Value of Social Media Marketing
Problem Statement
In today’s digital landscape, firms are increasingly investing in social media platforms to engage with their customers, yet the actual impact of these efforts on consumer behavior remains unclear. Understanding whether social media presence translates into measurable changes in purchasing patterns is critical for justifying marketing investments and optimizing digital strategies.
A firm seeks to analyze the impact of its social media efforts on consumer behaviors by examining purchasing patterns before and after launching its Facebook page. Upon initiating its Facebook presence, some consumers choose to become fans of the firm’s page (the treatment group), while others do not (the control group). Importantly, consumers in both groups continue to purchase from the firm throughout the observation period, providing a natural experiment to assess the causal effect of social media engagement on consumer behavior.
The firm collects the following data to address this questions.
Data Dictionary
| Variable | Description |
|---|---|
| ConsumerID | Identification code for consumer |
| Group | \(Group=\begin{cases} 1, & \text{if $ConsumerID \in TreatmentGroup$}.\\ 0, & \text{otherwise}. \end{cases}\) |
| Period | \(Period=\begin{cases}1, & \text{if $Week \geq 55$}.\\ 0, & \text{otherwise}\end{cases}\) |
| Week | Purchase occasion of consumers at weekly level |
| Spending | Dollar spending by individual consumers during each purchase occasion |
Theoretical Background
Impact evaluation of any policy intervention is one of the primary interests of policy makers. Such an analysis leads to evidence-based policy making.
In marketing, managers are constantly overwhelmed with various types of decision-making such as campaign design, new product development, market expansion, marketing promotions. One of the key questions that marketing managers need to know is “What is the impact of their decision making on the firm’s bottom line?”
In marketing, practitioners have widely used A/B testing to compare the two versions of some decision-making (e.g., whether to have white vs. blue background for the website) to determine which has better performance.
A/B testing is the basic kind of randomized controlled trials (RCTs).
The basic idea of RCT design is as follows:
- Treatment: Carefully formulate the intervention (e.g., whether to give price promotion or not?)
- Randomization: Randomly split the population into two groups:
- Treatment group: Those who receive the treatment (e.g., gets promotion).
- Control group: Those who don’t receive the treatment (e.g., does not get promotion)
- Measure the outcome of interest for both the groups, i.e., control and treatment groups,
- before the treatment has taken place
- after the treatment has taken place
- Compare the outcome across periods and across groups.
Difference in differences (DID) is one of the methods to carry out the last step of comparison.
Reference
Please refer to following article as a useful reference for this assignment
- [The Effect of Customers’ Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation]https://doi.org/10.1287/isre.1120.0460)
Social Media Data
A marketing manager from the firm has selected scanner panel data from a two-year period for this analysis. In the first year (weeks 1-54), the firm did not have a social media presence, while in the second year (weeks 55-108), the firm maintained its social media presence. The analysis assumes that the event — consumer participation in social media — takes place in week 55 for all consumers in the treatment group. The manager randomly selects 200 consumers from each group and observes their purchase behaviors.
Total observations: 14030
Total weeks: 108
Total customers: 400