Customer's Insight

CONTEXT

The aim of this research is to conduct a study on the customers of Emma &Arnold Reliable Logistics (E&A) to understand their key characteristics in terms of psychographics, demographics, motivations, and media usage. From this report, user personas and customer journeys will be generated using the customer data from the study which will be used as the foundation for the development of the content and media strategy for E&A.

E&A is currently located in Poland with a branch office in Oentsjerk, the Netherlands, and is active in the road freight transport sector  (Ozoo, n.d). It ships both consumer and non-consumer goods across Europe.  They consider as their core to ensure that the goods of their customers are handled with care and that they are delivered to their destination safely and on time. Reliability and consistency are key to them, and their main routes includes Germany, Netherlands, France, Belgium, Poland, Italy, and Czech Republic (Apollo, n.d).

According to Arnold, the director of E&A, their target audience includes small to medium companies engaged in the sale of consumer and non-consumer goods that require shipment to their final destinations. They intend to increase brand awareness and generate leads that can be converted into buyers of their services who can become loyal customers (Arnold, personal conversation, 10 November 2022).

Given the above background information, the study will focus on customers which are in the logistics business in Europe, in order to develop a business to business (B2B) content and media strategy.

Deliverable

Our ideal buyer is Joseph, a sociable logistics expert with a Bachelor's degree and a passion for researching online. He's an innovative thinker who's always open to new ideas to improve his logistics solutions.

METHODOLOGY

In this chapter the selected research methods are explained as well as the data gathering and analysis procedures. Quantitative and qualitative data collection methods were used, which are described in the next subsection.

As indicated by Revella (2015) a quantitative instrument such as a survey can be valuable to establish a buyer persona provided that it is correctly used to combine data established in qualitative instruments like in-depth interview (Revella, 2015). To adequately understand the target audience, the quantitative data was confirmed by qualitative data through the triangulation method. This will help to go deeper and to increase the breadth, complexity, and richness of our research (Saunders & Lewis, 2012).

2.1 Method & Procedure

The research method and procedures used in this study were selected to align with the research objectives. The aim was to gather both qualitative and quantitative data to create user personas. The focus was on understanding the content needs of the target group. Triangulation techniques were used to ensure data validity, credibility, and authenticity (Saunders, 2016).

The research method employed in this study combines survey questionnaires and interviews to gather data from multiple sources. The survey questionnaires were used to create user personas based on the responses collected. Also, interviews were conducted to supplement and validate the findings from the survey.

The survey questionnaire was distributed online through Google Forms and consisted of five sections with questions developed using nominal and 5-point Likert scale formats. Interviews were purposefully conducted with participants from the logistics industry to gather qualitative data. Nonprobability convenience sampling was used to derive a sample from the population of E&A customers.

To extract meaningful insights and patterns, the collected data were analyzed using statistical techniques and thematic analysis. The data obtained through the survey questionnaires and interviews were combined to create user personas representing distinct clusters within the target group. This will enable the development of targeted and meaningful content strategies.

By following this method and procedure, the study aimed to gather comprehensive and reliable data, ensuring the creation of user personas that accurately represent the content needs and preferences of E&A customers.

2.2 Questionnaire Design

The questionnaire was designed in five sections using Google Forms (see table 1 below). It consisted of five sections. The questions were carefully crafted, utilizing both nominal and 5-point Likert scale formats to ensure clarity for the respondents (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree) (Lietz, 2010). Scales with a large number of questions often confuse respondents because the wording differences between the scale points become trivial (Mooi & Sarstedt, 2011).

The use of the nominal and Likert scales allows for a structured and standardized approach to gather data. Additionally, a dichotomous question was included in the questionnaire to filter out respondents who lacked experience with E&A’s services, thus streamlining the process and ensuring that the data collected is relevant and applicable to the research objectives.

The Big Five model was employed to measure personality traits, whilst media usage and motivations were analyzed to explore customer behavior. Demographic questions were also included, covering gender, job title, and location of the company.

Table 1 gives a graphic representation of the questionnaire. In the first column, the different stages of the questionnaire design are listed. The second column highlights the theories applied in each stage, such as the Big Five model, Uses and Gratification Theory, and Maslow's hierarchy of needs. The third column specifies the scale used for measurement in each stage, such as the 5-point Likert scale or single select options.

By incorporating the mentioned theoretical foundations and measurement approaches, the questionnaire aimed to gather insights into customers' psychographics, media use, motivations, and demographic characteristics.

 

 

 

 

Items

 

Theory

 

Measurement

Filter question

The questions were meant to determine whether the respondents used E&A services.

 

Dichotomous question (Saunders & Lewis, 2012).

“Yes and No”

Psychographics

Questions about the customers’ psychographics was tested using the Big five model by D.W Fiske 1949 of the personality traits (Openness, Conscientiousness, Extroversion, Agreeableness, and Emotional stability) (Thomas, 2021).

Tested on 5 level questions on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree).

Platforms, Content types and media types

Media usages were according to (Pulizzi, 2014).

 

 

Questions about channels and platforms usage were added using the "Uses and Gratification Theory" or "need seeking" (Windahl, Signitzer, & Olson, 2008) The theory of satisfaction and gratification is based on two core questions: 1) why are people attracted to certain media? And 2) what kind of satisfaction does the media provide for people?

This was operationalized as follows.

Why are people attracted to certain media?

 

 

Platforms

·        I use this social media platform for information to ship my items.

Tested on 5 level questions on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree).

Content types

·        I use this media type for information to ship my items.

9 level questions on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree).

Media types

·        I consume these content types for information to ship my items.

 

Tested on 3 level questions on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree).

(Questions on satisfaction were omitted from the questionnaire to avoid duplication since it was tested in the interview).

Motivations

According to Mason and Bauer (2012), motivation is the intention of achieving a goal.

(Carpenter, Bauer, & Erdogan, 2012)

Motivation questions were added to discover what factors drive the customers to subscribe to E&A’s services according to Maslow hierarchy of needs  (McLeod, 2007), and three factors were tested.

1) reliable 2) handling with care and 3) consistency. The three dimensions were operationalized as follows.

Reliable - I use their service because they are delivered on time.

Handle - I use their services because my goods are handled with care.

Consistent - I use their services because of the consistent quality of services in handling the customer's goods.

 

Tested on 3 level questions on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree).

Demographic questions

Questions about gender, title, and the location of the company they work for were added according to (Mooi & Sarstedt, 2011).

 

List of 5 levels, single select option.

1 = Marketers,

2= logistics experts,

3= business owner,

4= Salesperson, and

5 = CEO

 

Operationalization

 

2.3 Data collection & analysis

The survey for this study was distributed from October 16, 2021, until October 28, 2021. Prior to distributing the survey, a validity check was conducted to ensure the accuracy and clarity of the measurements being used. The questionnaire was shared with fellow students and the staff of E&A, likely for feedback and to gauge their understanding of the questions. This process helps identify any potential issues with the survey design, wording, or comprehension before it is distributed to the target respondents. In this way the reliability and validity of the data collected through the survey was enhanced.

The distribution of the questionnaire was done online through the social media channels of the company and there was a total of 70 respondents. The final sample drawn from this population consisted of 67 respondents (3 respondents were invalid because they were part of the pilot test).

QUANTITATIVE RESULTS

Before analyzing the data, it had to be prepared in Microsoft Excel. SPSS was used to analyze the data and responses from several items that had to be coded in this statistical program to create clusters (see datafile on Blackboard).

3.1 Hierarchical Cluster Analysis

A thorough and organized hierarchical cluster analysis was conducted to lay a strong foundation for subsequent K-means clustering. The primary focus was on utilizing motivation variables as the key clustering variables. The ultimate objective was to determine the most suitable number of clusters for further exploration and analysis. After examining the dendrogram, it appears that three distinct clusters could be investigated.

3.2 K-Means Cluster Analysis

After conducting a hierarchical analysis, we proceeded with a K-means cluster analysis to further identify patterns and similarities within the data. This partitioning method made it possible to group observations into three distinct clusters based on their similarity in specific variables  (Soetewey, 2020). This approach proved to be a valuable tool in achieving our analysis goals.

 

             Distances between Final Cluster Centers

 

 

 

 

 

 

3,73

Table 2: K-mean cluster analysis Results (Motivations amongst the clusters).

 

It is important to carefully examine the k-means clustering results for the three clusters. Table 2 shows that larger differences in k-means values within a cluster suggest greater dissimilarities among the observations in the cluster, while smaller differences indicate higher similarity. The k-mean values closer to 5 indicates a higher level of motivation for engaging with E&A's services. This information could be helpful for developing more targeted marketing strategies and improving overall customer engagement for E&A.

 

Interpretation of the results

Table 2 above, is the ANOVA table showing the final cluster centers. Yellow colour signifies a lesser preference while green signifies more preference. Based on the analysis, it appears that cluster 2 has the strongest motivation of using E&A's services. The values in this cluster are very close to each other and approach 5, which is a clear indication of high motivation. However, it is important to be careful when making decisions based on these findings, as there may be other factors at play.

 

Consideration of additional factors

The k-mean values in cluster 2 are very close to each other, whereas for cluster 1 and 3 there is a greater dispersion in k-means. In addition, the k-means in cluster 2 are closer to 5, indicating a higher motivation for the customers in that cluster. Therefore, customers in cluster 2 are motivated best for using E&A’s services. The conclusion is that we should drop clusters 1 and continue with clusters 2 and 3, which would probably consist of customers that could be profitable to E&A.

 

Future Steps and Recommendations

In order to make a well-informed decision about cluster priorities, it is important to conduct further research. By conducting a thorough analysis, a more comprehensive understanding of the clusters' implications can be gained, which will guide decisions effectively.

3.2.1 Profiling

A total of 70 respondents took part in this research (N=70). These were customers of E&A. The final sample drawn from this population consists of 67 respondents (3 respondents were invalid). Of the respondents there were just a bit more male respondents than female respondents (37 vs 30).

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