“20M Px experiences so far”
“30% better CSAT scores with Px-powered chat over voice for the same queues”
These are not random numbers. They prove beyond doubt that predictive interactions create experiential loyalty. These figures tell us that customers who try Wow!px (an interactive guide that helps customers complete their online journeys with both self-service and chat) on their own the first time consistently like it and come back for more. The more they use it the more they like it. Customers aren’t forced to use it by a deepening of IVR menus that frustrate, or a lack of agent availability or a message that redirects them from the phone to the web. The guided journey is much like one in uncharted territory but with a trusted navigator (who knows the lay of the land like the back of their hand) by your side. That’s what brings them back, simply a love for the navigator we call Wow!px.
Businesses continue to dabble in various new strategies to turn negative experiences into positive ones, especially in the online and social media world. Yet, here we are, right where it all begins, nipping ‘negatives’ in the bud, delighting customers and clients and surprising ourselves with results that have blown away all our expectations. In the words of our Chief Client Officer, Kathy Juve, ‘Is this for real? This is way beyond all my expectations. Wow! I love the numbers!’. Yeah, that’s right about how all of us feel. As we continue to innovate and improve our solution architecture, our confidence in making you all go, ‘Wow’ now toys with the line that sets apart overconfidence and it’s soberer counterpart. But who cares, eh?
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This is the second of three posts that offer insight into what makes ‘chat’ click. Please look up our post about ‘Performance‘ and how it plays it’s part in ‘chat success’.
We talked about the significance of ‘Performance‘ a while back when we started the three-part blog post titled “Getting chat right with Px“. Today, we revisit the subject to delve deeper into what makes chat work as we talk about ‘Experience’ and why it’s so crucial to a successful chat program.
2008 - 2009: Enter, the recession.
Cut to 2010: Enter the post-recession customer. Demanding, vocal, in control and armed with the power to be heard and responded to.
Social media has done for customers what the internet alone did not – an amplification of voices that weren’t heard before. With consumers empowered to make episodes of bad consumer experiences go viral, businesses are determined to find a way to capture, control and deliver positive customer experiences everywhere. Add the expansion of the online experience over mobile applications for tablets and smart phones, and what emerges is a need for companies to deliver the ‘Wow’ factor with efficient, effective and well-differentiated experiences across media.
Think about it. A consumer’s online and frustrated with the lack of info they are looking for on your website. What’s the most natural course of action for them? Switch tabs to Twitter and go, ‘XYZ’s site sucks! Can’t find anything about Billing and Payments’. Anything that’s done after this rant is only damage control and reactive service.
Well, here’s an idea. Why not stop the customer from switching tabs and venting in the first place by helping them right when they need it most? ‘How?’, you ask. ‘Predictive chat’, we say.
Analyzing tons of online consumer behavior data in the background are predictive systems powering ‘predictive chat’. Soon as the system recognizes a point of failure on your website, the self-serve-slash-chat assistant pops-up, containing the customer on the web and preventing a negative tweet. Compare this scenario to one without any ‘magic’ happening on your website. Customer gets online, gets frustrated, gets on to Twitter, tweets, you tweet back, ask him to call you guys, he calls you and gets a resolution. You see how customer experience is higher with chat? No long hold-times, no frustrating call queues and instant solution to problems. That’s not all, though. Chat offers learning opportunities that simply aren’t available in voice. For example, It’s possible to mine not only structured data, but unstructured data such as chat transactions. These reveal ‘tones’ (words that indicate emotion) that work their way into quality monitoring and assessment, and in the long run, contribute to continuous improvement and better CSAT.
Another thing that’s possible with chat is the integration of real time customer feedback into QA forms. Unlike voice, where QA forms are parametric and unable to reflect customer sentiment. Chat, on the other hand, has interactive QA forms that score sessions based on what the customer said plus what the agent did or didn’t say or do. You see how that might play out really well for CSAT?
Leveraging the data and results from all of these previous interactions lets chat agents understand customer issues even before they arise. When an agent cuts to the chase, customers are pleasantly surprised that they don’t have to over-explain their issues (and can avoid the frustration it brings). Better interactivity owed to co-browsing and URL pushing adds to the already pleasant experience and fast resolution with the very first contact. All of this equals high positive CSAT every step of the way.
When was the last time you felt like you were on the hunt for an elusive treasure in uncharted territories? I had a real adventure not long ago when I tried to find out what the GFDL charge was on my credit card. 20 minutes and what seemed like a million clicks later, I felt like I was trapped in an uncrackable riddle each time, the ’search’ tab, which I thought was there to help me, responded to my query with an even more challenging one. Made me wonder, is this what the bank intended? I don’t think so.
A lot of the companies we deal with today encourage customers to help themselves online. They even promote it when you call them: ‘Please visit us at www.ourwebsite.com for a truly interactive and fulfilling experience.‘ Sound familiar? And, honestly, like many of you, I prefer to avoid calls and help myself online as much as possible.
I am all for businesses using self-service as a customer interaction channel. I think it’s innovative as well as cost-effective. A noble idea that would translate into noble experiences and happy customers IF self-service did what it was supposed to. Kind of a big IF right there. Instead, it too often contributes to the downward spiral which does no good to Customer Experience and Loyalty programs.
Traditionally, self-service has been a set of pages with DIY-steps aimed at basic problem resolution from the company’s point of view. To me, that is the fundamental flaw in the process because it usually involves an exhaustive search that all too often ends with a call to the contact center. Why? Because these pages don’t enable complete resolution, even with fairly common issues. For instance, how difficult is it to tell me, when I am looking for a resolution to a billing problem, that there were changes to tax rates on services that were behind the extra $5.99 on my bill? Should be easy, right?
Online self-service has a high adoption rate, which has expanded with the smart phone invasion. Sadly though, higher adoption hasn’t really translated into ‘meets or exceeds customer expectations’, primarily because customers have to wade through page after page in the FAQ wilderness instead of being guided along the journey.
Predictive technology is changing that. Google’s predictive search is immensely popular. Predictive self-service not only guides you to resolution, but surprises you with intelligent insights. Here’s an example of what has been achieved and can be replicated across the board. Let’s say you are a registered user (who isn’t?). You log in and navigate to the “Help” page of a website. Smart self-service tracks your journey on the site, matches it with data that it already has about you and predicts the purpose of your visit to deliver a customized FAQ that identifies the top three questions that might be on your mind. How cool is that!
I hear you go, “No, way!” No, c’mon! Yes, way! We’re doing it, we’ve done it and no one’s stopping us from doing it all over again.
A prediction-based platform that studies customer behavior on the web and combines it with available customer information makes it really easy for it to read your mind. Advanced analytics push the limits by sorting through available albeit generic content to deliver responses that are relevant and personalized to you, creating an ambience of a company making the “Help” page live up to its name.
What gives? Shorter customer journeys, predictive and customized FAQs, quicker problem resolution, single-channel interaction, reduction in calls to support centers and the oh-so-elusive happy customer! Again, it’s obvious.
Predictive Experiences delivered by Predictive Experience Solutions is the name of the game and it’s revolutionizing self-service before it turns into no-service.
Businesses have hopped onto the ‘chat’ bandwagon, drawn by the channel’s potential to offer fast, easy, high quality customer service at lower costs, and consumer interest in online interactions. These are all the right reasons, but results have been mixed; the majority of companies and their customers aren’t thrilled with chat, and, as a result, it’s usually less than 2% and even large chat operations are typically less than 10% of a company’s agent-led interactions.
A few companies though, are transforming their interaction mix with Predictive Solutions that have increased chat to more than 20% of their agent interactions and reduced cost-per-contact. Goes a long way to show that chat is a great service channel on the web, on smart phones and tablets like the iPad, provided it is done right and done smart. We have talked about the haves and the have-nots for chat for customer service before and we have identified the three pillars of chat success - Performance, Experience and Volume Conversion. Today, we’ll talk about Performance.
Performance - “I will see you and I will raise you 15%”
“My customer is happy calling me and we have great CSAT and FCR. Will chat be able to match the standard of performance we see with voice?”, asked the VP of Customer Service for a large retail business during a recent discussion about ‘chat’s viability’ on LinkedIn.
The answer is, ‘Yes’. While ‘flavorless chat’ programs - a combination of chat utility software and agents who can type - are limited in scope, Px solutions that blend self-service and chat can outperform voice by as much as 15% on FCR and CSAT. “Unbelievable”, you say? It’s true. Figure out what your customers want, route them to the right service, and hire the right agents. We compare flavorless proactive chat and Px chat solutions below to show you how the latter scores over the former.
Proactive chat often results in a ‘close window’ because the chat pop-up on the screen isn’t powered by any real idea of what the customer wants. Px chat analyzes visitors’ clickstreams, mines data collected during previous visits and interactions by any particular customer and in combination with other factors, determines the reason for the current visit. When the customer is invited to interact, the opening line is not, “Hi, how may I help you today?” but rather, “Hi, is your query about the extra $16 on your bill this month?”. Prediction reduces Average Handle Time (AHT) and improves and adds significantly to CSAT.
Px solutions also connect a customer with the ‘right’ agent, depending on what the system understands about the customers’ web behavior. For the more complex queries, tenured agents with high CSAT and FCR scores are connected to the customer while newbies are allowed to gain experience with simpler queries to begin with. This ‘right customer-right agent’ approach is the key driver for high FCR scores that we’ve seen with chat over voice. FCR is also improved by transactional data mining that identifies repetitive issues. Quick identification of such issues lets you address them with back-end changes to your systems, proper training for newbies, on-the-floor coaching for live agents and effective use of knowledge bases across the board.
The qualities that make a good voice agent - managing a series of one-on-one conversations - don’t work in the chat center where more than one interaction is managed at the same time by an agent. We know from our own experience during the early days of chat just how true this is. The hiring profiles of a great chat agent are fundamentally different from those of a great voice agent. Agent morale and performance will suffer - and so will customer service - if the right agents (and corresponding training, supervision and coaching) aren’t in place.
The bottom line is it’s hard to get performance from a flavorless chat pipe and agents but it’s easy to drive and measure performance with prediction.
We’ll talk about Experience and Volume Conversion in the sequels. Let us know what you think and what has or hasn’t worked for you in the Comments below.
Any guesses? Customer experience wins hands down. While ‘customer experience’ as a business priority is nothing new, it is the change in the rank order of customer experience versus cost that is. Just two years ago, when Global 1000 executives in the US and UK were asked to name their number one priority, the two words that came up consistently were “cost reduction”.
This year, the priorities shifted. Cost is still a high priority, but companies have realized that it has to be balanced with outcomes, especially where customer experience is concerned. More and more of the same executives have begun to emphasize customer experience as a company priority.
So what changed and why? When cutting costs triggers consumer dissatisfaction, it leads to consumer attrition which hurts the business and can lead to a downward spiral. Not surprisingly, a recent survey revealed that, even now, the average consumer is willing to spend more with a company that gives better customer service but “companies aren’t doing enough to earn their business”, feel two-thirds of those surveyed.
This brought about a change in the methods of measuring customer satisfaction, new customer experience scorecards, and the introduction of new initiatives to deliver a better experience to the end customer. Some are scrutinizing their outsourcing strategies to determine if a return to captive centers can provide better customer experiences.
Whether it is creating an app for the iPad (or any other smart phone for that matter) or introducing in-house retail experience, companies are focused on delivering more and better to the customer. Some of these cost money, but businesses are conscious that in the long term these measures will deliver sustained value and will open up greater opportunities for innovation around customer experience. The game has just begun.
Is chat an effective and efficient customer interaction channel for customer service? Absolutely yes. However while chat adoption for customer service is healthy the leverage of chat as a strong service channel is not so. There are many myths on chat. Consequently its effectiveness as an alternative channel to voice gets constantly questioned by both adopters of chat as well as by those who have not yet adopted chat.
Some of the common myths are that cost per contact in chat is more expensive than phone, customer experience and first contact resolution in chat is lower than voice and that it is not possible to reduce phone volumes through chat. All these myths have some common underlying realities. One, the common approach to implementing service chat has either been a technology or as a website experiment, through small pilots to evaluate the ROI and other benefits compared to voice. Second is the low awareness levels on how to leverage and grow chat as a service channel.
Consider this. 90% of customer service chat experiments/ pilots fail to produce the desired results within 4 to 6 months despite choosing a best in class chat technology. Chat cannot be tested as a technology or a website experiment. Running a customer service chat is not about putting a button chat on the website and seeing if customers click to chat or creating simple rules for targeting website visitors. Creating effective chat interactions requires deeper understanding of consumer contact behavior across channels, segmenting, targeting and driving smart interactions that can avoid potential calls from the website.
Secondly, most chat pilots start with less than 10-15 agents, with the expectation that it can be grown once the ROI is proved. This is a recipe for disaster. Such a small pilot cannot decisively prove anything vs voice and it is guaranteed not to get any executive attention especially in large contact centers. Chat programs need to start with an optimum number of agents that is modeled based on contact volumes using analytics. Growing the chat volumes requires an integrated execution of the analytical models with sophisticated operations. In addition chat also needs to be run as a unique channel without trying to lift and shift practices from voice operations. Many chat pilots start with tenured voice agents under the assumption that tenured voice agents have the product/ process knowledge and would be the best fit for a pilot. Incorrect. Chat operations require different skill sets, personality types that impact performance and productivity.
In effect running a service chat program effectively to produce significant results needs to be done with the vision to make the service transformation happen, backed by executive commitment and with a clear project plan that is not restricted to pilots. It is a science and not an experiment in art. And only few companies that have truly succeeded in transforming their service operations have cracked the code.
Are opinions on social media a lead indicator for CSAT? Absolutely yes. With millions of opinions expressed on social media sites such as Twitter/ Facebook everyday it has become a reality today. For example as a company we analyse tweets about several companies through 247tweetview (http://www.247tweetview.com) and when we compare the sentiments expressed by consumers with the end customer CSAT for our clients there is a clear pattern. Companies do not need to wait for a survey to be done/ analyse it and then figure out their CSAT scores are good or bad. The moment of truth is happening every minute/ every day.
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Customer Satisfaction Surveys have become the default to measure how content customers are. By nature, CSATs tend to be reactive; they measure the satisfaction of customers long after the customers and the business have completed their interactions.
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According to industry sources, an aggregate view of customer contacts and channel mix in the United States of America across major industry verticals (The US Contact Center Operational Review, 2nd Edition, 2008) shows that 89% of all contacts are served by the phone channel either through a live agent (65%) or through automated solutions (14%) such as Interactive Voice Response (IVR) or speech recognition. This data only considers “customer-company” interactions and excludes web based self-service and peer-to-peer interactions through social media/community forums/blogs whose growing impact in providing resolutions to customer service issues has not been satisfactorily estimated till date.
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The power of N=1, R=G has become very relevant in the Web 2.0 world, where a lot of end customer data is accessible and can be used to customize the experience for every individual visiting an online site, as opposed to the traditional retail model. The R=G part is an ecosystem.
In brick-and-mortar stores, traditionally, a lot of analysis was done to segment and drive the right traffic to the store, followed by advanced merchandising and pricing methods to drive up sales. However, in the new 1-to-1 online world, we are more advanced in how every movement of the visitor to a store can tracked.
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