Project Data Collection Plan Essay

Project Data Collection Plan Essay.

Project Data Collection Plan Essay

Project Data Collection Plan


June 18th, 2018

Project Data Collection Plan

DefinitionFor entrepreneurs, digital data is useful for any professional career because it is required in the planning process for the marketing and conducting the business. Every entrepreneur focuses on collecting useful data that can be used to make relevant decisions of the best business to start alongside creation of more targeted campaigns that hit the nail of the suitable audience.
Digital Data NeedsDigital data is needed to identify common behavior of the consumers so that the entrepreneur can decide on the best business to start in the market (Baltzan, 2008). Data guides on how consumers behave while online which is important in the selection of marketing channels for the new business. Digital data improve relevancy because it guides on the themes and topics that can be used when marketing a business. This increase relevance of campaigns to the audience where the audience are communicated only what they want to hear. Digital data increase flexibility where the entrepreneur learns the best ways to communicate to the audience.  This improves the agility of the campaigns which allows an entrepreneur to collect real-time data during the campaigns. Digital data help in the realization that not all audience is created the same because the data collected from consumers help on the realization of the needs (Sapsford & Jupp, 2006).  It assists entrepreneurs to conduct personalized campaigns with an aim to get the individual needs. Digital data assist entrepreneurs to understand the different users behaviors, their preferences, dislikes and likes (Baltzan, 2008). The data allow association of the marketer and the consumer through online platforms.  
Type of data                         Users of the dataIdentity data which includes any information that allows an individual to be uniquely identified (Hair & Lukas, 2014). This includes personal information such as names, post talk, email, date of birth, gender etc. Quantitative data is another type that describes how customers behave or reacts to the introduced business. This data include the communication channels used by the individual, transactional information, customer service information etc. Descriptive data which includes additional information pertaining to that customer. This can be family details, career details or even lifestyle of that customer. Qualitative data describes the potential behavior of consumers towards the business idea (Borkar, 2012). This can be in form of attitudinal information, motivational and the opinion of the consumers towards the proposed project. The data will be used by the management and the marketing team to identify the suitable business for the consumers.  The data will also be used by academic institutions for research purposes. Vendors and stakeholders of the business can use the data to advice the entrepreneur on which business is suitable for the stated consumers (Hair & Lukas, 2014).
How data management system contribute to organizational collaborationData management system defines the organizational collaboration because an organization that has a system connected to all departments will enhance collaboration. Any business should ensure that the data management system is connected for all departments in a way that they will work together to achieve a common goal. The choice of data management system in any business has a great contribution to how the departments will work together. The use of digital data and technology is the key to enhanced organizational collaboration.
Data collection  Data will be collected by the use of questionnaires, focus group discussions, observation and personal interviews (Sapsford & Jupp, 2006). These methods will ensure coverage of information for all consumers. Data will be stored in databases for easier access by the user. It can also be stored in computer hard disk where it can be accessed whenever needed. Emails and other online platforms like Facebook offer secure storage for the data because it has minimal likelihood to get accessed by unauthorized personnel. Cloud computing is also a safe place for data storage together with virtualization and big data. Data analysis will include hypothesis testing, the use of mean, standard deviation as well as regression (Sapsford & Jupp, 2006). The use of SPSS in the analysis may also apply in this case. Distribution of the data can be done majorly by the use of online platforms. Cloud computing, big data and virtualization will act as platforms where customer information can be stored and distributed to different users. Emails, billboards, and use of social media can also be applied in distribution of the data.  


Borkar, V. R., Carey, M. J., & Li, C. (2012). Big data platforms: what’s next?. XRDS: Crossroads, The ACM Magazine for Students19(1), 44-49.

Hair Jr, J. F., & Lukas, B. (2014). Marketing research (Vol. 2). McGraw-Hill Education Australia.

Sapsford, R., & Jupp, V. (Eds.). (2006). Data collection and analysis. Sage.

Baltzan, P. (2008). Business-driven information systems. McGraw Hill Higher Education.

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