How to not respond to customers

Reply target

Recently I had the need to contact a company for support concerning a feature they removed from one of their product which I, and many other users, sound extremely valuable. Despite it being a free service, the support team responded on a weekend in time that would put most enterprise vendors to shame. However, the content of their message left a lot to be desired:

Thank you for contacting us!

Personally, I’m glad you brought this out. At […], we are constantly working to improve our platform and products. Suggestions from […] like you are an incredibly important part of that process. Updates can be done without notice, we will keep you informed if we make an update on our platform. We want you to know how much we appreciate your input and support!

Parsing this message, we find a number of items for improvement:

  • They start by saying “Personally, I’m glad” – but this is not a personal matter, I am interested in the company’s position, not the agent’s personal opinion
  • Then “At […], we are constantly working to improve our platform and products” – in this case they made a change that has negative impact on the customer experience, in the opinion of a large number users
  • Then “Suggestions from […] like you are an incredibly important part of that process.” – First, this is a general statement that has no bearing on anything, and second, I did not make a “suggestion”, I pointed out a change that’s making it harder for me to use the product
  • Followed by “Updates can be done without notice, we will keep you informed if we make an update on our platform.” – which is a plain contradiction
  • And the concluding sentence is “We want you to know how much we appreciate your input and support!” after doing everything to show that they don’t

This vendor, with a single response, managed to transform an otherwise satisfied customer with a product problem into a skeptical customer, questioning their commitment and willingness to provide service. Analyzing how this happened leads us to several conclusions:

  • Being too familiar and personal, with phrases like “personally” and “I’m glad”
  • Using phrases that sound good but have very little to do with the situation
  • Using feel good language as a substitute to meaningful information

Do your response templates suffer from similar problems or are you making it every individual person’s responsibility to produce their own customer responses? Have you ever read those responses with a critical eye? Or, even better, ask someone else to do that? If you service customers in multiple countries and cultures, are you aware of the differences in perception between those and your native culture?

Update: while writing this post I received a message from the vendor:

I’ve passed your message to our engineering team and will be better able to help with your particular question. ou will receive a more detailed reply shortly; we appreciate your patience!

Which sounded like good news, until the following message arrived a day or two later:

Hi there,

We’re experiencing an extremely high volume of support requests currently and may not be able to directly answer every question received. Please browse our […] Help Center […] for articles that may help you resolve your issue, as it provides a lot of solutions to common issues reported by our learners.

If you have been able to answer your question in the last few days, there’s no need to reply to this message. If you have not been able to find your answer and still need assistance from us, please reply to this email and we’ll get an answer to you as soon as we can.

Thank you for your understanding as we continue to improve our support resources to help […] like you!
Coursera Community Operations

Many companies have challenges handling growth, this one seems to do a particularly bad job at acknowledging it and taking the actions required.

I’ll post further updates when, and if, they are received

How to create a partner support program

Business men in a hurry run & walk on time clocks

The blog has discussed in the past some aspects of partner eco-systems on support, mostly focused on the motivations of the two sides and the business relations between them. Recently I had the opportunity to discuss support oriented partner programs and the basic building blocks that make them successful. This post, therefore, will focus more on the operational sides of creating a partner program

Companies have different classes of 3rd parties acting as intermediaries between them and some, or all, of their customers. These 3rd parties are sometimes called distributors, OEMs, channel partners, VARs, and more. From a support perspective, however, we are mostly interested in two classes of partners – those who support their own customers and those who do not. In this post we’ll focus on the first group, and we’ll use the term partners for simplicity

Building a successful partner support program requires consideration of four specific points:

  • Which partners should participate – entry criteria
  • What does the company require from the partners
  • what does the company provide to partners in the program
  • What does the company do to ensure partners continue to deliver and what to do if they do not

To join the support program, partners should qualify in several levels:

  • Infrastructure – having a case tracking system, or using the company’s system. Phone access to support staff, ability to recreate customer problems, etc.
  • People – the partner must have dedicated, well trained people to address customer cases. Routing customer calls to services or pre-sales staff in the field is not an acceptable substitute

Members of the partners support program should be expected to provide a certain level of technical expertise and deflect a considerable number of cases before escalating the balance to the vendor’s support organization. It is important to remember that some cases might slip through the net. But, overall the proportion of simple cases that can be resolved via the knowledge base, problem recreation and other relatively simple activities should be much lower than those received from direct customers

Partners are an extension of the company’s support organization and as such their ability to successfully support their customers is key to their customers’ satisfaction with the products as well as propensity to renew their support and maintenance contracts. The company must therefore ensure partners have access to as many information resources as possible, from internal and external knowledge bases through customer cases all the way to training and more. When given access to customer cases then customer identity should not be shown to the partner staff

To ensure that partners continue to deliver the expected service levels to their customers, companies must think of developing a relationship that borrows some elements from the customer success discipline. For example, a periodic business review, where metrics are reviewed and an open discussion of what works and what doesn’t, and most importantly, how to capitalize on the positives and fix the negatives

In short, a successful partner program treats the partners as an extension of the company to ensure its success rather than ignore them, or even worse, create an adversarial relationship

How to not ask for feedback

Earlier this week I had the chance to participate in a seminar. It was an interesting day in a beautiful location, and lunch was provided. Part of lunch a bag of chips which contained this text:


It’s possible the manufacturer had every intention to solicit all feedback from customers. But, my first reaction was “what number should I call if I don’t love your chips?”

I am sure many of us have similar stories about such interactions, from the car dealership asking us to “fill the survey only if we can give them 9 or 10, otherwise call the manager” to this bag of chips. While these are amusing stories they have a valuable lesson – you get what you ask for, and if all you want is positive feedback that’s what you are most likely to get.

Having said that, let’s remind ourselves of the value in customer feedback. First, and usually the case of these entertaining messages, is reconfirmation – we’d like the customers to confirm for us that we are doing a good job. Second, and most importantly, is that systematic customer feedback helps us understand where our operation is failing to deliver the expected product or service. If we don’t solicit that feedback we’ll never get it and eventually lose to those who do and continue to improve their operation based on that.

Minimalistic Surveys?

Green hexadecimal computer code fading to the right

Recently I had to contact Coursera support to ask a question. A day later I received an email message asking for my impressions:


Clicking on the link in the message takes the user to a text box for additional comments.

Given my interest in surveys, and using them for insight and improvement, I found this message thought provoking. There are several benefits to using such a short survey:

  • Reduce survey fatigue – fewer questions will drive higher response rate
  • Binary choice – customers’ opinion is very clear

However, there are a few downsides to this type of survey:

  • Lacking nuance – gaining improvement insights from a single binary choice requires extensive additional processing and analysis to correlate results with operational metrics. Lack of rigorous analysis will drive over reliance on text comments
  • Interpretation bias – reading text comments in an attempt to gain systemic insight presents a danger of several biases. Eloquent comments will naturally be given more weight, and comments in foreign languages depend on the availability of someone who can read and translate them

With these points considered, can enterprise technology companies enjoy the benefits of shorter surveys without sacrificing the quality of insight produced? To answer that, we need to look at two distinct points:

  • What’s the shortest survey that will provide the information required to gain insights into the most beneficial improvements?
  • Can the company analyze text comments and maximize information gained out of those?

Finally, how can companies make shorter surveys work?

I believe that in order for these surveys to work well and provide meaningful insights several conditions must be fulfilled:

  • Sufficient volume of cases and responses
  • A wealth of operational data to correlate to survey responses
  • Rigorous analytic process, including text analysis (remember your non English speaking customers), and no, reading the comments for broader insights is not rigorous

Observations on Customer Experience Improvement

Good Better Best Keys Represent Ratings And Improvement

Just came across a very interesting article courtesy of McKinsey Quarterly‘s Classics mailing, discussing the need to optimize service delivered to customers needs. While it focuses on consumer businesses there are a few key learnings for enterprise technology support operations, demonstrated by this quote:

“Finding these savings requires rigor in customer experience analytics: […]. It also requires a willingness to question long-held internal beliefs reinforced through repetition by upper management. The executive in charge of the customer experience needs to have the courage to raise these questions, along with the instinct to look for ways to self-fund customer experience improvements.”

The McKinsey article identifies two main drivers of resistance to implementing effective improvements:

  • Organizational momentum and deep held, but often misplaced, beliefs. Frequently these beliefs are shared across management levels, causing the company to operate with ineffective goals that remain unchallenged
  • Lack of both rigorous analysis as well as the ability to present those results convincingly and effectively

A future post will discuss analytics techniques. Here I’d like to focus on a few causes preventing organizations from progressing towards effective and efficient improvements and combine a few of the blog’s previous posts for the benefit of new readers. First, we previously had a high level discussion of several differences between consumer and enterprise support, namely the different roles we interact with and the many more opportunities for friction.

We also wrote about complexity and volume. This is a very useful distinction, touching on the operational differences between high volume/low complexity operations and those with low volume/high complexity, as most enterprise support operations are.

Having said that, we frequently find concepts and metrics from consumer businesses that are not beneficial for the unique challenges of supporting enterprise technology. It becomes our job to educate the organization and provide deep, actionable insights to help the company excel efficiently. We’ll cover that in future posts

No Free Lunches, or How To Reduce Case Life

Clock and calendar

A few weeks ago I had an interesting discussion with a senior executive in an enterprise technology company. That person started his career as a support engineer, and at that time one of his main measurable objectives was case life – the average amount of elapsed time between opening and closing of cases in his ownership. His impression, at the time and even now, was that the only way in which he could impact that goal was to close cases prematurely. Presumably this was not the intended result of this goal.

That discussion opened the door for two questions: can case life be a valuable metric for managing support organizations, and if so, how can it be used in a meaningful and productive manner?

Case life, when we think of it, is an aggregate metric combining a variety of activities taking place throughout the case life, and many times more than once. Each activity has, therefore, a double impact on case life, first by its elapsed time, and second through repetition which, in turn, offers opportunities for improvement exist both by reducing the time each element takes, and by eliminating as many repetitions as possible.

When we examine the most common elements of a case life and analyze the influences on elapsed time and drivers of repetition we find that most of the time spent on a case is comprised of waiting for one of three activities to take place:

  • Producing problem documentation
  • Investigating the problem
  • Implementing a fix and verifying its effectiveness

We also know that for each of these activities we can reduce the time they take to perform, and the number of iterations required to bring them to completion. For example, producing the documentation required to investigate a problem will be much faster and require fewer repetitions when the documentation is generated automatically when the problem occurs for the first time. Having to wait for the problem to recur and then rely on verbal instructions from the support engineer will invariably create errors and require repeated attempts to get right. But, high impact changes require higher investment in tools or in the product.

If we map the options for reducing case life according to their complexity and anticipated impact, we’ll see something similar to the following chart, where the activities that impact case life the most are also those that requires the largest investment and involve higher levels of the organization:

Case Life Elements2

Taking all this into account, we can conclude that the ability of the support engineer to influence case life is relatively small and depends on their ability to manage the customer interaction efficiently and effectively. But, the bigger impact will be driven by higher investment and greater organizational focus on the various drivers.

Having reviewed this we can now answer the questions we initially posed:

  1. Is case life a valuable metric for the support organization?
  2. Should it be used to measure the support engineer?

The answer to the first question is a resounding yes. Case life, the way it develops over time and its composition gives us unique insight into the performance of the organization, helps us gauge the success of past actions and outline future development plans. On the other hand, measuring support engineers on case life is probably unproductive, and is likely to drive the behaviors discussed in the first paragraph. It is better to measure engineers on the specific element each needs to improve, and especially those they can directly influence

Autoupdate Anyone?

radiation warning sign

I recently wrote a post asking Are Your Technology and Policy Aligned? Today I came across this story about a German basketball team and the fallout when the laptop controlling their scoreboard decided to upgrade itself at the most inopportune time, begging the question of vendor responsibilities vs. those of the customer

There are several options vendors and customers can choose from. These range from fully automated to fully manual, with one or two additional options mid-range, such as alert only, or alert with automatic download and user controlled install. How should vendors and customers navigate these options and what criteria should be used for their decisions?

To answer, we need to understand the business and technology risks associated with the decision. For example, most of us would think that updating the anti-virus signature file on our PC is trivial and are happy to let that happen in the background. On the other hand, even this very low risk update taking place at the same time as an extremely critical process would not be acceptable to some users. Vendors, therefore, have to offer their customers a variety of choices they can adapt to their needs. Even more importantly, vendors have to repeatedly educate their customers on the risks and benefits of their choices

Customers, on the other hand, should understand their options and the impact of choices, and the resulting risks they are taking. For example, relying on a single laptop to run a mission critical application is probably not the smartest thing anyone can do. That same laptop could have failed for a variety of other reasons, from hard drive crash to power supply failure. The only reason this event received press coverage is the timing it chose to update itself.

Lastly, I mentioned this post to a friend, his response was a link to this video:

Basic Concepts of Six Sigma

Six Sigma Blue Stripes Horizontal

I recently came across a post titled Using Six Sigma to Improve Customer Experience and Service. As it touches on several topics close to my heart I read it with great anticipation and sadly even greater disappointment.

Since I feel the author misses the basic concepts of six sigma and the many improvement opportunities it offers support and services organizations I decided to attempt and correct some of the misconceptions and offer a different perspective to some of the points discussed.

First and most obviously missing is the fact that six-sigma is an iterative improvement process. DMAIC, therefore, is circular as shown in the chart attached to the original post rather than being a one time linear activity, at the end of which is the six-sigma nirvana stage of 3.4 defects per million.

Second, the statistical concepts behind six-sigma are never mentioned, nor is the meaning of 3.4 defects per million opportunities (known as DPMO). Here is a brief explanation. Sigma is a measure of spread of a normally distributed population, and measures the number of standard deviations fitting within a certain range. That range, in turn, is the acceptable performance range, so performance within that range is considered good, and outside of it is bad. To achieve one sigma, for example, about 68% of the population must be within the acceptable performance range, for two sigma, 95.5%, and so on, as shown below:

Sigma ValuePercentage Within Range

The last item I’d like to touch on is the need to make quality improvement, six sigma or otherwise, an inclusive initiative. It should ensure each and every employee understands the improvement process and expected results, and is able to make contributions.

Obviously, it is not possible to increase sigma levels by going through the phases of DMAIC without transforming service delivery, and it is extremely unlikely that a single journey through DMAIC will take you into six sigma performance levels. However, the benefits of improvement, even from one sigma to two sigma are enormous. So, the value in six sigma is in the journey and in creating the continuous improvement culture rather than reaching the elusive ultimate destination.

How To Follow Up On Your Survey Results

Fill in the customer satisfaction survey

Recently I have seen a number of discussions and posts discussing ways to follow-up on NPS surveys. Strangely, the writers seem to focus on transforming NPS, which is a quantitative survey with rigorous interpretation methodology into a qualitative interview, where insights are gained from reading customers’ comments or follow-up interviews to ‘drill down’ for the reasons behind the ratings. This accentuates the challenge with NPS results being non-actionable, and poses several additional problems we must think about and offer other methods to supplement the ratings.

First, let’s discuss the reasons for not using comments and interviews for extra insights from surveys:

  1. Sample size is always a concern for surveys. Comments are not always filled by customers, therefore the sample size is further reduced
  2. The manual nature of interviews will inevitably make scalability and cost a concern, further reducing sample size
  3. With global operations, language and time zones may eliminate a portion of the customers due to your inability to conduct interviews or correctly interpret comments
  4. Confirmation bias, where interviewers and comment readers only account for responses that confirm existing concepts, may pose a significant threat to the success of the survey program
  5. Discrepancies between comments and actual drivers of dissatisfaction are well documented. Relying on comments only will prevent you from confirming the comments via metrics

Now, should you read survey comments, or interview customers who rate you poorly? Absolutely, but do not confuse that for your main insights. Comments and interviews provide illustration to the broader conclusion you derive from researching the details of the survey and correlating them with your operational and demographic information.

So, how should you go about analyzing the responses from your NPS survey in greater detail?

First, by all means, call your customers back to follow up on survey results. Call those who rate you poorly, as well as those who rate you well. But, also correlate the results with demographic and operational data. For example, how does score vary across regions or industries? Do customers using a certain feature or function rate better or worse than others? Does your score vary based on support case count or their duration? How do events over time impact customers’ score? Last, and equally important, remember that non-responsive customers do that for a reason as well. Can you identify different factors that drive customers’ response rate? Does any of that indicate their propensity to renew, or churn?

In conclusion, go ahead and experiment with your customer survey results and the drivers behind them. Do not assume that what works for others will necessary work for you. If you have access to a person with statistics knowledge seek their help in building a regression model that identifies the impact of each factor on customer satisfaction. If you don’t, there’s much you can do on your own to analyze the results and understand your company’s specific environment and reach conclusions on what to improve next.

Process Mining and Customer Support

Coal Miner Pump Fist With Pick Ax Retro

Recent months have been busy investigating the Process Mining discipline and its potential applications in enterprise technology support. A relatively recent discipline, Process Mining uses advanced analytics techniques to analyze logs from various systems and identify process flows and various other parameters parameters. The Process Mining Manifesto defines it as follows:

Process mining is a discipline positioned at the crossroads of computational intelligence, data mining, and process modeling and analysis. The idea of process mining is to discover, monitor and improve real processes by extracting knowledge from the event logs produced as part of on-going business activity.

At this point you may ask yourself what problem Process Mining will solve for you. To help answer this question I’ve created a short powerpoint presentation:

Most process driven organizations go about implementing their processes and the IT systems that support them in a manner that creates a disconnect between the process model as designed and implemented into the organization and the IT system on one side, and the ‘real life’ process as eventually used by the organization on the other.

Implemented correctly, Process Mining helps us answer two questions. First, what’s my organization doing? and second, how different is that to the prescribed process? We can then identify discrepancies and problems, isolate their root causes and take action to change either the model or the way it’s executed.

Customer support departments are very disciplined in recording all activities and interactions in a CRM system, which makes them prime candidates for Process Mining investigation.

How does process mining work? There are several commercial and open-source tools that will process your CRM’s log files and produce a chart of the executed process. Some will also allow you to filter for the most common paths, the longest process steps and bottlenecks. Contact us for more details and further information.