Impact of social media on Marketing

– Managerial and Market Research

Impact of Social Media on Marketing

Group II

Mathematical Equation

Marketing is the dependable variable and the independent variables are social media sites such as Facebook, Instagram, LinkedIn, WhatsApp, and Twitter.

Hence the equation would be:

Y = X1 + X2 + X3 + X4 + X5

In the above equation:

Y stands for Marketing

X1 stands for Facebook

X2 stands for Instagram

X3 stands for LinkedIn

X4 stands for WhatsApp

X5 stands for Twitter

The equation shows how Marketing is affected through these different social media sites. Since social media has an impact on marketing, this makes marketing a dependent variable and the social media sites are independent variables.

Indicators

The link between Marketing (Y) and the independent variables (X1, X2, X3, X4, X5) is that social media allows running ads that help promotions. Marketing on social media also helps to generate views, creates connections, and networking.

Reliability and Validity

· Internal reliability - We observe people and rank their social abilities in internal reliability. Diverse people have different perceptions and observations, and we require a highly co-related output in a survey approach to arrive at a fixed and solid conclusion.

· Construct Validity - In order to see the majority and compare the same kind of doctrine, we compare the ideology of people we got from the survey and try to compare the same features among people.

· Convergent Validity - Since only one type of data collection method is utilised in this procedure, it does not have convergent validity.

Limitations of Quantitative Research

· Lack of resources for data collecting for research - Large-scale study would be an appropriate sample size in quantitative research methods. Because data from the entire country cannot be collected, data from a single province (Ontario) would be collected.

· Expensive and time-consuming - Data collection for the study might be time-consuming and costly, making it difficult to acquire all of the information that was required.

· Limited outcomes in quantitative research - The participants are asked closed-ended questions while taking the survey. As the responses might be any of the expected ones, this limits the possible outcomes.

Research Method

The data for this study will be collected by a survey method. This makes it easy to reach out to a large number of people at once, as well as collect data, integrate and analyse responses. It also helps in comprehending the responses, which may lead to a research conclusion. The aim would be to conduct surveys with 50 to 75 people, focusing on today's youth (ages 18 to 25) and middle-aged individuals (26 to 45). There would be 20 to 25 questions which would not take up too much of their time (participants') but, would help obtain the information needed for the study. The surveys can be sent via e-mail or even WhatsApp, depending on the preferences of the participants.

Quantitative Data Analysis

As per the mathematical equation of this research, there are 5 independent variables which are – Facebook (X1), Instagram(X2), LinkedIn(X3), WhatsApp(X4) and Twitter(X5). Each of these independent variables would have questions that vary accordingly, that can be categorised into;

· Nominal data – The survey may include questions related to the participant’s gender, types of social media they prefer to use. The options(answer) to these questions, can be named but not measured.

· Ordinal data – Since there may be questions where the participants would have to choose whether they agree to the question or disagree the same. The responses to these questions are the ones that can be measured on a particular scale.

· Interval Data – There could be questions where the participants would have to choose an option which may have a particular option which shows a bracket. For instance, age of the participants can be between 10-year age bracket and there could be 3-4 options accordingly.

As it has been devised, the 3 types of data are – Nominal, Ordinal and Interval. To analyse the data the following 5 tests will be used:

· Contingency table – It can be used for Nominal or Ordinal data, and it will help in comparing any of the two variables. For instance, between men and women who agrees or disagree that Facebook is the best market place.

· Pearson Correlation – This one is usually used for interval data. This would help to find a correlation between interval data and another type of variable.

· Kendalls Tau – B – This would be used for ordinal and/or interval ratio. For instance, comparing difference between participants who prefer using Facebook to participants who prefer Instagram.

· Spearmans Rho – They only look at pairs of ordinals. For instance, comparing difference between participants who prefer using Facebook to participants who prefer Instagram.

· Cramers V – This test would be between 2 nominal variables, reported along with contingency table.