Customer Experience Big Data Dysfunction book and Self-Assessment

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Self-Assessment Questions

Customer Experience

@CRMetrics

25

BIG DATADysfunction

10



Customer Experience

25

BIG DATADysfunction

Instructions: Keep track of your “Yes” responses

10

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About Customer Relationship MetricsWe make corporate missions and customer passions happen.

20 years ago at The Purdue University Center for Customer-driven Quality, Dr. Jodie Monger (President and CEO) began working with contact centers to uncover and leverage customer experience insights to improve customer relationships.

Most often, contact centers contain the most abundant and richest source of customer experience business intelligence. Our primary mission is to collect, evaluate, and disseminate customer intelligence to assist the senior leaders in making decisions relating to the customer experience using leading technology with no or little IT requirements.

We are an independent source of customer intelligence information for those needing to affect change.

We engage in activities that support research law.


INTRODUCTION

Customer Experience Data problems have always existed.

In fact, it’s not an issue whether or not you have a customer experience data problem, the issue is ‘HOW BIG IS IT’?

Everybody has customer experience data problems. On a personal level, it may be the time you must invest to deal with your bank about an account error or it may be the effort to return an item from a retailer. Throw kids into the mix and your data problem gets bigger.

As an organization, improving the customer experience will increase sales, improve service, and lower costs which result in greater profitability.

This self-assessment focuses on customer experience data and an organization’s probability of success in developing real customer-centricity.

Customer Experience Big Data Dysfunction Diagnostic


INTRODUCTION

The questions in the self-assessment are designed to be a guide to identify the symptoms associated with Customer Experience DATA DYSFUNCTION in your organization.

Identifying symptoms is not providing a solution to your dysfunction, nor can these questions be used as a tactical plan to overcome this terrible illness.

But, we have found that answering “YES” to these questions (answering “YES” IS A BAD THING) has often provided an effective a tool for diagnosis, as have lengthy explanations of the characteristics of customer experience big data dysfunction.

We appreciate that the diagnosis of customer experience data dysfunction is a matter that must be very serious and very strategic.

Our hope is that the awareness generated from this assessment will help your organization develop the actions for change.



It’s the biggest customer challenge facing businesses today

The biggest challenge faced by consumer businesses today, as it relates to the customer experience, is data conversion disorder.In psychology, conversion disorder is a somatoform disorder characterized by medically unknown and often disabling neurological symptoms. Individuals diagnosed with conversion disorder present with at least one unfeigned and unintentional symptom which affects voluntary motor or sensory function, resembles a neurological or medical disease, and involves psychological elements. Symptoms may include impaired coordination, paralysis, weakness, difficulty swallowing, double vision, blindness, deafness, seizures, amnesia and loss of consciousness.

Many consumer businesses are experiencing similar symptoms of data conversion disorder. This disorder is increasing in magnitude because the elements that cause the disorder are growing. Consumer businesses that are heavily concerned about sales, retention, competition, and brand are more at risk for stronger forms of the disorder.

Consumer businesses with data conversion disorder typically present with several symptoms including low cross-functional collaboration, incorrect/slow/no action, long decision-making processes, re-work, corporate arrogance, complicated and complex processes, failed product launches, disconnected strategic plans and tactical metrics, high suspicion, and low trust, to name but a few.



At Customer Relationship Metrics we have identified several root causes for this disorder that go beyond the typical human control issues of politics and bureaucracy. The first is a group we refer to as the three V’s of Customer Experience Big Data:

• Volume: Data about the customer experience is growing by terabits per second for many organizations. Surveys are not (and should not) be the only way to capture the customer experience. In this context, the amounts of both structured and unstructured data that are being collected is literally crushing many organizations.

• Variety: One thing that is making customer experience data so big is a greater variety of sources than ever before.

• Velocity: As organizations relentlessly press towards real time, data volumes get big in a hurry. This can also add to the frustration as practically no organization can take action in real time.

If you combine these three V’s with the other root causes, you begin to see the business case for Customer Relationship Metrics and how we address it with our services.

http://metrics.net/blog/2012/07/bi-insights-drive-tangible-innovative-partnership/

http://metrics.net/blog/2012/02/holistic-medicine-call-center-customer-experience/



The second set of root causes encompasses the people resources. We call these the three C’s of Customer Experience Big Data:

• Count: Many companies are running very thin on people and are handcuffed because they are unable to add work to an already overburdened workforce. Most organizations just do not have the time or resources to uncover insights and to act because they are too overwhelmed with day-to-day demands.

• Complexity: As mentioned in the three V’s, this customer experience big data problem is complex and getting more complex with every passing day. Addressing this issue requires special skill sets that most find to not be internally available. Customer experience data scientists are needed with skill sets that extend well beyond those of data analysts or statisticians.

• Culture: What we refer to here is not company culture but rather cultural bias. In order for a customer experience data scientist to analyze and interpret the customer experience accurately, they must know the culture of the people from where the data are collected. A customer experience data scientist that lives in the US could not correctly interpret customer experience data from India no more than a customer experience scientist in India could interpret the customer experience data from the US. Conducting statistical tests and interpreting results are different. The cultural bias in each would result in inaccurate interpretations that actually add to the data conversion disorder.



The second set of root causes contains people resources. We call these the three C’s of Customer Experience Big Data:

• Count: Many companies are running very thin on people. Many companies are handcuffed because they are unable to add work to an already overburdened workforce. Most organizations just do not have the time or resources to uncover insights and to act on them because they are too overwhelmed with their day-to-day demands.

• Complexity: As mentioned in the three V’s, this customer experience big data problem is complex and getting more complex with every passing day. Addressing this issue requires special skill sets that most all find to not be internally available. Customer experience data scientists are needed with skill sets that extend well beyond those of data analysts or statisticians.

• Culture: What we refer to here is not company culture but cultural bias. In order for a customer experience data scientist to analyze and interpret the customer experience accurately, they must know the culture of the people from where the data are collected. A customer experience data scientist that lives in the US could not correctly interpret customer experience data from India no more than a customer experience scientist in India could interpret the customer experience data from the US. The cultural bias for each would result in inaccurate interpretations that add to the data conversion disorder.

Very few organizations are immune to data conversion disorder. The best you can do is to know that it does exist and that chasing symptoms will not impact the root causes. This assessment has been designed to help you to better identify symptoms so you can plan a root cause attack to keep the disorder from being a debilitating disease.


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Understanding the behaviors of customers and employees, their impact to business results and the business potential, is exploding in need.

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• A growing number of key decision-makers need / want analytical capability • High-risk with relying too much on “gut feel” • Time window for decision making and agility is shorter • Dispersion and decentralization of our workforce • “Most vital” business information not rapidly identified • Insufficient visibility into operational activity • Inability to identify and act upon business opportunities (revenue growth, cost reduction,

customer acquisition, etc.) • Poor understanding of competitive threats • Increased dependence on the performance of external stakeholders • Cyclical nature of our business (feast or famine)

Source: Aberdeen Group



Customer Experience

25

BIG DATADysfunction


10



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(1.) Are you spending a lot of effort trying to get two more calls monitored to meet a quota for each contact center agent?


(2.) Are you ever upset that marketing slammed you with another surprise that blows up in your contact center?

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(3.) Do month-end reports take two or more days to compile?

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(4.) Is the actual value of a customer an UNKNOWN?


Companies with high levels of employee engagement improved operating income by 19.2% while companies with low levels of employee engagement declined 32.7%. --Towers Watson

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(5.) Are the costs to support the different customer interaction methods an UNKNOWN cost?

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(6.) Is your IVR drop rate greater than 4%?Note: If you don’t know, answer YES.


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(7.) Are Marketing and Corporate Communications handling your social media customer service?



Analytics Dilemma

Source: ASTD-Feb 2010

McKinsey Global Institute projects that by 2018 – in only 5 years - “… demand for analytical positions could exceed the supply being produced on current trends by 140,000 to 190,000 positions”. Furthermore, they project “a need for 1.5 million additional managers and analysts in the US who can ask the right questions and consume the results of the analysis effectively.”

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(8.) Do you feel like the “red-headedstepchild”?



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(9.) Are you concerned that your 250 canned reports deliver little-to-no actionable insight?


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(10.) Do you find yourself and others saying, “We’ve always done it this way.”?



22. D

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Our Risk-free 2-10 GuaranteeOur work is guaranteed to deliver results.

We can guarantee value that software can not and WILL NOT.

Within six months of working with us, we guarantee you will experience a minimum 2% decrease in costs or an improvement in sales and a 10% improvement in customer experience scores or we will, at your option, accept the portion of those fees that reflects your level of satisfaction. Guarantees are based on project scale and scope and will be outlined prior to the start of your project.

Big Data Dysfunction Diagnostic

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Customer Experience

25

BIG DATADysfunction


10



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Number of “Yes” Responses:

0-2: EXTRAORDINARY and rare 3-6: BEST of the best, a role-model7-11: ABOVE average, keep striving12-16: AVERAGE, yet high competitive

risk17-20: RISK of business failure21-26: GET OUT of there

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Customer Experience

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BIG DATADysfunction


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Customer Experience Big Data Dysfunction book and Self-Assessment