The Pitfalls of Using Predictive Models

Football

I joined my friend's fantasy football league this past season. I was skeptical to join at first. My friend's league had been together for 7 years, each participant with deep knowledge about nearly all the NFL players and the game. I, on the other hand, have not followed NFL football for nearly 20 years and had only a superficial knowledge of only the popular NFL players. Given my lack of knowledge, I thought that I could use predictive modeling to help me pick my fantasy team during the … [Read more...]

Clarifying Employee Engagement: A Review of Four Employee Engagement Measures

employee_engagement_review

The concept of employee engagement is a popular one. Companies with higher employee engagement have better outcomes (e.g., higher customer loyalty, increased employee performance, business growth) than companies who do not. Consultants tout their own measure of employee engagement and present research to show its effectiveness. From the stuff I read about the benefits of employee engagement, I figured I should learn more about this area. I recently stumbled upon an excellent article by Bill … [Read more...]

Visualizing the Three Components of Customer Loyalty

Figure 1. Plot of factor loadings for 7 customer loyalty questions reveals two general types of customer loyalty

I use factor analysis (more on that below) often in my customer experience management research. Specifically, I use it to help understand how to best measure customer loyalty. The value of factor analysis, however, is sometimes lost in the details. In this post, I adopt a visual approach in presenting factor-analytic results of some prior research to help show that customer loyalty is really best conceptualized as a multi-dimensional construct, not easily captured using single-item … [Read more...]

Analyzing Big Data: A Customer-Centric Approach

Big Data

The latest buzz word in business is Big Data. According to Pat Gelsinger, President and COO of EMC, in an article by the The Wall Street Journal, Big Data refers to the idea that companies can extract value from collecting, processing and analyzing vast quantities of data. Businesses who can get a better handle on these data will be more likely to outperform their competitors who do not. When people talk about Big Data, they are typically referring to three characteristics of the … [Read more...]

Ten Guidelines for Clean Customer Feedback Data

Detection of Data Errors

Customer experience management (CEM) programs involve the collection, analysis and dissemination of customer feedback. These customer feedback data are extremely valuable to businesses. Customer feedback data are used to help senior executives identify and improve key drivers of customer loyalty. They help call center staff immediately address specific customer issues.  They help managers understand how their business unit compares with other business units. Finally, customer feedback data can … [Read more...]

The Practice of Customer Experience Management: An Overview

Customer Experience Management (CEM) is the process of understanding and managing your customers’ interactions with and perceptions of your company or brand. The ultimate goal of CEM is to build valuable relationship with customers so they stay with you longer, advocate on your behalf and expand their relationship with you over time. A CEM program consists of a set of organized actions that support the goal of CEM. While a CEM program has many moving parts, an easy way to organize those … [Read more...]

The Practice of Customer Experience Management: Paper for a Tweet

To get paper: 1) click image, 2) Tweet about it, 3) download paper

I have been writing (books, articles, blog) on the topic of customer feedback and related fields (CRM, CEM, VOC)  for many years and am accumulating a lot of content. In the process of organizing this content, I wrote a short paper about the practice of customer experience management (CEM) that provides a solid foundation for a larger book on the topic. The Practice of Customer Experience Management: The Paper This 5-page overview explains the practice of CEM using a 6-component model and … [Read more...]

Four Things You Need to Know about Your Customer Metrics

Measurement criteria for customer metrics: Reliability is about precision/consistency of measurement; Validity is about meaning of measurement

A successful customer experience management (CEM) program requires the collection, synthesis, analysis and dissemination of different types of business metrics, including operational, financial, constituency and customer metrics (see Figure 1).  The quality of customer metrics necessarily impacts your understanding of how to best manage customer relationships to improve the customer experience, increase customer loyalty and grow your business. Using the wrong customer metrics could lead to … [Read more...]

Assessing the Validity of your Customer Experience Management Program

reliability-validity-quadrant

Companies with customer experience management (CEM) programs rely heavily on customer feedback in making business decisions, including, setting strategy, compensating employees, allocating company resources, changing business processes, benchmarking best practices and developing employee training programs just to name a few. The quality of the customer feedback directly impacts the quality of these business decisions. Poor quality feedback will necessarily lead to sub-optimal business decisions. … [Read more...]

The Net Promoter Score: Let Us Not Forget The Past

Beyond the Ultimate Question

Those who cannot remember the past are condemned to repeat it. Those words are as true today as they were in 1905 when George Santayana coined that phrase. In 2003, the Net Promoter Score (NPS) was formally introduced by Fred Reichheld.  His and his co-developer's overstated claim that the NPS was the best predictor of business growth (e.g., better than overall satisfaction) was never replicated.  Here is a classic blog post from 2007 to help remind you of the NPS past. I am guessing the … [Read more...]