In the following chapters it is intended to explain the methodology used. The purpose of this section is to provide the basis to support the analysis. In the sections below it will be presented the research design, research method, the research strategy, and data collection and analysis. Furthermore, the challenges and ethical implications of this data is also described.
5.1 Research design
A research design is the logic that links the data to be collected and the conclusions to be drawn to the initial questions of a study; it ensures coherence. Another way of viewing a research design is to see it as an action plan for getting from the questions to conclusions.
Rowley, J. (2002).
An explanatory research is conducted, taking the example of marketing automation roll-out plan of GE Healthcare and the sources mentioned in the theoretical framework. Based on the context of B2B, the challenges of marketing and sales operations, and this approach to marketing automation, it is intended to unveil the best practices for a successful implementation of this technology.
In order to answer the research question which is “how does the implementation of marketing automation impact B2B companies?” the following objectives were set:
1. To evaluate the key factors of adoption of an enterprise software for marketing automation
2. To define the best practices to implement marketing automation 3. To identify the impact of marketing automation
5.2 Research method and strategy
This project intents to use a deductive approach to answer the research question. The research is based on secondary data collected from the case study of a B2B company, GE Healthcare, and its experience with marketing automation. As explained by Rowley, J.
(2002), case studies as a research method or strategy have traditionally been viewed as lacking rigour and objectivity when compared with other social research methods […] On the other hand, despite this scepticism about case studies, they are widely used because they may offer insights that might not be achieved with other approaches.
A pattern matching is deployed to analyse the data found in the case, in support with the theory presented and the input of the interview. According to Saunders, M. L., et al., (2009, pg. 500), using this approach, one will need to develop a conceptual or analytical framework, utilising existing theory, and subsequently test the adequacy of the framework as a means to explain findings.
Moreover, a case study provides explanatory data that helps understand with narrative a situation that happened in the past. According to Yin (2003), (as cited in Saunders, M. L., et al., 2009, pg. 500), another pattern matching procedure, which refers to as a special type, involves an attempt to build an explanation while collecting data and analysing them, rather than testing a predicted explanation […] explanation building is designed to test a theoretical proposition, albeit in an iterative manner, rather than to generate theory inductively […] Yin states that his hypothesis-testing approach is related to explanatory case studies.
A definition of case study by Stake (1995), (cited by Simons, H., 2009, pg. 19) explains that a case study is the study of the particularity and complexity of a single case, coming to understand its activity within important circumstances. Simons, H., (2009) explains that what defines a case study is its singularity – of the phenomenon being studied.
In this research, the case study involves a singularity in detail from which the implementation of marketing automation took place. It considers specific elements that were relevant for the company to cover and that are more specific to B2B marketing and sales.
The singularity of this case, however, presents concepts that are applicable to other B2B companies.
5.3 Data collection
The case study of GE Healthcare is instrumental to obtain the qualitative data for the analysis. According to Simons, H., (2009), instrumental (a case study) is where a case is chosen to explore an issue or research question determined on some other ground, that is, the case is chosen to gain insight or understanding into something else. According to Woodside, A. G. (2010), […] to insure that the data have a high degree of nomological validity (i.e., empirical pattern of findings fits theoretical pattern), the research might incorporate alternative questions that favor each theory (e.g., several different scenarios illustrating alternative theories could be evaluated by the respondent to see which best matches his/her
“reality”).
In this case study, the roll-out plan provides an understanding of the considerations by the project management team for structuring the implementation strategy. This data is of great value to understand how a large and well-known company used to evaluate their challenges, and what changed after the implementation. The specific case to GE Healthcare was also selected due to the availability of the information on the implementation plan, relevant to support the context of marketing automation and B2B.
Although different tactics of collecting data were evaluated, including surveys, there is a major challenge when researching B2B companies. Finding the right audience for the surveys or interviews is complex due to the different roles, understanding and actual experience with the subject of study. Also, according to Simkin, L. (2000), B2B surveys are notoriously difficult to conduct owing to secretaries gatekeeping, busy managers not wanting to “waste time'' attending discussion groups or completing questionnaires, incentives not being as attractive to recipients as in much consumer research, and confidentiality concerns being a major drawback. Yet, it was possible to obtain references from the interview conducted with the expert in the field of digital marketing and technology.
The data collected from the interview provides qualitative data based on experience with the implementation and execution of marketing automation applications and the coordination with sales and marketing departments. The relevance of the data collected is subject to the application in B2B using Marketo, the same solution explained in the case of GE Healthcare.
The questionnaire made was also based on the initial observations of the case study and to fit
into the objectives of the research. This way it is intended to use compatible data and have a perspective in the same level.
5.4 Data analysis
The analysis of the data gathered is oriented to a subjective approach. As the base of the data collected comes from different sources of content and statements by experts, in a field that has been scarcely studied, its analysis requires standardising concepts and interpretations.
Also, processes are different in different companies, but best practices that prove an overall success can be explained in a general way.
This study intents to analyse the implementation of marketing automation on two dimensions: the technical and the operational aspects of the implementation. For this purpose,
5.5 Challenges in data collection
There was a challenge to find data that could explain in more detail the process followed to obtain the results in terms of sales. This data was not found specifically in the notes within the account statements of GE Healthcare, nor there were further explanations in the different sources found. In addition, large B2B companies like the one presented often have strict policies for sharing information.
As a relatively new approach to marketing and sales, there are few case studies to compare.
There is an overall lack of understanding about this technology, and only few companies have been able to structure an implementation plan that considers all the factors. The approach mentioned in the strategy was to make use of the information available and use suppositions in support with the other framework presented.
Another challenge in data collection is the often-strict policies of companies in sharing information about their processes. This is due to their position against competition, in which an established process represents a competitive advantage. The more the companies implement this solution and share their success stories, the better it will be for researchers to gather the necessary data for their studies.
5.6 Ethical considerations
The data gathered to analyse the case study was public and available. Moreover, consent was given by the author of the roll-out plan to use and reference the information presented. As for the interview conducted, there is a policy that does not allow collaborators to talk about the internal processes of the company, nor it is able to publish content that points directly to the company. For this reason, the name of the company and collaborator are subject to disclosure. It is also important to define that the only purpose of the data gathered from these sources is merely for its relevance in the study and are not to be used in any other way.