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Posts tagged with ‘Voice of Customer’

How Employee Satisfaction Correlates to Customer Experience

Pharaoh's teamMany customer experience practitioners stress the importance of employee participation in companies’ customer-centricity efforts. Intuitively, it is hard to disagree with the anecdotes they tell and conclusions they draw from these stories. There are numerous studies that attempt to connect employee engagement with various business goals, but I could not find any that link it directly with customer experience. If you know of any such studies, please share them with me.

 

It’s important to point out that employee engagement, defined as “the emotional commitment one has to their organization and its goals”, is very different from employee satisfaction or experience. An employee can be very engaged even without being satisfied with her working conditions, and vice versa.  I would like to pose that in the long term an employee is not very likely to sustain his emotional engagement without the consistent commitment of the company to improve his experience working there.

 

Since both customer experience and customer engagement are very subjective perceptions any attempt to measure either one presents methodological challenges. Every one of such attempt usually attracts very vocal supporters and detractors. Based on conviction that human perceptions are best described by stories, we aggregated and mined the stories of McDonald’s restaurant employees shared by them  online (3,327) and the reviews of its customers (4,412). The Opinion Miner algorithms discovered patterns in these “stories” and measured frequency with which these patterns observed as well as a collective sentiment associated with each one. While such analysis can be much more detailed, for this article we decided to focus only on the most frequently observed patterns.

 

While McDonald’s employees, who shared their stories,  are quite satisfied with their benefits, learning experience and training, they don’t perceive their work environment positively. You can see the chart below. The size of the bars represent the intensity of a sentiment expressed.  MCD Emp chart   Even though the majority of employees who shared their story online are disheartened by their pay rate, this comes seventh in terms of its importance to them. The most important signal, from the perspective of this inquiry, is a negative sentiment toward customers that comes through the employees’ descriptions of their relationship with their company. It is hardly a surprise that customers reflect this attitude in their assessment of McDonald’s customer service (-4%) as it is seen on the chart below. MCD Cust chart

Despite relatively positive assessment of food, ambiance and cleanliness customers don’t think that McDonalds offers them a “good value”. The price matters less when you are served with disdain. Restaurants are not in a food business-they are in the hospitality business and unengaged employees do not seem to be very gracious hosts.

 

This is just one, randomly selected, example. However, the result suggests that companies serious about improvement of experience for their customers have to pay closer attention to measuring and monitoring the satisfaction of their employees.

 

The “Agile” Approach to Consumer Product Marketing

When process succedsThe term Agile is most familiar to people involved with software development, but the basic concepts can be applied to consumer products successfully as well. At least two of its core principals – use of iterations and collaborative involvement of product users (i.e. customers) – were effectively practiced years before the term was introduced and became commonly accepted.

Wide acceptance of Agile methodologies arguably resulted in dramatic increases in software project’s ROI caused by:

  • reduction in the number of abandoned projects
  • cost reduction for user training and documentation
  • increase in user adoption of the “final” product

In other words, the application of Agile methodologies reduces the uncertainties of delivering an expected outcome.

Development of software to simplify business user’s jobs, has at least one critical similarity to the development of many consumer products – customers cannot clearly articulate their requirements. Particularly, the latent ones. Of course there are tools to help you do this, Kano analysis, being one of the most popular. Unfortunately, not enough consumer product marketing professionals are known to use these tools. That manifests itself in a very high failure rate of bringing consumer products to market. The actual rates of consumer product failure are quoted anywhere from 30% to 80%. The numbers vary by industry and are controversial because they do not clearly articulate what “failure” means. I define a product “failure” when it did not deliver the originally forecasted revenue.

Accenture research estimates that the CE (consumer electronics) industry alone has spent $16.7 billion a year to “receive, assess, repair, re-box, restock and resell returned merchandise.” More than two thirds of these costs, or $11.2 billion, are characterized as No Trouble Found (NTF). In other words, the products did not meet the customer’s expectations. Personally, I find the term NTF very disturbing – $11 billion waste caused by poor market requirement definitions and misleading advertising, is indeed a big trouble. That number does not include the cost of the customers time wasted, hit to the brand reputation and environmental costs of transporting and stuffing landfills with failed products and packaging.

The cause of the CE product NTF fail is relatively easy to diagnose – too many products are conceived by engineers who value the “cool” factor the most, without any reference to actual customer needs. That approach worked well while the price and advertising were the most critical factors in customers  purchase decisions. The last few years have seen a dramatic increase in the importance of customer experience delivery as the most influential factor in selecting a product.  The revenue growth of the leaders (Apple and Samsung) are cooling down, while the rest of the CE companies are seeing a drop in revenue and profit contraction.

Meanwhile, there is some evidence that small “un-brand manufacturers” are doing well by practicing “Agile” – looking methods to capture market share from the established brands.

  1. They “collaborate” with the customers of their competitors by analyzing product reviews they published online. They learn what caused these products to fall short of their customers’ expectations and why they purchased these products on the first place;
  2. They design products based on the results of that “collaboration” and their interpretation of consumer needs.
  3. They manufacture small lots of products to test the accuracy of their interpretation, market reaction and analysis of the feedback before going to the next “iteration”;
  4. They form customers’ expectations by “communicating” the product properties with the language used by customers to describe their experience.

“Agile” product marketing is a better approach when scale of design and manufacturing does not work anymore. It is not “cool” that sells your products today, it’s the experience your company delivers to the people who buy them.

 

In Defense of Anecdotal Evidence

During the last two decades traditional retail business has experienced a disruption similar to an earthquake delivered by the proliferation of ecommerce. That earthquake caused tsunami-like floods of online customer reviews describing personal experiences with specific products. Those retailers, who embraced this wave of untamed customer feedback, surfed it to higher “visit to conversion rates”, growth and profitability.   The way I feel isToday millions of customers share their experiences online about a wide variety of products and services, both personal and business related. Based on multiple studies, the trust other consumers give to these reviews is increasing from year to year.   While the flood of experiential information provided by customers and its influence continues to grow, many marketing researchers still question its value to business. To be fair, there were some interesting studies conducted that found correlations between the quantitative aspect (star rating) of customer reviews and the restaurants’ revenue. However, qualitative research of the actual reviews is being sneered upon and labeled “anecdotal”.

“The expression anecdotal evidence refers to evidence from anecdotes. Because of the small sample, there is a larger chance that it may be unreliable due to cherry-picked or otherwise non-representative samples of typical cases. Anecdotal evidence is considered dubious support of a claim; it is accepted only in lieu of more solid evidence. This is true regardless of the veracity of individual claims.”  The underscore is mine.

Interestingly, the above quote comes from Wikipedia, that itself has been attacked by status quo defenders as “inaccurate”. Yet, this quote is the best definition I could find online, after checking more “official” sources like Oxford and Merriam-Webster.   Since Customer Experience is a perception, there is no more meaningful evidence to communicate it than an anecdote. Based on the definition, two primary reasons for not using it to form strategic decisions are the size and quality of the samples in terms of representation. When it comes to customer reviews, the available volume (sample size) often exceeds the size of samples collected by most quantitative marketing research projects. Mining of these anecdotes produces very meaningful insights with a real business return on investment that quantitative methods are not capable to discover. Such techniques allow:

  • discovery of patterns and trends within the multitude of “anecdotes”,
  • measurement of their relative importance to customers,
  • measurement of the sentiments associated with these patterns.

The cross-sectional representation of these findings may subsequently be validated via traditional quantitative methods.   The internet democratized many aspects in our lives and not everyone likes it. The selection of sampling strategies for research used to be the prerogative of professional researchers, who often act like high priests of the illusive cross-sectional representation probability standards. In reality, very few of them actually practice any probability sampling methods beyond relatively basic demographics. The proliferation of inexpensive online survey tools enable people, without special training, to conduct marketing research. Most marketing executives, the recipients of this research, have neither the background to venerate these methods nor have experienced a measurable advantage using them. On the other hand, customer reviews often can be subjected to sampling based on gender, geography, age, time published, etc. to improve probability of more full representation of the customer base.   Those who continue to belittle a value of untamed customer feedback to business will fall victim of their own elitism and become even less relevant than they are now. Change before you have to.

3 Steps for Improving the Value of Voice of Customers

Every company collects customer feedback in one form or another. It is the ability to HEAR what their customers SAY that separates successful companies from “also run”s. Below are 3 steps that can help your company to improve its hearing:

  1. VOC value 1Stop manipulating it

 

The availability of inexpensive survey tools, that allow you to produce and send your questions to thousands of email addresses, does not translate into valuable knowledge of how your customers experience doing business with your company. The type of questions you ask, inevitably influence the type of answers you receive. Implement ation of a shiny new “customer engagement” software, does not translate into meaningful insights for improving your products and services. People’s motivations for choosing to engage and conditions of their engagement, inevitably corrupt a value of their input.

“Just because something isn’t a lie does not mean that it isn’t deceptive.” Criss Jami

Just because you have no intent to manipulate Voice of Customer does not mean your efforts produce trustworthy results. Focus on listening to what customers have to say on their own accord and without any guidance.

“It’s not at all hard to understand a person; it’s only hard to listen without bias.” Criss Jami 

 

2.  Stop being an order taker

 

It became fashionable to quote Henry Ford and Steve Jobs in arguing that VoC is not a source of innovation. I am not sure there is an VOC valueargument to be made – if customers were able to produce Market Requirements Documents, who would need innovators? It only means that if you expect customer feedback to spell out MRD for you, perhaps innovation is not your calling. The VoC is one of the best sources for learning the problems customers trying to resolve by “hiring” products available to them. Understanding of their problems and empathy with their experience, inspire true innovators to “translate” customer feedback into breakthrough products and services.

“The aim of selling is to satisfy a customer need; the aim of marketing is to figure out his need.” P. Kotler

 

  1.  Stop using selective hearing

 

Just because you pretend that VoC is limited to the customers who answer your questions, Word of Mouth does not stop influencing the rise or fall of your product’s fortunes. You can hide your head in the sand, but that will likely accelerate the distraction of your brand reputation. According to Jeff Besos, who knows a thing or two about customer-centricity:

“If you make customers unhappy in the physical world, they might each tell six friends. If you make customers unhappy on the Internet, they can each tell 6,000.”

You are more likely to learn from Word of Mouth analysis what really is important to your customers and why they buy your product, than from their responses to your survey.

Message to CX profession – Transparency begets trust

I get requests to complete surveys quite often. They come from my bank, after in branch transactions, websites I visited, customer service of my credit cards and cable providers. caged bird tweetsThey all want to know how I would score whatever is important to them, and leave a little space for my comments. Some of these surveys are just 2 or 3 questions long, but others expect me to answer pages of seemingly repetitive and circular questions.

I have never seen a survey request that explains coherently why my opinion is so important to them. In other words, they never indicate what is going to happen after I have completed the survey, carefully answered all the questions, and provided very detailed comments. Presumably, if the tabulated scores are high enough, whoever created or sponsored these surveys, will high five each other and cash their bonuses. But what about my needs? Would my contribution help anybody to make a better selection? How would I know if my responses contributed to a better product or service? Sometimes a company proudly advertises their customer satisfaction success, but I wonder if  their claims can be taken seriously because there is no way for a consumer to validate them. For these reasons I stopped answering survey requests a long time ago.

Amazon is considered by many, the poster child of customer centricity. I have done business with Amazon for over 10 years and made hundreds of various purchases over that time. I cannot recall a single survey request from them, ever. Could it be, customer-centric Amazon does not care about the customer experience they provide? I think they don’t survey their customers because they understand the power of authenticity that is growing fast with the advance of social consumer. Amazon understood that consumers will never trust a brand more then they trust each other. A long time ago, instead of collecting self-serving survey ratings, they decided to enable their customers to share their experiences with each other in an open forum. Yes, over the years there were incidents of manipulation attempts. Yes, the Liekert stars are not particularly informative. However, overall the customer reviews are extremely valuable to consumers who learned how use the reviews to reduce the uncertainty of their purchasing decisions.

“Amazon does not make money selling goods. Amazon makes money helping customers make good purchasing decisions.”

According to Keller Fay Group research, two primary reasons customers write reviews and publish them online are:

  1. (90%) Help other consumers to make the right choice for them – kind of: “pay it forward”
  2. (70%) Help brands to improve their performance. Consumers rely on the transparency of their input to motivate brands to act

I can only guess that since Amazon does not survey their customers, they probably use the content of reviews, posted on their properties, to measure the level of customer satisfaction of doing business with them. There are plenty of very informative references in many product reviews that indicate how customers regard their experience with Amazon. Explosive and continuous growth of this company is also a pretty good indicator of the consumers’ affinity.

So why do so many companies still shy away from exploring the content, provided by their customers without solicitation? The answers I’ve been given by Voice of Customer practitioners over the years have a common thread:

  • Lack of control over the process
  • Doubts in authenticity of reviews
  • Fear of negative sentiments

In other words, it seems these companies do not trust consumers, who provide their feedback transparently. Yet, these very companies expect consumers to trust them with their feedback without any transparency at all. How reasonable is such expectation?

Can’t Buy Me Love or Superior Customer Experience

Oneness of CXSuperior Customer Experience cannot be delivered without the well orchestrated cooperation of all departments of a company. Yet, this cooperation is very difficult to achieve. The primary reason for the existence of organizational silos is operational efficiency that allows companies to scale their growth. The opposite side of the coin is a lack of unified vision and, as a consequence, the inability to work toward a common goal. This problem has caused many calls for “breaking down the silos“, but I would like to discuss a more constructive approach. Revolutions rarely produce positive ROI for anybody, but their instigators.

There are two approaches commonly discussed to a solution of this problem – heroic leadership act of salvation or/and buying more technology. Neither approach is likely to yield a significant change, in my opinion.

Buying an exercise machine does not improve your health – change of your lifestyle will. Buying marketing automation or big data technology does not improve your company’s prospects for long term profitability growth – delivery of superior customer experience will. Change, before you have to.

Modern organizations are managed by metrics and the dreaded silos are so efficient because they are focused on measurement of isolated sets of results. To continue with the health analogy – measuring blood pressure will not prevent a heart attack unless, the patient is prepared to balance his diet and physical exercise. Similarly, measuring customer satisfaction will not prevent erosion of the company market share, unless the company is prepared to balance it’s operational KPIs and holistic customer experience metric.

The impact of each department within an enterprise on overall customer experience is often neglected and poorly understood. While each one has established metrics to measure its performance, only Customer Service/Support departments are obsessed with measuring customer satisfaction. However, even Customer Service rarely gets it right:

  1. Their obsession is not about holistic customer experience, but about customer satisfaction with customer service.
  2. Their operational KPIs are often cost efficiency focused, and in direct conflict with customer experience goals.

That makes Customer Support department metrics largely irrelevant to the other departments of the company.

A Customer Experience metric is a single measure of how customers perceived their overall experience with the company. However, there are multiple reasons why that perception has formed in their minds. Discovery and measurement of these underlying attributes of the customer experience offers an opportunity to link these attributes to those departments which impact the attribute scores. Below is a crude illustration of the concept.

Link CX with departments

Samples of verbatim used by the customers should be examined to make the linkage more relevant and accurate. Additional sources of internal relevant information such as product returns and customer support ticket volume/complexity would be critical for triangulation on the actual impact of the attribute on the overall customer experience.

This approach is not limited to B2C companies. Just ask your business clients to describe their experience doing business with your company. Let them do it in their own words and resist the temptation of introducing surveys or other company bias inducing formats. The analysis of their unstructured feedback could produce similar charts. The key is to record multiple experiences of your customer’s employees from different departments. Their experiences could be quite different about different attributes of your relationship.

Breaking the silos is an undesirable and unattainable goal. Alternatively, re-examination of operational KPIs of every department for their impact on delivery of superior customer experience will bring the change we seek.

Customer Experience and Balance of Power

Social Media protestDuring the last few years we witnessed tremendous political impact of social media on politics, both in  government and corporate realms. The examples abound from the social media fuelled Arab Spring demonstrations and political campaign funds collections, to the well publicized resignations of corporate leaders.

The role of social media protests focused on removal of specific individuals from their positions is somewhat troubling. It brings distant and horrifying memories of lynch mob parties and witch hunts. The fact that today’s victims are not physically harmed and cannot see the faces of their tormentors, does not make this practice fair or progressive. However, these protests were very effective in achieving their goals so far.

I wonder if this approach would also be as effective in compelling businesses to treat their customers better. Organizations and agencies that are charged to protect consumer interests are not doing a very good job for variety of reasons. Imagine Comcast customers start to protest the proposed acquisition of Time Warner Cable via a heated social media campaign. There are two reasons why the customers, and consumers at large, would consider to join such protest:

  1. If this proposal is accepted by the government agencies considering it, Comcast will be allowed to control both what content their customers consume AND how they get to consume it.
  2. Some consider Comcast to be the worst company in America.

I am not sure how this title was “awarded” to Comcast and don’t vouch for accuracy of the process that reported this distinction, but according to 2013 Temkin Experience Ratings, the TV Service Providers are firmly on the bottom of the poll as a group. Our own measurements produced Comcast social NPS® ratings below the Time Warner’s that are not particularly high either. However, this article is not about Comcast – it is about effectiveness of a social media protest and its potential application to consumer rights. If you are a lucky person who did not have a personal customer experience with the US cable companies you may want to see this video

 

 

Customers have been flooding social media sites with their complains about Comcast for years. Yet, the government has consistently allowed  them to acquire competitors that may have provided comparatively better experiences to their customers.

It appears that protests against faceless corporations do not produce the desired effect – provide better customer experience or let others do it. What will happen when consumer rights’ activists learn to become more effective by targeting specific politicians of the Senate Judiciary Committee, or other such agencies, who vote to allow a specific corporate merger that is detrimental to customer experience?

When and if this happens, the first political demotion or resignation will signal to businesses that their customers are not their assets, to be acquired or sold, they are the stakeholders and should be treated as such.

Social NPS® is an algorithmic estimate of customers response to the question – “On the scale of 0-10, how likely would you recommend this product to a friend or a colleague?”. It is produced by applying Opinion Mining technology to online CGC (customer generated content).

NPS, Net Promoter, and Net Promoter Score are registered trademarks of Satmetrix Systems, Inc., Bain & Company and Fred Reichheld.

Experience of Customers Helps to Forge Shoppers’ Expectations

I thought you would be tallerIf you believe, like I do, that happiness is about expectations management, customer reviews are your best bet for selecting your next car, smartphone or restaurant because they will likely deliver an experience you expect.

“The big advantage of a major brand over a small competitor is a residual expectation in a consumer mind of reduced probability to be disappointed. When quality is hard to predict a brand serves as a proxy to likelihood of good experience. The detailed and product specific experiences, shared by actual customers, help to decide if this product is for you. Surely, this information is not perfect, but if it is in statistically representative volume, it the best way to shrink the gap between your expectations and your experience.”

Skeptics often cite that reviews from customers, who may not be like you, make the usefulness of these reviews highly questionable because people have very different attitudes and product adoption skills. While this is undisputable, the large number of reviews and filtering options available allow for a reasonably easy match between a shopper and the customer profiles. The personality and attitudes of a customer shine through the language of the reviews and help a shopper to “try on” an experience of people like her. The absence of a “story” is one of the key reasons why ecommerce sites that substitute actual reviews with score cards experience lower traffic and visit-to-purchase conversion rates than their competitors who publish complete reviews.

Most of content generated by customers is fact based. There is no sugar coating or attempts to manipulate your emotions. The language of reviews tend to be more specific, more matter-of-fact and focused on the personal experience the writer had with a product in question. Warm and fuzzy is much less effective when it faces meaningful competition from more “rational” sources.

The language also betrays fakers and dumb marketers who sometimes try to manipulate the market. Faking reviews effectively is not as easy as people may think. The language used, vague description of details and lack of personal experience knowledge are easily noticed not only by an attentive reader, but even by algorithmic filters that consistently give them low confidence score. In addition, it is impossible to tip the scale with an occasional fake review, and a sufficient volume of them can be easily spotted and tracked to the source. The financial penalties imposed by FTC for publishing fake reviews have run into hundreds of thousands of dollars, but that fades compared with damage to the reputation of the company that commission such activities.

It is surprising how few marketers consider customer reviews to be a valuable source for marketing intelligence because they cannot control and/or manipulate it. Instead they prefer to rely on “big data” acquired without customers’ consent and often against their wishes. Those marketers who do hear what real customers want to tell them quickly discover what specifically make one product more valuable than the alternatives to their best customers and prospects. Actual use of this intelligence to support their product marketing processes helps them consistently outsell their competitors by a wide margin without price discounting.

You cannot eliminate an uncertainty, but experiential information provided by customers helps to resolve it much faster and much more specifically than any brand advertising or company centered survey.

 

 

 

 

 

 

Lies and big data

Big data and lies it tells usThe other week someone brought to my attention an article with a title “Lies Data Tell Us” by Steven J. Thompson, CEO at Johns Hopkins Medicine International. The title took me aback, but as I read it I realized the article was really about better practices required for data to be more useful. Use of the provocative and somewhat misleading title resulted in nearly 12K views, dozens of comments and hundreds of shares in social media. When I started looking for this article again, the search brought a number of links that associate data, big data, etc. with “lies”. Most of the authors blame data or unscrupulous mining and analysis technology vendors for all sort of business problems resulted from “data lies”.  It seems some of these authors use the following definition:

 Data Scientist (n): A machine for turning data you don’t have into infographics you don’t care about.

I would like to examine a process people often follow when they deal with data.

Since the term “big data” is thrown around a lot, I would like to define it in the context of this article. Mere volume and velocity of data does not constitute “big data”, but multiplicity of data sources and data formats does. From that perspective the term “big data” describes an enterprise data aggregated from multiple departments and multiple data bases (i.e. data warehouse model), linked with data from sources external to a company, in a structured and/or unstructured format. Mining such set of “right data” may produce very valuable intelligence. However, all can also result in waste of money, efforts and opportunities if

  • The mining process does not produce relevant new intelligence, or
  • The intelligence is not used for action.

We act when we believe the action will result in a desirable outcome. We never know for sure, but we estimate probability based on our experiences in similar circumstances. These dynamics influence how we select, search and interpret the data into intelligence, or lack of thereof. Subconsciously we select data that See no evidencewould likely provide confirmation of our existing beliefs. This usually means that we heavily rely on internally generated (controlled) data  and heavily discount externally generated data. 

We like to use such terms as unbiased and objective, but the very process of selecting a data set introduces bias and subjectivity. It is unavoidable. It is a much better practice to embrace and understand a bias that is pragmatic, and define a purpose of an inquiry. You don’t see people mining a mountain to find “whatever” is there. They carefully select and test an area for an indication of high concentration of desired mineral before the exploration and mining start.

If the purpose of your inquiry is improvement of customer experience, assemble a data set from the most relevant internal and external data sources available. If you limit your data set to a company controlled data, you introduce a company bias.  In such a case the likelihood of discovering any new intelligence for improving your customers experience is quite low. Forget about data mining and just continue your archaic surveying exercises of “guess and validate”. If you include data generated by customers without solicitation and control, you will introduce customer bias. Introduction of channel generated return data and customer service data will allow for balancing of the biases. Correlation of trends in controlled and external data sources will help to discover potential gaps between your beliefs and emerging evidence. However, even the best evidence cannot automatically make people abandon their beliefs and start acting differently, but that is a subject of another article.

The point is – data cannot lie to us; we have to do it ourselves by not mining it honestly and competently.

B2B Customer Experience Management – a story from the trenches (Part 2)

In the last week post I wrote about the reasons the examples of B2B Customer Experience Management successes and failures are not as widely available as B2C ones. I also started describing a specific example of pitfalls on a journey of CX discovery. This post is about negotiating these pitfalls and translating findings into actions. 

Data-Insight-ActionThe suggestion was made to take another stab at the problem, but from a different perspective. Until now all inquires were focused on the product. Perhaps focusing on why the visitors downloaded the free version, or even why they came to the website on the first place, would provide insights that would help to increase the conversion rate.  It was clear that the free version was not sufficiently meeting customer expectations as only 18% were still using it for “minor” projects after 6 months from a download. What was not clear is what kind of projects did they hope to tackle with the product. This is not an easy question for tabulating answers. However, a clear and statistically representative answer would help us understand if our website attracts “wrong” customers, i.e. there is a mismatch between problems they have and solutions we offer.

Interestingly enough, the “survey” (with open ended, free format, questions that focused on customer’s experience, instead of company’s problems) generated over 13% response rate. The automated analysis of this feedback exonerated the digital marketing team – they have been attracting “right” customers—but the customers’ actual experience with the product did not live up to expectation created by the marcom. The detailed analysis of collected customer feedback produced  a list of CX attributes in order of their importance to the customers, as well as a measurement of delta between their expectations and experience (example). Two issues stood out, as they caused customer disappointment by 25% and 38% respectively – customer support and usability. The first finding incensed the customer support team, who stormed in armed with NPS=87. The customer support team was serving only paying customers, while the fremium ones were supported by other customers (community) and an automated knowledge system. That caused us to separate the customer feedback data by paying and fremium customers contribution. Indeed, paying customers did not experience any disappointment with customer service. Usability was a problem for them as well, although with much lower impact.

A deeper dive into their comments produced the following insight: the product has sufficient functionality to meet target customer expectations, but only the savviest and/or most technical users are capable of figuring out how to draw on this functionality to achieve the goals they expected the product to deliver.

Plan of action:

  1. Extend full customer support (2nd tier/priority) to fremium customers and offer 1st tier as a paid option without conversion to a paid license.
  2. Launch-process-driven. i.e. customer-centered, UX study to learn how to simplify use of the product
  3. Re-design the product front end based on the UX study findings.

Afterword

Implementation of the first step of the plan resulted in 4% of additional revenue from increased conversion ratio after the very first quarter. Learning from Zappo’s experience, the management shifted 20% of the marketing budget to customer support, which is now considered a revenue generating department. The subsequent steps, when gradually implemented into production, reduced customer support load to below original cost per customer.

Most of us are very focused on what we think we do – product people are product-centric, customer service people are support-centric, etc. – but we all are in business of delivering the best customer experience, and we should excel in our part of it without losing a focus on the big picture.