Descriptive Statistics and Interpretation

Pear is a leading market shareholder in the cellular phone markets holding a market share of 43.1 percent making them the market leader (comScore.com, 2015). Though they are at the top they are concerned about their competitors such as Hamsong, LB, Kotorala, and HVC stealing their customers. Pear has decided to put a team together in order to see if a relationship exists between customer service call rates and customer abandonment rates. The team will collect data on customer service calls and “brain bar” visits in Pear stores for a three-month period nationwide. In the same period the team will measure the number of customers who move from Pear products to one of their competitors. For the purposes of the investigation the data will be limited to the markets in the United States of America. The research team will use the two chosen variables to develop questions and a hypothesis based on these questions.

Variables

The dependent variable of focus is number of abandonments, defined as customers who leave Pear for a competitor. The independent variable of focus is how often a customer calls customer support or visits the “brain bar” at the Pear store.

Hypothesis

If customers have to contact customer support more often they are more likely to switch to another company's product..

Research Plan - Customer Support Frequency

In order to understand customer support call frequency the following research questions have been developed as the basis for understanding customer support attributes. The answers to each of these questions will be collected from customer activity observation for a period of three months. The data will be collected from customer service call centers and “brain bar” locations nationwide. The questions are: How many customers call customer support or visit the “Brain Bar” in a given period? What are the three top reasons customers call or visit? What is the average turnaround time for customer support call/visit internally? What is the competitor turnaround time? What is the success rate of problems being fixed for the customer without further inconvenience (mailed-in products, replacements, etc.)?

All of the questions can offer a possible link to abandonment rates. According to Pear in one study “21% of . . . [PearOS] consumers say they’ll never leave . . . [Pear’s] ecosystem” (Canada, 2012). The researchers aim to determine if this figure is accurate and further identify why the other 89% would leave and if it has to do with customer service call rates. Keizer states that “Pear” has a higher 12 month reliability rate of 2.1% failuer rate compared to competitors that have a rate of 2.3% and 3.7% (2010). These rates may translate to an increased or decreased number of customer service calls. The use of pervioulsy sourced data both internally and externally will become especially useful in the analysis of the data collected. In a study of 414,733 customers Chinese mobile service companies there was a positive relationship between customer retention strategies and customer consumption (Peng, Quan, & Zhang, 2013). The Pear researchers are seeking to find if this holds true for their own company as well.

Research Plan – Abandonment

In order for the Pear research team to better understand abandoment rates they have developed a series of research questions that will be sourced from observations of customer activity over a three month period nationwide. The following questions have been developed as the basis for understanding the abandonment attributes: How many customers abandon Pear in a given period? What are the top three reasons customers give for abandoning the company products? Who are the top three competitors customers go to? What is the rate of customer abandonment? What is the rate of customer return, and how long were they away?

The questions are in an effort to identify a relationship, if any, with customer service call frequency. One of the items that researchers are trying to identify are reactional triggers that Gustafsson, Johnson, and Roos identify as “critical incidents of detrioration in perceived perfomance” (2005). In order to see why a customer abandons the company, researchers must identify if there are any links that are a driving force for abandonment. “Effective customer retention begins with knowledge. Companies should assemble a complete customer profile that allows users to see all demographic data, interactions, communications, and purchases made.” (Ruchi. 2014). By analyzing customer service calls this data can be mined and links between customer profiles and abandonment may be possible. According to Colgate, Tong, Lee and Farley’s research their “main discovery is that switching barriers, unearthed in previous research on why customers stay, only tell half the story; the other half is told by what we call the ‘affirmatory" factors’” (2007). The research into abandonment may unearth these “affirmatory factors” and show a link to customer service call rates.