Deliver psychic customer service with predictive analytics

In customer service, knowledge is powerful. In American Express’ 2014 Customer Service Barometer, 99% of customers said that getting a satisfactory answer or being connected to a knowledgeable agent was an important part of a great customer service experience.

Unfortunately, expectations don’t always match reality. A Dimension Data report found that one of the top three reasons first contact resolution (FCR) is dropping is because of a lack of knowledge. But that’s not to say customers aren’t getting knowledgeable service—it just may not be a human they’re getting it from.

Psychic customer service

Customers want a service experience that knows who they are and what they want. Luckily, companies can figure out just that using predictive analytics, which anticipates how customers will interact with a brand and what decisions they’ll make regarding purchases.

Several big brands are providing the “psychic” experience customers want using the power of predictive analytics:

  • Netflix—The popular streaming service provides TV and movie recommendations using an algorithm based on users’ rating histories. According to a ConversionXL article, they also look at other factors, such as “when did a customer pause, how many times did she pause, what was the color of the movie title that attracted the customer, etc.”
  • Gmail—Google’s proprietary email service presents you with targeted offers based on the content of the emails you’ve received. This “automated processing” shows you offers it thinks you’ll find interesting, but you can still report those messages as spam if they’re not relevant.
  • Amazon—Everyone’s favorite online retailer displays items that they think pair well with what you’re currently looking at. They reference factors like customers’ past purchases, items they’ve rated, purchases compared to other customers, and even items sitting in virtual shopping carts.

The best part about these recommendations and predictive analytics is that they’re automated—customers can view options quickly and easily and self-serve, something 40% of customers would prefer to do. These services anticipate what customers want before they even know it themselves, saving your company time while still making sure customers get the information they need.

Granted, the companies listed above are big organizations with a lot of resources at their disposal, and access to the latest and greatest technology. But you’re likely already collecting data on customers, whether it’s their name, email, or the company they work for. So what are some ways you can start using that customer information to deliver a smarter automated service experience?

Using predictive analytics in customer service

There are a number of ways your business can start using predictive analytics in customer service, including but not limited to:

  • Recommendations/Upsell— There’s a reason the companies listed above provide recommendations: to make life easier for customers. If you know what items your customers have been browsing, you can use predictive analytics to offer up items you think they’ll like, saving them the time it would take to have to search through items manually. Just don’t go too overboard with recommendations—Target learned this the hard way by sending a twenty-something customer pregnancy-related coupons based on her purchases before she even knew she was pregnant.
  • Reminders—Customers may forget things, but that doesn’t mean your business should drop the ball. If you’re a company that provides medical equipment, for instance, your customers may forget to reorder on time. But by using predictive analytics to determine when they’ll run out of supplies, you can send targeted recommendations that arrive at just the right time. This way, your customer stays healthy, and your business makes a transaction that would have been forgotten otherwise.
  • Retention—Studies have shown that a 5% increase in customer retention can increase profits by 25 to 95%. If customers aren’t opening your emails or haven’t interacted with your brand in a while, you can use predictive analytics to schedule outbound communications that reengage them on a channel they prefer.

Conclusion

It’s not hard to get started with predictive analytics—companies like IBM offer great predictive analytics services, and partner companies allow you to incorporate their intelligence over channels like voice and SMS. We predict your customers just might love it.

Truly effortless self-service: The future of proactive customer support

Self-service has an inherent flaw: Effort. What would you do with all of the time and energy you’d save if you didn’t have to stop working to diagnose and resolve issues? The next evolution of self-service shifts that effort from customers and technical support staff to proactive technologies.

Today, self-service requires a lot of effort

phone-and-coffeePicture yourself as a system administrator managing an enterprise-wide application.  A business leader contacts you to report concerns that have been impacting the productivity of his staff for a week. This sets off a time-consuming process of investigation and diagnostics. You could search a vendor’s support web site to find articles related to your condition or post to a community forum, but if all else fails, you’re calling the vendor for help. Depending on the complexity of the application and problem, this can take hours, days, or weeks of work. Work that takes you away from more important activities. Meanwhile, the business leader who’s having the issue is losing money, and becoming frustrated with you and the vendor. Value erosion is growing by the minute as productivity is lost.

…But there’s a brighter future

In the next generation of self-service, you’re still that system administrator. You wake up in the morning and an app on your phone tells you that the enterprise system is experiencing performance degradation. The app sends you a knowledge base article with details on the problem and lets you know that a self-healing fix is expected to resolve the issue within the hour. A Service Request has already been opened for follow-up and the system will report back at the end of the day if the fix has been successful. Since the performance degradation has been identified before it becomes a truly impacting problem, the problem will resolve itself before the business leaders lose any productivity. The system itself is doing the heavy lifting, so instead of performing manual diagnostics or researching fixes, you can finish your first cup of coffee.

Internet of Things technologies, data analytics/machine learning, and robust knowledge capture best practices are making a new proactive support engagement model a reality, transforming the technology support industry. In this new proactive model, the “voice of the product” will be the communication mechanism to vendors and manufacturers. Rich data streams will provide real-time information about assets. Analytics and machine learning technologies will identify immediate problems, trends, and patterns to knowledge in the form of recommendations, solutions, benchmarks, and self-healing fixes.

When resolutions are not already known, proactive service requests will be initiated, kicking off an investigation by the vendor’s support staff, and notifying the customer of its progress. All of this value can be delivered back to the asset or customer proactively through any number of communication channels.  A loop that automatically identifies a problem, matches it to a solution or service request, and provides that solution with little to no human interaction is now complete.

Further insight

promo_Mar31-2016_blogThis proactive support experience becomes a competitive advantage for the customer through dramatic productivity and product efficiency gains. Machine to machine communication and auto correction are becoming a reality and will be the backbone of tomorrow’s support organization.

On March 31, I’ll a part of an expert panel featuring Jordi Torras, Founder and CEO of Inbenta, and Melissa Burch, Knowledge Strategist with Irrevo, for a webinar titled Preparing for the Next Evolution of Self-Service. Join us for a deeper dive into how self-service will evolve, and hear actionable strategies that will help you future-proof your self-service experience.

Scaling your customer success program: 4 goal-setting tips for Customer Success Managers

This post is a part of our Customer Success series written by Francoise Tourniaire and follows the last post about segmenting customers. You can read the first post in the series here and the post about scalable methods for customer success here.

This time, we turn to the issue of how to structure goals for customer success managers (CSMs). If you are a CSM and your manager has not set formal goals for you, keep reading! You will be able to suggest meaningful goals for yourself.

1. Match the goals to the mission of the customer success organization

Customer success has five big jobs: onboarding, monitoring customers’ health, retaining customers, upselling, and of course advocating for customers. Goals and objectives for CSMs will depend on the balance between the five.

ft_onboard-advocate

Most customer success organizations focus on onboarding, monitoring, and retention, as discussed in steps 2 and 3. If your organization owns converting prospects, or is in a situation not covered in steps 2 and 3, read step 4 as well.

(Goals for the important role of advocate are usually carried by the manager of the team rather than by the CSMs.)

2. Goals for Onboarding

Customer success teams often choose to have onboarding specialists, whose goal it is to help customers adopt the product quickly through a series of training sessions, guidance to tailor the service, and adoption campaigns. The goals of onboarding specialists usually focus on the number and speed of onboarding projects. It is even better to measure the success of the onboarding projects. Were customers satisfied with the training and coaching? Did they correctly complete the assessment instruments (if any)? Did they manage to use the product without requiring additional assists from support or the CSM?

Onboarding specialists may receive a bonus based on achievement of their goals, or sometimes a fixed compensation.

3. Goals for Retention & Expansion

The goals of CSMs that are not pure onboarding specialists are sometimes based on customer satisfaction (as measured by a periodic survey) but are almost always driven by customer retention. There are many ways to measure retention so the computation mechanism matters, a lot. It can either be:

new MRR / old MRR

or

renewed MRR / MRR up for renewal

The first formula includes upgrades (expansion revenue); the second does not. This is an important distinction. If the goals include expansion sales, CSMs may neglect smaller customers who are unlikely to expand—and that may be just what you want. If not, either use a pure retention goal (i.e. use the second formula) or set two goals, one for retention and one for expansion. Set targets based on historical data, with careful uplifts added each quarter.

Note that neither formula relies on the activities that CSMs perform (onboarding sessions, QBRs, regular updates), only the results of the activities.

CSMs’ compensation usually includes a base and a significant bonus based on retention and/or expansion. (CSMs do not normally receive a commission, which is reserved for sales reps.)

4: Special Cases

Startups

In startups with no reliable history of renewals, it’s often difficult to set meaningful individual retention targets. Instead, use a group target, with the added benefit that group targets promote teamwork. (It’s not a bad idea to give CSMs both an individual and a group target, even in established teams, as recognition of the importance of teamwork.)

When Customer Success is all about Sales

If CSMs are deployed mainly to convert prospects or to push expansion purchases, their goal should be based on conversions (and their compensation may well be in the form of commissions.)

When Account Segments Behave Differently

Large accounts tend to renew at much higher rates than smaller accounts, regardless of the industry. New accounts churn a lot more than established accounts. And “at-risk” accounts, those that demand the most effort, are much more likely to churn.

If all CSMs handle a variety of accounts, no problem: you can set the same goals and the same targets for everyone. But if they specialize the CSMs by customer segment, take the mix into consideration. For instance, the retention goal for “at risk” CSMs may be only 50% while for others the target is 90%.


Francoise Tourniaire is the founder of FT Works and co-founder of ChurnSquad.  Both companies provide consulting, training, and coaching to create and improve customer success initiatives. Her latest book, The Art of Support, provides guidance for both customer success and support executives. Contact Francoise at FT@ftworks.com or 650 559 9826 for more information.

Customer Experience 2015: A year in review

looking-back-2015

As we tie a bow on 2015 and look forward to 2016, we can’t help but observe that the landscape of the customer service industry has changed. Customer support organizations are becoming more customer-centric, and with that, have adopted a more targeted approach to improving the customer experience.

We’ve asked a few experts to share their thoughts on how customer experience has evolved over the last twelve months:

Melissa Burch, Knowledge Strategist, Irrevo

The demand for a cohesive experience from pre-sales through to post sale has never been higher. Prospective customers and existing customers both demand the ability to find the information they need to make buying decisions and help themselves use products more effectively. To meet that demand, everyone inside the company has to work together to deliver relevant and timely information needed throughout the entire customer lifecycle.

Rich Weborg, CEO, OneReach

Today’s customer experience is 24/7, part of a multilingual, multichannel, multi-location world. There’s more data available around user preferences and how they interact with your business. In addition, there are better tools handling better interactions, so data is easier to manage. We’re creating customer experiences based on real-life data, and it’s easier to design them than it used to be. Customer data is integrated across multiple channels. Automation has also allowed for more proactive customer experiences, helping customers before they ask for it. In addition, smarter interactions based on artificial intelligence-type analysis.
But with all these innovations, it’s become somewhat harder to manage the customer experience. Customers expect a consistent experience across channels, so companies need to be able to deliver. Another challenge is that there’s more opportunities to expose yourself to criticisms; it’s harder to hide behind bad UX.

Tim Whiting, VP of Marketing, Opinionlab

In 2015, true omnichannel customer engagement arrived with an exclamation point as evidenced by the domination of mobile retail interaction during Cyber Five. Viewing consistent cross-channel customer experience (CX) as a competitive differentiator gave way to customer’s expecting consistent cross-channel CX as market parity and looking for CX innovation.  We enter 2016 with omnichannel CX established as the new battleground for customer acquisition and loyalty.

Laurel Poertner, Knowledge Strategist, Irrevo

The customer experience landscape this year is all about ME.  That is, how well do you really know “ME” as your customer?  On-line and in-person experiences alike, the more personalized, preemptive and on-demand you can make an interaction, the higher the value it will have.

The bar for quality customer experiences was raised in 2015, and the next twelve months will see even more evolution. Check out our recent webinar, The 5 Knowledge Trends that will Reshape Customer Experience in 2016 to learn how you can stay ahead of your customers’ expectations.

 

Customer Success, Part 2: 4 Methods for creating a scalable Customer Success program

This guest post by Francoise Tourniaire is the second in a series that takes an in-depth look into creating a successful Customer Success program. You can catch up with Part 1, Setting the stage for customer success, and Part 3, How segmentation delivers value to customers – and your business


high-touch_low-touchThe traditional idea of customer success is the ever-friendly customer success manager who gets customers set up and comfortable with the tool and checks that all is well on a regular basis, bringing interesting suggestions to improve the customer experience. Sounds lovely, right? But it’s expensive.

It’s expensive because it is a high-touch process: the customer interacts with a human being (the customer success manager), in a 1:1 interaction. In contrast, a low-touch process uses alternatives that allow customers to get what they need with fewer 1:1 human interactions, instead using self-service or group interactions for most of the activities.

Clearly a low-touch customer success process is less expensive, and easier to scale, but can it deliver equivalent results for customer retention? This second blog post of our customer success series shows how low-touch, low-cost alternatives to the high-touch, high-cost, traditional model of customer success can deliver results both for onboarding customers and for ongoing retention efforts.

Leveraging Self-Service

It would be difficult to conceive of a customer success process that is purely self-service, but it is very effective to mix self-service activities with personalized check-ins. Here are three ways to make use of self-service:

  • Online training. This can be short videos, recorded webinars, or full-blown computer-based training if you can provide it.
  • Onboarding plan. Giving customers a list of steps and activities to set up the system minimizes confusion and suggests a firm schedule. It can be delivered in self-service, group settings, and also
  • Just-in-time hints. Customers usually follow a predictable path, which makes it possible to deliver helpful hints, ideally in product, as they start using new features for instance.

Leveraging Group Delivery

Many customer success activities can be done with a group of customers rather than with just one customer. Customers get the warmth of a human interaction but at a much lower cost to the organization.

  • Welcome call. The welcome call introduces customers to the onboarding process and can be a small-group affair, scheduled a few times a week to accommodate several customers at once.
  • Live webinars are great training tools and perfectly appropriate if customers all use the system in a similar manner. They can apply to product training or best practices sharing.
  • Online communities. Communities are helpful for all customers. Consider maintaining a separate forum just for new customers, whose concerns may not match established customers’.

Leveraging Big Data

Mining customer data can help you understand patterns so you can deploy better tools and specific customer success strategies as needed to rescue at-risk customers.

  • Health monitoring. Although not foolproof, customer usage is a telling sign of successful adoption. Customers that are not using the tool at all, or using it lightly or incompletely can be flagged for intervention.
  • Churn analysis. While health monitoring focuses mostly on usage patterns, churn analysis evaluates a holistic set of data across customers to detect patterns of defection – which become opportunities for action. Don’t delay churn analysis until your data is “perfect”: start with what you have, and build up over time.

Leveraging Repeatable Processes

Even when you must use a high-touch approach, a repeatable process improves efficiency and consistency.

  • Scripted onboarding. Rather than asking the onboarding specialists to create a custom program for each customer, script the sequence, ideally by customer segment.
  • Adoption campaign kits. Help customers train and motivate their internal users with pre-packaged materials and suggestions. This can be a pure self-service item, or be a part of a program driven by a customer service manager.
  • Responsive support. What is support doing in a customer success checklist? Well, we would not want customer success to be nothing more than an escalation channel, would we?
  • Business environment tracking. Just like support organizations capture their customers’ technical environments to expedite troubleshooting, customer success organizations should have a structured method to capture relevant features of their customers’ business environments.
  • Targeted, scripted check-ins. Equip the customer success managers with a reason and script to contact customers. Use the outcome of health monitoring data (see next paragraph) to trigger the contacts rather the calendar, at least for lower-value customers.

The high-touch model of customer success is wonderful – for key customers. By leveraging self-service, group delivery, big data, and repeatable processes, you can deliver excellent low-touch services to most customers so you can lavish high-touch services on key or at-risk customers. Tell us how you deploy low-touch programs.


Francoise Tourniaire is the founder of FT Works and co-founder of ChurnSquad. Both companies provide consulting, training, and coaching to create and improve customer success initiatives. Her most recent book, The Art of Support: A Blueprint for Customer Success and Support Organizations, is now available on Amazon. Contact Francoise at FT@ftworks.com or 650 559 9826 for more information.

Customer Success, Part 1: Setting the Stage for Customer Success

This guest post by Francoise Tourniaire is the first in a series that takes an in-depth look into creating a successful Customer Success program. The series continues in Part 2, Creating a Scalable Customer Success Program, and Part 3, How segmentation delivers value to customers – and your business

What is Customer Success?

The idea of customer success is that appropriate nurturing yields loyal customers, which in turn yield profits. Customer success aims to:

  • Increase customer adoption, which leads to
  • Increase customer retention, which leads to
  • Reduce customer churn and
  • Increase expansion revenue

Customer success is the brainchild of SaaS vendors, but the approach and techniques can apply to all organizations.

What Does Customer Success Consist Of?

Customer success organizations provide a range of services, which can be organized in five categories:

  • Onboarding to help customers get started with the vendor’s product or service. Onboarding is more than pure training: it also helps customers navigate the setup and customization of the tool. Onboarding occurs at the beginning of the customer lifecycle, but it can continue as customer usage expands, new users are added, and existing users discover more sophisticated uses of the product or service.
  • Customer health monitoring. This includes monitoring the usage of the tool as well as ongoing communications with customers.
  • Retention. If a customer is determined to be at risk, specific initiatives may be deployed to rescue the relationship, from a simple conversation to touch base with the customer to offering additional training or adoption assistance.
  • Lead generation. Customer success organizations diligently cultivate leads from existing customers, usually passing them on to the sales team, but sometimes closing them themselves. Some customer success organizations also own the renewals of subscriptions and maintenance contracts.
  • Customer advocacy. Providing structured feedback from customers to internal teams is an important function of customer success organizations.

Are All Customer Success Organizations Alike?

No! Customer success organizations have a variety of roles. Differences are common in these four areas:

  • Whether they own the onboarding This is usually the case, sometimes through a specialized subgroup. For complex products and services that require a professional services team, onboarding may still exist in the form of encouraging users to engage with the platforms.
  • Whether they are responsible for technical support. Usually not, especially for more complex products: a separate team handles technical questions. But customer success managers are sometimes asked to provide first-level support.
  • Whether they are directly responsible for renewals. Usually, a dedicated renewals team or the sales team itself takes responsibility for renewals (assuming renewals are not automated), although the customer success organization is often measured by the renewals percentage.
  • How much selling they do. Most influence and suggest, but do not have a sales quota, so as to minimize conflicts of interest with customers and channel conflicts with the sales team.

How Do I Get Started With Customer Success?

If you are starting from scratch, the first step is to identify your main issue: do customers never start to use your products? Do they start, but then lose interest? Do they fail to renew? Fail to expand? Or do you simply not track any metrics?

Focus your initial efforts to resolving your main issue. Perhaps it’s simply starting to measure retention (or its mirror image, churn).  Or it may be putting in place a robust onboarding program so customers can get started in an orderly manner. Or analyzing the reasons why customers fail to renew.

Make sure that the initial efforts are proactive, not just aimed at preventing customer escalations. Escalation management is important, but it is a support function, not a customer success function.

In our follow-up posts, we will show you how to segment customers and how to define reusable processes for onboarding and retention.


Francoise Tourniaire is the founder of FT Works and co-founder of ChurnSquad. Both companies provide consulting, training, and coaching to create and improve customer success initiatives. Her most recent book, The Art of Support: A Blueprint for Customer Success and Support Organizations, is now available on Amazon. Contact Francoise at FT@ftworks.com or 650 559 9826 for more information.

Cognitive Engagement: The Future of Customer Experience

The future of customer engagement will be run by a machine.  That is what Forrester predicts for the near future.  Kate Leggett of Forrester states that one of the top trends for 2015 will be that “organizations will look at ways to reduce the manual overhead of traditional knowledge management for customer service.  In doing so, they will explore cognitive engagement solutions — interactive computing systems that use artificial intelligence to collect information, automatically build models of understanding and inference, and communicate in natural ways.”

robot_csrEarlier this year, IBM launched the Watson Engagement Advisor.  It is one of the first of its kind to pave the way for a new way to engage customers.  It “via cognitive computing intellect, can proactively engage with a business’ customers, and continuously learn from interactions, anytime and anywhere, providing fast, more accurate and personalized interactions”.  IBM Watson was the computer that beat former grand-champions on the TV quiz show Jeopardy!.

Where to invest and focus

Obviously not all companies will have IBM Watson in their arsenal to interact with customers providing them with immediate answers to their complex purchasing questions and problem resolutions.  However, many have 2015 goals to solve problems faster and improve relationships with their customers.  Adding artificial intelligence to your self-service website or as an internal tool for agents will transform how companies engage with customers.  As products become more and more complex and the amount of information available grows, the need to hone in on an answer quickly proves increasingly difficult through manual means.  A dialog takes up valuable time to try and get to the right response.  Self-searching can be frustrating if you don’t use the right terminology or give up easily.  The effort the customer has to make using artificial intelligence is greatly reduced and answers are available in a fraction of a second.  It is as if they have their own personal assistant there to answer their questions. It will also allow companies to expand this assistance across multiple channels.

Preparing Your Knowledge Data

The effects of using Cognitive Computing is already leading consumers to demand a new level of engagement and interaction from companies.  One way to help prepare systems for this new capability is to make sure new knowledge is coming in.  Without the data (or knowledge), there won’t be anything to cull through to hand off to customers.  Still some human intervention is needed.  New knowledge needs to be created in order for it to be used by customers and agents.  This will be especially important as companies invest in cognitive engagement systems and start to find that the speed and accuracy of the answers correlate directly to the amount of knowledge within the system.

Make sure processes are in place

Finding ways to focus on the new problems should be part of any knowledge program.  Whether it be analyzing which knowledge base articles are used frequently and exposing them, communicating and training customers on how to find articles on the known issues, or making changes to products that remove the issue completely. Make sure your knowledge program has these processes in place to focus resources on creating new knowledge.

Let the system do the work

The way to evolve how you engage with customers is to reduce the effort they must make to interact with your company. Artificial Intelligence allows a cognitive system to cull through big data for relevant responses while taking into account the nuances of human language.  While there will always be a need for the human touch in solving customers’ problems, the key is to focus on the new problems.  Let the computers take on the ones that already have an answer and can find it a whole lot faster.

 

Metrics that Matter: Going Beyond CSAT and NPS

analytics_groupIf you’re behind the Customer Service Operations curtain in any capacity, you’ve got strong feelings about which metrics tell the most comprehensive, actionable story of your customer experience. It’s easy to fall into a routine of looking at only a few of the heavy-hitting metrics, but to get a clear picture of your organization’s performance, it’s important to ask yourself what stories you might be missing out on by overlooking some of the alternatives to perennial favorites like CSAT and NPS.

We asked a few experts in the customer experience industry to tell us a little about their favorite metrics:

 

Melissa Burch, Senior Knowledge Strategist, Irrevo

I am a huge proponent of using a balanced scorecard approach to measurements with a small number of critical data points to monitor.  If you talk to me long enough, you will realize that I don’t recommend narrowing your measurement scope to just one data point.  However, there is one measurement that is often left off a balanced scorecard and this is the one where you measure and calculate your self-service success score.  Our friends at Oracle recently shared their approach to this.  I’ve summarized it here and encourage you to learn and then apply the measurement approach that works for you.

To do this, you need two data points to derive your success score.  The first data point is the number of times customers visit your support site and view at least one piece of information there. Don’t forget to include content, community forums and all other self-service options provided.  These are the total number of times your customers attempted self-service for the time period of your calculation.

The second piece of information is the self-service success rate. This is calculated based on data captured during the customer support site survey which asks users if they were successful at finding the information they were looking for.  The response to this customer survey question will give you your success rate.

Once you have these two data points, you can calculate your customer self-service success score by multiplying the number of self-service attempts by the success rate to determine your overall success score.  So for example, if your customers attempt to self service 1,000 times per month and you know that they are successful 50% of the time, then you have a self-service success score of 500.  This means that your self-service support offerings provided customers what they needed 500 times during that month.

After establishing your baseline self-service success score, identify ways to improve the self-service offerings in ways that drive greater value to your customers.  Use the self-service success score to monitor your impacts.

Tola Begbaaji, Discrete ERP Customer Solutions, Aptean

I don’t know that there is one metric. For me it is a triad – a combination of customer satisfaction, time to resolve, and time to respond. Put another way – customers want Q2R.  Quick, quality, resolution.  If a team is resolving issues quickly with quality, then typically their customers are satisfied. Each element is important.  A resolution is not just an answer to the ticket.  It is something that resolves their problem. It’s not enough to be quick. Speed is irrelevant when the solution is not high quality.  Quality of course speaks for itself, but the term implies completeness and thoroughness.

These three metrics help you to evaluate whether a support team is providing quick, quality resolutions on a regular basis. If the issues are being resolved quickly with quality, then customer satisfaction will tend to be high.  You can review the trends of time of respond and time to resolve to see if they are staying steady or if they are increasing or decreasing. For example, if time to resolve and time to respond are increasing, you will expect to see a corresponding decline in CSat.  If you don’t see this CSat decline, then it is a warning sign that the team may have a huge backlog, and they are only closing primarily the newest tickets.

So, in order to make the triad into one metric, I might call it something like CSaTimeToResolveRespond.  That would make a nice hashtag, don’t you think?  #csatimetoresolverespond

Laurel Poertner, Knowledge Strategist, Irrevo

A tried and true metric that gets a lot of attention from C level executives is Customer Satisfaction.  While I think this metric has its place in the corporate world, I believe it is short sighted and customer loyalty depicts the customer landscape for an organization much more clearly.  Customer loyalty, defined as the customer’s intention to keep doing business with the company, increase the amount they spend, or spread positive word of mouth can be measured by using the Customer Effort Score (CES).  CES asks the question “How much effort did you personally have to put forth to handle your request?” The reason this is such an important metric is the power it has to predict your customers’ intentions.  The more you can see what is coming the more time you have to prepare your organization to head off future issues.  This can also spur companies to implement new systems and processes to use the CES to make improvements that directly impact the customer experience and ultimately drive higher customer loyalty.

Elias Parker, Managing Partner, OneReach

There are a lot of call center metrics out there that measure customer satisfaction—CSAT, Net Promoter Score (NPS), even First Call Resolution (FCR). The way they measure satisfaction is different, but the end result is the same—to make sure the customer is happy. But what if I told you there was a call center metric that could do nothing but measure a customer’s happiness, one that tracked their satisfaction through every interaction? There is, and it’s called the Smiley Face Index (SFI).

The Smiley Face Index isn’t meant to displace other more complex call center metrics.  Rather, it’s just the simpler way of looking at customer satisfaction that we sometimes need. It literally measures the number of smiley faces exchanged by a customer and agent during a web-chat or text message interaction. Simply put, more smiley faces = more happy customers.

Learn more about the Smiley Face Index.

Matt Berger, Content Strategist, MindTouch

The one metric that support teams can’t ignore (but so many do) is organic web traffic – the measure of how many people find your help content through Google. On the surface, this seems to fall into the marketing realm, but organic web traffic will help turn support from a cost center into a revenue generator. Support teams are always looking to lower support costs by reducing customer effort and increasing ticket deflection. Our customers see a distinct correlation between increased organic web traffic and ticket deflection: more web traffic means fewer tickets, which in turn means lower support costs. By analyzing the amount of traffic, as well as the demographic, geographic, and behavioral data around that traffic, support teams can continue to fine-tune the self-service experience.

Our customers have also noticed that opening help content to the online public has the added benefit of bringing buyers to this information. Web traffic analytics can help inform sales and marketing teams about buyer behavior. Those little FAQs you thought you had to produce are the key to understanding how to better serve both buyers and customers. Through online self-service, support teams aren’t just supporting current customers, they’re supporting the buyer’s presale experience as well.

Learn more about how organic web traffic supports your business goals.

Introducing #KMCXchat: A Knowledge Management & Customer Experience Tweetchat

Support content is at the heart of the customer experience. It fuels every customer touchpoint, from call centers to social support to self-service. That’s why we’ve created #KMCXchat, an open conversation on Twitter where experts from both fields discuss the intersection of Customer Experience and Knowledge Management.

Join us on September 24th at 2pm Eastern for this tweetchat.

Topic: Metrics & Content: Working together to improve the customer experience.

We’ll be joined by our co-moderator, @OneReach.

What’s a tweet chat?

A tweetchat is an online discussion on Twitter that focuses on a particular theme. Anyone with a Twitter account and an opinion is free to join the discussion by tweeting responses to messages that use the hashtag #KMCXchat

They’re a great way to learn from experts in related fields who have the same goals in mind. Also, they’re fun!

How do I participate?

On September 24th, at 2pm Eastern, search for #KMCXchat on Twitter. Many folks find it easier to use a tool like Hootsuite or Tweetchat.com to track mentions of our hashtag. When you see a tweet that sparks your interest, chime in with your own tweet.

Don’t forget to follow us on Twitter to hear more about our upcoming events!

 

 

Customer Journey Mapping & Customer Effort: Your Questions, Expert Answers

Our recent webinar, Journey Mapping 101: Reduce Customer Effort and Improve Customer Experience, covered key points on how to create a customer journey map, and related that to a reduction in customer effort and improvements to the customer experience.  We had a large, passionate audience, so it’s no surprise we couldn’t get to all of the questions during our Q&A period.

In this series of posts, our Senior Knowledge Consultant, Melissa Burch, and David Kay, Principal of DB Kay & Associates, take on some of the insightful questions asked by our audience.

Q: What are some tips/tricks to help us figure out how to quantify customer effort?

Melissa: I think examples are the best way to share tips and tricks. So, let’s assume you want to quantify the effort it takes to log a web-based help request/service request.  You could quantify on several variables including: number of minutes it takes, number of clicks it takes, number of questions asked, and number of screens presented.  Establish a consistent scoring mechanism that you use to translate the raw data into a scoring sheet.  Then, as you watch a user complete the task, capture the data for each question.  After the user is finished, translate the raw data to the scoring sheet to arrive at your overall effort score for that task.  It would probably be helpful to watch a few internal testers to make sure that you don’t observe another data point that you would like to capture.

Q: Who are the right people to have in the room to do a customer experience journey map?

David: The most important people in the room are the ones who actually do the work—interacting on-stage with customers, and implementing processes backstage.  While it’s great to have managers involved as well, we find that managers often know the theory of how things are *supposed* to work, and how things work in the real world can be significantly different.  Of course, you also want a cross-functional group that can speak to the end-to-end process we’re mapping.

Q: How do we pick which journeys to map?

David: This is one of the most interesting parts of a journey mapping workshop.  You want journeys that are “just right.”  Too broad, like the complete end-to-end customer lifecycle, doesn’t let you get into enough details to learn much of anything important.  On the other hand, journeys that are too narrow are likely to miss out on important key moments of truth, which often happen in the hand-off between groups or processes.  In general, look for a journeys that are a single experience for the customer (even if it lasts weeks or months), but which involve cross-functional efforts on your end.

Q: We really need to give more attention to our customer effort.  Where do you recommend we start?

Melissa: Begin by reviewing the data your customers have already provided.  This likely will be in various formats but when reviewed as a whole, will give you some ideas on how to address customer experience opportunities. Perhaps there are already teams who look at it, but chances are they are reviewing it with a specific purpose in mind.  I recommend you look at it with a wider lens to help identify and quantify some specific pain points. After getting armed with data, present your recommendations to the executive sponsor.  Then, we recommend you move forward and gather data to quantify observations. The data is required to help prioritize and focus efforts.

Further insight

If you missed the live broadcast, you can watch a recording of this webinar.

Stay tuned to the Irrevo blog for more Q&A from this session, and follow us on Twitter to be the first to know when we share new posts.