are being used, looking at survey fields within chat to see what their usage is as well as through our reporting API and various integrations connecting with other systems like CRM or ticketing. So we consistently found that clients like our reporting suite because it’s so comprehensive and it does allow clients to get the insights they need from chat and apply them to other channels as well.

Chat is a fantastic tool because you can get so many different reports and statistics from it. When you’re thinking about telephone service, for example, it can be a difficult process to actually gauge how effective a particular call has been. Some years ago, I was a quality assessor myself, and to really understand quality it was a very long process of call selection, call listening, checking a variety of different systems for customer and interaction data, marking things down on a separate scoresheet, and finally providing feedback to the employee.

With chat, it’s much easier because you can immediately see from the chat transcripts how the chat went, you have all the data regarding the customer and their satisfaction, you have all the data regarding how long the chat was, what resources were used, and how it was wrapped up. Most of the data you need to drive quality is built in, and I would say from a quality and continuous improvement point of view, chat is a fantastic tool to make those continuous improvements more easily than traditional channels.

RB.AI: I absolutely agree that live chat data can be leveraged to simplify QA. Earlier we spoke about using live chat for sales as opposed to customer support, and you mentioned Comm100’s conversion reporting tool. I’d love to hear your expertise in leveraging data to see how much chat contributes to the sales cycle.

KC: Absolutely, it’s important to have visibility over ROI from any communication channel you have. Chat Conversion reporting is an amazing tool that allows businesses to analyze live chat data to see straight away how chat is contributing to the sales cycle. Once a client has let us know what a conversion is for them, whether it’s a sale or a download or something different, we can link those conversions to chat records so it’s easy to see what agents contributed to a sale and how exactly they did that. Clients can then put processes in place to replicate those successful results, not only through agent coaching but by more automated processes such as using successful prompts in proactive chat invitations and canned messages, which can be personalized to particular customer segments. All in all, conversions reporting gives a lot of insight into exactly how chat drives the sales cycle and means that viewing the process of how chat drives sales as more of an art than a science just isn’t correct anymore.

Originally published here.

Customer Experience, Emotional Intelligence, Technology, Work

Rapportboost.AI Interview Part 2: Chat With Emotional Intelligence

Here’s part 2 of my interview with Rapportboost.AI – you can access part 1 here.

This time, we’re taking on the topic of emotional intelligence and discussing how technology can help in delivering emotionally intelligent customer interactions.

As Augmented Intelligence transforms the workforce, emotional understanding is proving to be an essential component of brands’ interactions with their customers. After discussing live chat agent training in Part One of our Interview Series, we asked Kaye Chapman, Customer Experience and Training Specialist at Comm100, to shed light on the best strategies for chatting with emotional intelligence.

RB.AI: Let’s talk about emotional intelligence. This concept is of special importance to us at RapportBoost.AI because we help brands use high-EQ to achieve increased revenues and conversions when using chat for sales. What are some measures you’ve found to be effective for chatting with a certain level of emotional intelligence?

KC: Regardless of use case, emotional intelligence is helpful for agents across the board, given that EI is such a cornerstone of effective personalization. It’s important for chat agents to be able to pick up on specific language and to understand how they need to adapt their behavior to suit that particular customer. When I’m thinking about how to promote communication in an emotionally intelligent way, one of the things I encourage agents to do is take full advantage of the canned message library and save those phrases that have been especially impactful. Make sure that there is a constant cycle of trying things, evaluating them for effectiveness, and using them in the future if they have been successful.

RB.AI: I think we are all excitedly watching conversational commerce take off and that has to do with so many things, such as making purchases through cell phones and the fact that millennials like to chat. For these reasons, do you think sales and chat will converge in the near future?

KC: I think sales and chat are already converging, and it’s exciting to see organizations using tactics like Account Based Chat to engage with key prospects – we liken it to “rolling out the red carpet” for customers by providing them with experiences that are deeply personalized. I do think conversational commerce is going to get bigger and it is going to be the thing that separates out the wheat from the chaff in terms of who does well in the future and who doesn’t.

RB.AI: Agreed. Along those lines, could you talk a little bit about channel optimization and some strategies you’ve used to optimize live chat?

KC: We advocate effective journey mapping to understand what types of customers are coming into which particular channels. We also encourage our clients to think about the concept of channel blending or channel pairing when they are planning different channel mixes, what channels they engage on, and how they can move customers from one channel to another. The idea behind channel blending or pairing is rather than thinking about channels in isolation, you can think about how to use the best aspects of different channels to form a great experience for your customer. For example, chat is fantastic for helping people with urgent issues in a synchronous way. But you can also enable knowledge base integration to live within the chat window, and clients can configure it so that customers go through the knowledge base before they hit an actual live chat agent. Now, that’s fantastic because, from a customer’s perspective, it might not be so easy to find out where a knowledge base is on a client’s website, it might be that your customer’s in a little bit of a rush, it is just that rush aspect that makes it easier for them to speak with an agent. Actually positioning the knowledge base within the chat window gives customers more choice to select a channel that suits them, and obviously, there are big bonuses there for clients as well in terms of deflecting unnecessary query types from chat.

Originally published here.

Customer Experience, Learning & Training, Technology, Work

Winning Live Chat Training for Your Customer Service Team

Implementing live chat for your customer service team might seem like a major decision—and it is!—but it is only the first step in modernizing your customer service strategy. Luckily, implementing a live chat system on your website is often pretty simple, but a tool isn’t useful if your teams aren’t trained to use it properly, and aren’t fully on board with its potential to make life easier.

Simply giving technical training on the new system and then letting your agents loose won’t prepare them adequately for the task. The agents might not be prepared enough to adapt their existing customer service knowledge to the live chat system—which could cause negative encounters with customers through misinterpreted comments, slow chats or grammar gaffes.

Because of this, it’s important to back up systems training with training focused on the experience of your live chat customers, helping your agents to understand the service impacts of your new channel. Here are five things to consider when giving effective chat support training to your team.

  1. Words, Tone and Body Language 
  2. Professional customer service agents understand that all face-to-face communication is made up of three different elements: words, tone and body language.Telephone communication can be tricky since agents can’t rely on assessing a customer’s body language to get more insight into what they’re thinking and feeling. Extra attention needs to be paid to words spoken, and the tone they’re spoken in, to accurately ‘read’ a customer. And when communicating back to customers, words and tone need to be delivered and moderated carefully in order to communicate in a clear way.Live chat presents extra challenges. Without being able to hear a customer speaking or see their body language, how can you read the subtleties of their communication to truly understand the meaning of what they’re saying? And how can you demonstrate listening and friendliness or build rapport by simply exchanging typed messages?Attention to wording here becomes absolutely crucial in allowing you to do all of this. Agents need to step up their communication a notch to consider sentence structure, word choice and conversation flow in building and assessing the intent of a communication.

    Top Tip
    : Hold a short training session introducing the Mehrabian communication model and ask your agents to consider the impacts of not having tone or body language to help them communicate. Questions to ask include: What problems could arise through relying on just words to communicate with? How could miscommunication occur? How could this be prevented?
  3. Live Chat School If you’ve ever attended a formal, ‘classroom-based’ training session, you’ll know that the most important part of learning is actually applying the knowledge you’ve learned in the workplace. Indeed, one of the most highly regarded training models there is states that as much as 70% of learning occurs through hands-on, on-the-job work, not through structured training sessions.That’s not to say there isn’t a place for formal training sessions—just that the most effective adoption of live chat expertise comes through checking and facilitating learning while your agents are using the software. Building in an extended training period after initial live chat training is a great way to give your agents the space to experiment in their approach until they are handling the software like experts.

    Top Tip
    : Introduce ‘Live Chat School’ after initial live chat training by setting standards for your team to attain, and assessing them throughout the extended training period. Once they hit targets for customer satisfaction, chat length and/or utilization, ‘graduate’ them to your regular quality assurance program.
  4. Spelling and GrammarWhen you hired your telephone-based agents, it’s unlikely that you paid much attention to their writing, spelling and grammar skills. In fact, you may have forgiven some mistakes they made on their resumes because, after all, they didn’t need top-notch writing skills.You may have held mock customer interactions with them, listening to how they sound on the telephone, their ability to reassure and assure customers through careful vocal communication.Live chat doesn’t make these skills redundant. However, it does require agents to brush up on their writing skills. Agents with sloppy writing or bad grammar reflect badly on your company, causing customers to question the abilities and professionalism of your staff.

    Top Tip
    : Hold a ‘Grammar Police’ themed quiz, testing agents on common grammatical mistakes and giving a prize to the top ‘Grammar Cop.’ Back this up by ensuring that agents have access to a style guide which sets the standard for correct spelling, capitalization, punctuation and sentence structure.
  5. Live Chat ScriptsMost telephone-based agents will have a set of standard scripts they use in conversations: for example, their greeting and closing messages to customers.Live chat as a system is unique in that any of these scripts can be added as shortcuts in the agent console, saving them time in their interactions.Live chat scripts can also be used to speed up interactions and improve quality outside of these standard scenarios—for example, by adding scripts to discuss product features without missing any key details, or for giving complete instructions on how to reset a password.It’s important for you to acknowledge how important scripts can be in increasing quality and saving time, and to give your agents the chance to think creatively about how they can develop scripts that work well for them.

    Top Tip
    : Hold a scripting workshop for your agents. Examine what scripts are already used, what scenarios new scripts could be written for and the advantages of these. Make sure to discuss potential time savings and the reduction in needing to repetitively type out the same statements for different customers.
  6. In the Live Chat Customer’s ShoesIn their telephone-based work, your agents will already be pretty clear on the factors of their service that impact the customer experience. Wait times, clarity of communication and transfers between departments are prime examples of situations which can destroy the customer experience if handled badly—or enhance the customer experience, if done really well.Live chat software presents extra situations that can either enhance or degrade your customers’ experience. The time taken to respond to a message, the use of canned responses and the ability to share screens all add new dimensions to the customer experience that you and your agents probably haven’t considered.

    Top Tip
    : Hold an ‘In their shoes’ training session. Split your agents into two groups and ask them to take the viewpoint of one of your customers. Ask one group to imagine and script the best possible customer experience that could be had while using live chat for a range of real-life scenarios. Ask the other group to script the worst experience which could be had. Once done, ask them to share and question them on their decisions: what impact do certain agent actions have on live chat? Why do these actions occur—through accident, or intent? How can they be mitigated against (if bad) or adopted (if good)?

Implementing live chat may require your existing team to stretch their skills and capabilities to adapt to new ways of communicating with your customers. Given the right tools, the right training and the right perspective, your team will continue to deliver the top-notch service your brand is known for through this rapidly growing and heavily preferred channel.

Originally published here.

Customer Experience, Learning & Training, Technology, Work

RapportBoost.AI Interview Part 1: Live Chat Agent Training Drives CX

It was awesome to have been able to spend some time chatting with Dani, Meredith and the team at RapportBoost.AI – a fantastic company working on AI and augmented intelligence for contact center agents, blending this with a strong focus on emotional intelligence.

In this interview we discuss agent training, call center customer service and AI in the contact center.

Live chat agent training is one of the most innovative spaces in today’s customer experience ecosystem. From canned responses to augmented intelligence, companies are training their live chat agents with technology more than ever before. We sat down with Kaye Chapman, Customer Experience and Training Specialist at Comm100, to talk about leveraging live chat agent training to drive customer experience and success.

RB.AI: You’re a huge advocate for implementing learning and development techniques to drive positive customer experience outcomes. Could you share some of your insights regarding effective live chat agent training?

KC: Absolutely. Effective live chat agent training has to be centered around customer needs and experiences. In the last few years, we’ve seen an incredible pace of change when it comes to the customer experience. Customer expectations are changing, new technology is being integrated into business practices and business models, and our products and offerings at Comm100 are evolving in step with the industry.

In this environment, companies need to stay agile to be able to react to customer needs. Several approaches to learning and development allow companies to do so. When helping people learn a piece of software, a golden rule of training and development that I often suggest is that live chat agents should be getting just 10% of their knowledge from formal learning experiences, 20% from colleagues, and 70% from on the job learning.

What this means for us and other vendors is it’s vital to look at a variety of different ways to help agents develop their knowledge of whatever software they’re using, not just giving initial training and relying on that to be enough. This includes making good use of knowledge bases and having a range of learning materials available for live chat agents to reference that integrate multimedia such as photos and video.

The best customer experiences are invisible – customers shouldn’t have to go out of their way to get the information they need to solve a problem, and should have ample self-serve materials at their fingertips – and the same can be said for the live chat agent’s experience of learning to use our software. We make sure they’re really well supported to be able to develop their knowledge quite organically, without much extra help being needed from us.

RB.AI: We so often think about generating a frictionless experience for the customer, but the same can be said for your customers that use live chat software, such as West Corporation, Whirlpool, and Stanford University. You want their experience of learning to use that software to be frictionless as well.

KC: That’s right.

RB.AI: When you visit a contact center, how do you assess the workspace and create a plan to provide the optimal channel ecosystem for a brand or company? I would imagine this involves a bit of specialization on a case-by-case basis.

KC: We actually don’t encourage our clients to use any particular patterns or funnel for fielding queries from multiple channels. What our platform does is support customer choice with the idea of being present whenever or wherever the visitor wants to start a chat, from any channel. We coach our clients, where possible, to let the visitor decide and not the company, which is an essential aspect of being truly customer-centric. Our platform supports multiple channels that work together with our integration of knowledge bases, social media channels, and ticketing system. We coach our clients to make use of all these resources together for a better experience for the agent and the customer as well as the use of canned messages, which help to achieve consistency and compliance of responses while reducing knowledge load for front-line agents.

RB.AI: It sounds like you’re making great strides to automate customer chat to remove the burden from the front-line agent through various technologies. I understand that Comm100 is also developing a chatbot. Could you expand on how this bot is integrated into your software environment?

KC: Chatbots are developing rapidly, their adoption is spiking, and for good reason. A correctly configured chatbot service can deflect a significant proportion of customer queries from the contact center, allowing agents to upskill and focus on the more complex questions the chatbot can’t answer.

It’s important for clients to be realistic about what exactly chatbots can handle. At the moment I’d say AI tech is capable of handling 80% of the use cases an organization would encounter. If clients are realistic about exactly what sort of queries their chatbot can handle well and the sort of training required for it to do that, chatbots can provide real cost savings for the business.

It’s good to consider that while many of us think of chatbots as being about conversations, many of the successful use cases I’ve seen involve bots undertaking transactions, such as pushing out credit card forms, confirming a customer’s account information, delivery times and the like. They can also help with resourcing, for example, when agents aren’t online chatbots can provide 24/7 coverage. Also, it’s worth considering that chatbots don’t get sick, they won’t be late for shifts, and they don’t get upset when a customer is rude – so there’s real potential there for chatbots to act as a great backup to cushion you from instances where your human agents might suffer from those issues.

One thing that’s often a concern for clients is making sure that the chatbot is well trained and it doesn’t degrade the customer experience before it improves it. A big part of what we do is working very closely with our clients to ensure chatbots are trained effectively for each business and industry, that it can be effective, it does have contextual awareness, and it’s personalized to the client’s business too.

Originally published here.

Customer Experience, Technology, Work

The Challenge of AI Voice Assistants in Customer Service

During May, Google’s I/O 2018 conference was held to show the latest in Google’s offerings to developers around the globe. While Google demonstrated a lot of different new tech at the conference, it was their keynote demonstration of its latest “Duplex” technology which has lit up the internet.

Duplex uses Google Assistant to call companies on a user’s behalf to perform simple, structured tasks, such as booking a haircut or scheduling a restaurant reservation. While voice synthesis isn’t exactly new, it was the humanlike inflections and natural conversational flow in these calls that many found to be jaw-dropping (or, alternately, terrifying).

If you haven’t yet seen Google’s demo, click through to watch it now, and prepare for your mind to be blown. (Skip to 43 seconds to get straight into the demo.)

Although this technology isn’t yet consumer-grade, Google says it will start to test Duplex within Google Assistant as early as this summer. How then should our customer service operations handle this upcoming customer-side automation in voice calls?

Identify Verification & Trust

Part of the reason why Duplex has caused so many ripples is because it gives a glimpse into a rather dystopian future – one where humans can’t tell whether they’re talking to an AI (causing many to wonder if the Turing testhas been passed by this new tech).

Before now, voice assistants haven’t been capable of holding natural-sounding conversations. But the calls demoed by Google, complete with inflections such as “Mm-hmm” or “Ah, gotcha”, sounded so lifelike that it’s clear the human operators on the other end had no idea they were speaking to an AI.

That in itself has caused outrage – with commentators pointing out that ethical problems occur when service workers and call center staff are unsuspectingly experimented on by Google’s human-sounding AIs. Google reacted to this outcry by asserting that working versions of Duplex should have the ability to identify itself built in.

But whether AIs self-identify or not, the cat’s already out of the bag for anyone considering whether their identity verification processes will need to change as a result of this technology – the answer is undoubtedly, yes. The key to how exactly processes will need to change lies in whether AIs are required to self-identify or not – whether by Google themselves, governments or any other regulatory body.

If AIs are required to self-identify themselves as such and state that they’re acting on behalf of a human, should agents be responding to their wishes as if they were that human? I can easily envisage scenarios where AIs can eventually make payments, change data or perform any other process that has impacts on customer or company – only for the customer to respond that the AI’s actions were a mistake and not authorized by them. How then can we determine human intent behind the actions of an AI?

If AIs are not required to self-identify, issues emerge around trust and standards. As it stands, technology like Duplex is only effective in a limited range of scenarios, making it easy to ask a question that sits outside of the AI’s programming to test whether it’s a robot or not (for example, “Who is the president of the United States?”)

Having agents ask these types of questions to try to weed out the “robots” from the humans is reasonably straightforward. But how will those questions evolve as AIs get smarter? Will they constitute a new, more intrusive layer of data protection processes that we have to subject unsuspecting customers to? What happens then when we speak to human customers who cannot answer these questions – through health issues, a lack of shared cultural understanding, or anything else? Could we be dooming them to be treated like little more than unfeeling robots?

Emotion & Empathy

Speaking of feelings, Duplex brings big questions as to what will constitute effective customer service in the future. Our current, human-focused model of optimal customer experience runs on the premise that if you focus on solving problems quickly, accurately and in a friendly manner, you’re likely to achieve good customer outcomes.

But AIs don’t feel. All the niceties and small talk in the world don’t matter to them. Considering that humans and AIs have different needs and priorities during issue resolution, we could see two distinct sets of standards emerge.

The first relates to service standards for humans – and as beings who have thought and felt in much the same way for thousands of years, I can’t see these undergoing any huge revolution in the future.

But a second set of service standards relates to how we can provide optimal service to AIs. I can see these standards relating to focusing on clear language, accurately clarifying intent, and decreasing emotionality in speech which could cause confusion to an AI – quite the opposite of the emotion-centered training we’ve been giving to front-line agents for decades.

Taking Humans Out of Interactions

Thinking about the role of our front-line customer service agents in the potential applications of this technology, we must consider the messages that Google is implicitly sending about the service employees customers speak to every day to get things done.

PC Magazine sums this up deftly: the implicit message embedded within Duplex is that there’s no need for customers to ‘suffer’ through speaking to service employees to get things done. In one of Duplex’s demonstrations, the lady taking the call has a thick accent that is a little difficult to understand. The AI handles this with little awkwardness, making it clear that even in service situations that can be tricky for customers, machines can handle this instead, removing all of the ‘bother’.

I still believe that human interaction and emotion is what humanizes our brands, and makes them friendly and accessible. And putting myself in the shoes of my agents, there’s something that stings about the implicit message within AI-driven voice calls – that other people see talking to them as a waste of their time.

But I do believe that the best kind of customer service is invisible, that is, mediated through access to a range of easy self-service and digital options available to prevent customers from needing to make inconvenient phone calls. Maybe then we need to focus less on the perceived value of individual interactions, and think instead about downsides of the phone as a communication channel that have caused Duplex to become a customer need.

Phone Calls as Inconvenience

The development of Duplex points to an issue innate in customer service operations – and that is, while phone calls are often the best way for a customer to accomplish a goal, they aren’t always convenient. The rise of live chat, self-service and social messaging channel options has happened as a result of this issue. These channels allow more customers to connect with organizations in ways that don’t take up all of their time or attention, require them to take time out of their day, or prevent them from multitasking while they solve problems with organizations.

The necessity of Duplex (and its positive reception by many) shows that while many organizations see cost or effort barriers to providing service over non-voice channels, clearly for some customers that isn’t good enough. Given that organizations such as Deloitte predict volume of voice interactions to businesses to fall from 64% of all channel communications in 2017 to 47% in 2019, organizations need to consider better ways to connect with their customers than by relying on voice-centric service models.

Automation promises to hold the key to dismantling these cost and effort barriers to multichannel service, as we’re now seeing within Chatbot uptake by firms big and small all over the world. While we’ve been exploring Duplex as a tool for customers to take advantage of automation in their own lives, let’s look at what the impacts are when the tables are turned and organizations can use tools like Duplex to evolve and improve their service offerings in a multichannel climate.

What if Duplex Could Help Organizations?

In the spirit of Moore’s law, it’s feasible to consider that given the current pace of technological advancement, and as a privately-owned company, Google will be looking for other ways to apply this technology, helping them to profit from it and secure its future development.

Because of this, I predict that it won’t be long at all until AIs like Duplex are pitched as a replacement for customer service agents on voice channels.

We can already see the evolution from human-led to AI-led service within other channels. Chatbot services are now handling a good percentage of everyday organizational queries over live chat. Considering that studies show that it’s realistic to aim to deflect between 40% – 80% of common customer service inquiries to chatbots, the same deflection principles could be used to help technology like Duplex to drive the same change for voice.

For voice as a channel, the closest thing we have to this right now is the dreaded IVR. The difference between IVR and AIs, however, is in the promise of service that truly helps, rather than hinders. While IVR is almost universally viewed as an unwelcome hurdle to jump on the way to service from a human agent, chatbots are proving that for certain service scenarios, AI can be as efficient as humans – if not more so, due to their speed, constant availability and scalability.

Projecting the development of this technology for voice interactions within the contact center, we’re faced with some questions. What types of voice queries are ripe for automation, and how can we channel these to AIs in a way that doesn’t add more options to a traditional IVR? What happens when customers can’t tell whether a voice agent is human or an AI? Whether that AI self-identifies or not, how does that reflect on our companies? Could we even be ushered into an age of universal mistrust in customer service where our human agents are treated badly by customers, as if they were robots, because our customers just can’t tell the difference?

Perhaps exploring automation within live chat can throw some light on these questions. I’ve seen many organizations who are meeting these issues head-on within chat – and many are digging deep into customer needs and preferences to harness this technology in ways that are both comfortable for their customers, and effective for their businesses.

A Values-Centered Approach to Automation in Customer Service

Now is the time to reflect on how our businesses will handle customer-side automation coming this year, and how more organizations can handle automation-related issues generally as technology develops.

We can take the lead from design ethicists such as Joe Edelman to consider how best to work with this technology in a way that doesn’t result in negative outcomes for our businesses, our agents or our customers.

Edelman proposes a values-centered approach to the design of social spaces online, and by using this same philosophy, we can consider how AI voice assistants detract from or complements the values of customers and other stakeholders interacting with it. Whether it’s us or the customer who’s automating, great service design will come from a consideration of not only what each party aims to achieve but also how their service preferences are denied or accommodated.

When we can consider the values of our customers and our employees, and how those interface with the needs of our businesses, we can start to use this technology in ways that are helpful and useful to them, morally sound, and which deliver the time and resource benefits that both businesses and customers want.

Originally published here.