The Synergy of Social Media Communication Engagement and Non-Profit Success:

An Investigation into the Correlations between Online Metrics, Website Traffic, and Financial Outcomes in the Non-Profit Sector

Ray Xiaorui Yu

Director: Dr. Richard Maloney

Instructor: Dr. Ruby Yu

Submitted in partial fulfillment of the requirements

for the Performing Arts Administration Graduate Program

in the Department of Music and Performing Arts Professions

at New York University

[2023]

Abstract

This study delves into the crucial relationship between social media engagement, website traffic, and the financial performance of non-profit organizations. It emphasizes the potential advantages and impacts of adopting effective social media strategies to stay competitive in today's digital landscape. Despite the increasing importance of social media marketing, many non-profits remain reluctant to invest in such strategies due to constraints like limited resources, expertise gaps, and organizational culture barriers.

The research analyzes correlations between various social media metrics, website traffic, and financial performance, shedding light on the importance of a robust online presence for non-profit organizations. The results demonstrate significant positive correlations for the majority of the proposed relationships. However, the connection between social media interactions and website traffic remains inconclusive.

The findings underscore the need for non-profit organizations to adapt and embrace social media marketing to improve their financial performance, reach new audiences, and maintain competitiveness in an ever-evolving digital environment. The study acknowledges its limitations, including data unalignment and a limited scope of social media platforms, and recommends future research directions for a more comprehensive understanding of the relationship between social media engagement and non-profit success.

Keywords: 1. Social media 2. Marketing 3. Non-profit organizations 4.engagement

5. Interaction  6. Corporate communication 7. Statistical analysis 8. Financial performance

Introduction

The rising popularity of focus on social media strategies has changed the traditional corporate communication approach. Firms and organizations have largely invested in social media marketing. In 2021, 91.90 percent of U.S. marketers in companies larger than 100 employees were expected to use social media for marketing purposes. In the United States alone, social media marketing spending is expected to exceed 17 billion U.S. dollars in 2019 – almost a ten billion increase compared to 2014 (Dencheva, 2023a)1 

The reason for the popularity of social media in marketing is its effectiveness.  According to the findings, out of 2750 respondents, 37.9 percent reported that they had made anywhere from one to 25 percent of the time a purchase after viewing an online or social media advertisement. During a July 2022 survey of B2C content marketers primarily from North America, 88 percent of respondents stated they used Facebook to distribute content in the 12 months leading up to the survey (Dencheva, 2023b). 2Additionally, 91 percent said they had used Facebook for paid content promotion in the same period. A survey of business-to-business marketers conducted in November 2022 found that 22 percent of respondents used LinkedIn as their preferred type of social media for their content distribution, while 21 percent used Facebook for the same purpose (Dencheva, 2023c).3

As a social media strategist, I managed communication campaigns for for-profit organizations with revenue sizes ranging from 50,000 US dollars to millions. These organizations' main social platforms are Meta (Facebook and Instagram), which includes media buying on Facebook and Instagram. The effectiveness is obvious: multiple businesses achieve an average of 30% consistent growth in New York for clients' customer size and incomes. For the entertainment industry, such as gaming apps, they produced and optimized over 1,500 pieces of video content per year under my management alone, including Avia Games INC, Farlight Games Industry, and many more. Investing in social media ads and content production sometimes exceeds 70% of the company’s total expense. With digital media marketing efforts, proven customer growth, and consistent spending on social media ads, one company successfully attracted 400 million dollars of new investment in 2021.

In contrast, some non-profit organizations are not interested in investing largely or even a little into social media marketing. Due to the interviews and the company’s financial report, some non-profit organizations focus little or none on digital marketing, according to interviews initiated in 2021 and 2022.  For Roulette Intermedium, from 2021 and 2022, it had no spending on advertising. For Flushing Town Hall, they mentioned: “We do not need to market. We only need volunteers.” Surprisingly, in some non-profit organizations in the New York area, using social media is not considered to engage community audiences, advertise programs and venues, or use social media as a fundraising tool. According to Facebook Internal Data, 2018, more than 480 million people worldwide are connected to a nonprofit page on Facebook. The unstoppable social media marketing trend should be paid attention to and needs to be deeply researched for non-profit organizations.

Are non-profit leaders’ reasons for not investing in SMM (Social Media Marketing) thinking marketing art should follow the saying “good wine needs no bush?”

• Limited resources: Nonprofits also have smaller marketing budgets than for-profit businesses and therefore tend to receive less social media attention (Kenton, 2022). 4

• Lack of expertise: Nonprofit organizations have a team with limited human resources. The responsibilities are shared between the paid team members, the volunteers, and the board of directors. The skeletal team also manages social media marketing for nonprofits. But since the team has other responsibilities, they may not concentrate fully on social media (Goswami, 2021).5

• Limited understanding of social media platforms: With social media platforms in perpetual beta mode, which is the consistent release of new functions, change is a constant in social media platforms. This makes it challenging to research social media marketing and the metrics associated with social media (Dwivedi et al., 2021). 6

• Complex metrics: It is important to establish data sources of record for each KPI identified in the metrics framework (during the planning stage) to ensure all parties involved agree on a single version of the truth about program performance, as well as determine the necessary data infrastructure to plan for and establish in time for the launch of any social media effort (Murdough, 2009).7 

• Organizational culture: Nonprofit organizations are notorious for leading the charge with print materials, brochures, and direct mail campaigns to round up supporters and donations. However, most donors who respond to direct mail postcards and letters are over 55 years old. This leaves a huge segment of potential donors untapped. It’s essential for nonprofits to adapt to the rise of digital marketing and social media marketing (Dublino, 2023).8 

Non-profit organizations are facing a pressing need to adapt to the digital era and leverage social media to enhance their marketing impact. The rise of social media platforms is transforming the ways in which non-profit organizations can engage with their audiences, build external relationships, and operate as social networks (Kanter & Fine, 2010).9 The COVID-19 pandemic has only accelerated this trend, as non-profit organizations have had to shift their operations online and embrace digital channels to reach their stakeholders. However, many non-profit organizations still struggle to leverage social media effectively, lacking the expertise or resources to develop a comprehensive digital strategy. As a result, there is still a significant gap between the advanced social media marketing strategies utilized by the private sector and the underdeveloped strategies implemented by non-profit organizations. This discrepancy can lead to missed opportunities for nonprofits to engage with new audiences, generate donations, and drive social change.

The urgency for nonprofits to embrace social media cannot be ignored, as evidenced by recent studies highlighting the importance of digital engagement for the success and sustainability of these organizations. It is a must for non-profits of all sizes to learn how social media marketing can benefit their overall performance, better engage the community, promote their programs, and attract donations. While the nonprofit sector needs a research paper to identify the relationship between the efforts in social media channels and the organization’s growth and development, this paper might potentially help with this research gap. Thus, detailed data-driven research can benefit non-profit sectors to re-evaluate and adjust their communication strategy and financial planning on social media marketing. In this paper, I will explore the following question:

Why is non-profit social media engagement important to the organization’s development and growth? What can nonprofits do for social media marketing?

Literature Review

Social media has become a ubiquitous aspect of modern society, transforming the way people communicate, socialize, and consume information. The proliferation of social media has also led to its adoption as a critical tool for marketing and communication in both for-profit and nonprofit organizations. As such, there is a growing body of literature exploring the use and effectiveness of social media strategies for achieving marketing and communication objectives. This literature review provides an overview of recent studies on social media use in marketing and communication, with a particular focus on the challenges and benefits of using social media in non-profit organizations. The review also examines the role of social media engagement in building strong relationships between organizations and stakeholders and its impact on consumer behavior towards social ventures.

Social media is now developed as a key marketing focus for many organizations. The study shows the effect of social media on significant changes in consumer behavior (Igarová, Kádeková, & Košičiarová, 2022).10 A recent study shows an overview of the behavior of social media users in association with their overall relationship to advertising on social media and influencer marketing based on a questionnaire survey. Social media is able to expand beyond geographical borders; social media create strong links between consumers in different states and social environments. The study shows that the total number of respondents born in the years 1995 – 2010 (Generation Z), of which 71% are affected by advertising contributions on social media. Advertising on social media also stimulates shopping behavior by more than half of the interviewed Generation Y members. A total of 57% of respondents answered the question in the affirmative. And Generation X, born between 1966 – 1976. 44% of people in this group are influenced by advertising on social media when purchasing products. The study shows that social media can affect a wide range of age groups' audiences resulting in stimulating purchasing behavior. The limitation of the study is a relatively limited sampling size of 726 respondents replying to the researchers’ questionnaires, and the questions in the survey were not revealed in the paper. Responses from the participants to show whether their purchasing behavior was affected by social media could be subjective. However, it showed an aligned result with the popularity of marketers’ use of social media, that social media is widely used for organizations’ strategic communication.

A qualitative research paper explaining the exploding use of social media in the past decade has underscored the need for guidance on how to build SMMSs that foster relationships with customers, advance customer engagement, and increase marketing performance (Li, Larimo, & Leonidou, 2021).11 The paper explained a conceptualization of the

process of developing social media marketing strategies, which is similar to the theory of change methodology. The paper identifies the final output for the social media marketing objectives should be customer engagement, which reflects the outcome of the firm–customer (as well as customer–customer) connectedness and interaction in social media (Harmeling et al. 2017)12. It is essentially a reflection of “the intensity of an individual’s participation in and connection with an organization’s offerings and/or organizational activities, which either the customer or the firm initiates” (Vivek et al. 2012, p. 127)13.  

Another recent research assessed four social media platforms:  Facebook, Twitter, Instagram, Pinterest, and YouTube, by initiating in-depth interviews with 20 senior FMCG marketers, followed by an online questionnaire comprising 21 senior marketers (Valos, Maplestone, Polonsky, & Ewing, 2017).14 The finding was: engagement is best facilitated by Facebook and Instagram; agility through Facebook, Twitter, and Instagram; reach through Facebook, Instagram, and YouTube; and listening through Facebook, Twitter, and Instagram. However, the selection of tools should relate to the specific objectives, segments, and markets being targeted, as with all media selection. Higher levels of engagement, while being challenging for marketers (Barger, Peltier, & Schultz, 2016; Malthouse, Calder, Kim, & Vandenbosch, 2016)15, can lead to greater brand equity, share of wallet, retention, return on investment (ROI) and proactive WOM (Schultz & Peltier, 201316; Vivek, Beatty, & Morgan, 201217).

To evaluate the effectiveness of the organization’s social media strategy, it is recommended to use a data-driven decision-making method. One study found that the tourism and hospitality industry should invest more resources in analyzing the behavioral patterns of online users by utilizing big data analytics (Sakas, Reklitis, Terzi, & Vassilakis, 2022)..18 The study executed statistical analysis of the extracted tourism big data to find the correlation among the KPIs of 10 tourism organizations’ websites and social media. The outcomes clearly demonstrate the efficiency of social media advertising for companies aiming at building social interactivity and traffic. The study results evident that the future of digital advertising lies in the development of hyper-targeted advertisements. It advised hospitality marketers to deliver personalized messages to the targeted audience based on their behavior and receive valuable feedback. Though the study is limited to the focus of the tourism and hospitality industry, and the sampling size is 10 organizations, the quantitative data-driven methodology provides a relatively high confidence level of results that can be referred to the culture and entertainment industry. It also suggested the marketer pay close attention to UGC type of content and use AI-powered tools to boost the user experience, detecting patterns in data and forecasting behavioral attitudes.

A publication explains the doubts and concerns of non-profit organizations about using social media (Kanter & Fine, 2010).19 Marnie Webb, the co - CEO of TechSoup Global, asked,  “What, if anything, does all of the clicking, blogging, and  “ friending ”  add up to in the end? ”  Some non-profits still question that even millions of people use social media to connect with one another around causes, but exactly what difference does it make?  In recent history, nonprofit organizations have veered toward keeping their organizations behind closed doors. Some have worked hard to keep their communities and constituents at a distance by pushing out messages and dictating strategies without listening or building relationships. These habits and missteps hurt and limit organizations and their communities. The book encourages non-profits to start experimenting with social media and faster adapt to the changes in communication. It also suggested organizations use mapping techniques such as web crawls and web scrapes to implement qualitative analysis. Though the publication did not provide detailed data evidence to show the correlations about what social media can truly help with a non-profit’s development, due to the early stage of social media studies when the publication was released, it explained the reasons and challenges that a non-profit organization.

A more recent study summarized the challenges of using social media and implementing strategies (Gordon, 2017).20 The study collected data through semi structured interviews, the review of documents, and the review of the social media pages of five social media marketing professionals in nonprofit professional membership organizations in the Chicago region. The issues that the organizations with implementing SMMS are the culture of the organization, keeping affiliates aligned with the brand, tracking content for effectiveness, an appropriate time to engage, lack of training staff, lack of subject matter experts, lack of leadership understanding, difficulty engaging users, lack of measurement tools, lack of measurement tools, prioritizing content, lack of bandwidth, and managing negative posts.  The findings of this study also indicated the need for leaders to develop social media marketing strategies for increased engagement. Social media leaders should use analytical tools such as Google Analytics and Simply Measured Analytics to measure the impact of the content posted on their organizations’ social media pages. Chary (2014) noted social media marketing is the effort of social media marketing leaders to develop content that attracts consumers and includes the customers’ willingness to share the content with others to create brand awareness. However, the research does not indicate what aspect and how social media can benefit a nonprofit organization.

One study conducted interviews with South African non-profit sectors (Makgosa, Botha-Ravyse, & Van der Merwe, 2019).21 It also argues that content marketing uses different social media platforms on which non-profit organizations could manage content to draw attention to and ultimately attain a favorable brand. The study's findings yielded valuable insights into the ways that non-profit sectors in South Africa practice social media communication. The benefits of using social media for communication are acknowledged, yet vital aspects such as sourcing content, considering stakeholders’ needs and demographics communication, using available planning tools, and recognizing employees as internal ambassadors are not considered.

While social media can change consumers’ behavior, as other communication channels, they can be used to drive the target audience’s behavioral change for organizations to achieve their mission and vision more than simply purchasing activity. A study conducted in Ghana surveyed 485 commercial drivers who participated in a corporate social marketing campaign aimed at reducing road accidents. The results showed that the attributes of the corporate social marketing campaign, such as persuasive communication strategies and incentives, had a significant positive impact on the drivers' behavior change (Tweneboah-Koduah & Coffie, 2022).22 The principles and strategies discussed in the paper could potentially be applied to non-profit organizations as well, as they also aim to promote positive social change.

Social media can be a communication channel used for non-profits as general management, public relations, and fundraising tools (Suh & Hoang, 2021), 23 and major attention is required when non-profits face the fact that nonprofits today are operating in an environment characterized by fewer resources, greater demands and increased competition for donors, volunteers, and clients (Hackler & Saxton, 200724; Levine & Zahradnik, 201225). One study examines 319 museums’ data from the 2013–2014 fiscal year of NCCS data, official museum websites, and six social media platforms. This study provides empirical evidence that promoting nonprofit communication strategies that reach out to the public and stakeholders is not a passive phenomenon but, rather, depends to a large extent on a market-oriented strategy that requires real investment in these communication channels. Therefore, to remain sustainable and obtain sustained competitive advantages, nonprofits need to pay more attention to their social media communication strategies and better mobilize their communication resources.

A study about Fourth Generation NGOs' communication strategy, which are non-governmental organizations that operate in advocacy and social movements, highlights the importance of leveraging online platforms such as e-mail lists and web-based platforms to create a basis for the organization's stratification of audience according to its levels and scopes of identification with the NGO's vision (Duong, 2017).26 Though the limited sample size is the flaw of the research, the research reports an in-depth case study of a single NGO based in Washington, DC, and discusses how fourth-generation NGO constructs and implements its communication strategy through participant observation, informal interviews, and website and media reports.

Social media engagement is mentioned in marketing studies, and as well for non-profits’ communication research. A study shows that engagement is the third facet of propinquity and emphasizes that dialogic participants "give their whole selves to encounters" rather than maintaining a status of neutrality or as an observer (Li & Voida, 2022).27 The study used Grounded Theory as a research method to analyze interviews with nonprofit professionals regarding their use of social media for dialogic communication. SMPPs (social media public practices) most strongly embody the principle of engagement through the prevalence of posts that contain questions to solicit feedback. By asking questions, SMPPs can "get people thinking" and foster productive organization-public relationships with trust and mutual understanding. Overall, engagement is important because it allows for interactive dialogue between nonprofit organizations and their stakeholders, which can help build stronger relationships and improve communication practices.

Multinational corporations have identified advertising on social media as a marketing strategy, using it to drive the publicity of their engagement with their cause. Social media helps businesses allocate their experience and skills, step into their user's wisdom, permit users to support other users on the platform and obtain potential users by sharing quality content. Thus, social media advantages include brand growth and recognition, and user experiences through interactions, recommendations, and maintenance of credibility. Dedicated engagement in interactive conversations enables NPOs to communicate with bloggers and wider networks of representatives and investors not just to raise awareness of the audience but also to influence them and mobilize supporters of the organization (Mehrotra & Siraj, 2021).28

Social media engagement is important because it reflects the public’s openness and  willingness to participate in conversations and discussions with executive leaders, which contributes to organization-public relationship building (Yue, Men, & Hart, 2022).29 Researchers examined 1,200 tweets posted by 300 executive leaders (150 from each sector) over a period of six months. The study found that nonprofit leaders were more likely to use dialogic principles, while corporate leaders were more likely to use social presence strategies. However, both types of strategies were associated with higher levels of social media engagement. The study also suggests that public engagement with executive leaders' posts on Twitter can contribute to building mutual understanding and long-term relationships between organizations and their public.

A study also found that social ventures should not only attract interested segments through social media but also engage and enhance their sense of belonging and commitment (Park, Chung, Hall-Phillips, & Anaza, 2016)..30 The study used a quantitative research method and collected data from 304 US consumers through an online survey. The survey included questions about social cause involvement, identification, commitment, and loyalty to social ventures in social media. The researchers analyzed the data using structural equation modeling (SEM) to test the proposed six hypotheses and confirmed the positive impact of social cause involvement, identification, commitment, and loyalty on consumer behavior towards social ventures in social media.

Literature Review Conclusion

The literature review covers several aspects of social media use in both for-profit and non-profit organizations. One key finding is that social media has the potential to change consumer behavior and stimulate purchasing activity, particularly among younger generations such as Generation Z and Millennials. However, to achieve this, social media engagement is important as it reflects the level of interaction and connection between organizations and their stakeholders. This is particularly relevant for non-profit organizations, which often rely on building strong relationships with their supporters and communities.

The review also highlights the challenges and benefits of using social media in non-profit organizations. While social media can be an effective communication and marketing tool, nonprofits still need to be more certain in adapting to new communication trends and techniques. This is especially important as non-profits often operate in environments characterized by fewer resources, greater demands, and increased competition for donors, volunteers, and clients.

To assess the effectiveness of social media strategies, the review suggests the use of data-driven decision-making methods. One study showed that analyzing behavioral patterns of online users through big data analytics can help organizations build social interactivity and traffic. Social media analytics can also help organizations deliver personalized messages and receive valuable feedback, which can ultimately lead to higher levels of engagement, brand equity, and ROI.

The review also discusses the importance of social media engagement in building relationships and improving communication practices between non-profit organizations and their stakeholders. This includes the use of dialogic communication principles and strategies, such as asking questions and soliciting feedback, which can help foster productive organization-public relationships with trust and mutual understanding.

Given the importance of social media engagement, the review explains why Instagram will be assessed for this paper. Instagram is known for its high level of engagement and user interaction, making it an ideal platform for nonprofits to connect with their audiences. The review also highlights the use of Meta, specifically Facebook Ads Manager, to find the paid media correlation for the effectiveness of social media strategy.

To summarize, I provide a logic model to help deliver a clear visual representation of the research framework, illustrating how social media engagement can lead to increased financial revenue for non-profit organizations and contribute to achieving their mission and vision. It shows the steps and relationships between the output, outcome, and impact of social media strategies in non-profit organizations. The logic model (Figure 1) emphasizes the importance of social media engagement and revenue generation for non-profit organizations and provides a framework for understanding the research findings in the literature review. It also serves as a guide for the data collection and analysis process, enabling the assessment of the social media strategy's effectiveness in achieving the desired outcome and impact.

Figure 1. Logic Model of Implementing SMMS for NPO’s Growth

The literature review emphasizes the importance of social media engagement and data-driven decision-making methods for non-profit organizations to achieve their mission and vision. The main social media data to analyze for this paper is engagement, which reflects the level of interaction and connection between organizations and their stakeholders, and can ultimately lead to changes in behavior and improved communication practices.

From the literature review, it is found that there is limited research on the effectiveness of social media marketing strategies for non-profit organizations: While social media has been shown to have the potential to change consumer behavior and increase engagement, there is little quantitative evidence to suggest that social media engagement can have a positive impact on financial revenue and website traffic for non-profits. This paper will deliver research exploring the causal pathways through how social media engagement can contribute to non-profit development and growth.

Methodology

Data Collection Tools

To answer the question of why is non-profit social media engagement important to the organization’s development and growth and what nonprofits can do for social media marketing, this paper analyzes the relationship between social media performance for the selected organizations, website traffic, and growth in finance. For the quantitative data collection, I examined multiple non-profit organizations in the New York area for reported form 990’s revenue.

To investigate the use of web scraping tools for automated data collection from social media platforms, quantitative data is collected and analyzed. From the CFA Society new york conference, How Alternative Data Is Changing the Research Process, held on March 29, 2023, Kevin Nutter, System2’s Partner, which is a consulting firm helps investors integrate data science into their approach by providing sourcing, engineering, and analysis of big data as a service, explained:

It is difficult finding data. So for us, scraping is a huge component. When we talk about using different data, scraping is a great way to use different data. We have an in-house scraping team…So you know, from my perspective, it's very difficult to sort of dip your toes in and then have a successful outcome. I mean, obviously, you can do top lines top line, you know, there's a lot of platforms, out there there's a lot of great data, it's much more efficient now it's much cheaper, and that's great.31

Also, Paul Pickett, Business Development and Senior Account Executive at Vertical Knowledge, mentioned:

…Another popular use case for web scraping data is moderate social media platforms. By scraping social media platforms and websites, businesses and investors can collect data on consumer sentiment, brand mentions, and even consumer complaints. This data can be used to gauge public opinion on brand track on brands, track marketing campaigns' effectiveness, and even identify potential crises.32

Thus, to collect social media data, web scraping tools for public information were utilized. Three types of web scraping tools and data providers were implemented in this study for data collection: Influencity, an influencer marketing platform that provides access to social media profiles’ data and processes all in one; and Similarweb, which is an aggregation of online information and data including website’s traffic available to the public; and Meta ads library, that contains data regarding organizations’ paid media information on Facebook, Instagram, Messenger, and Audience Network; Cause IQ, a website that contains such as organizations’ financial data to help professionals prospect for nonprofits, research opportunities, benchmark their clients and enrich existing information. These three tools allow access to the latest real-time data on the organization's social media before April 27th, 2023, the website traffic data in Q1, 2023,  and the most recent reported organizations’ form 990 for their financial status, that mostly reported in 2020 and 2021.  

Selection of Examined Organizations

The selection of non-profits is limited to nonprofit performing art organizations based on the revenue of Cause IQ in the New York City, New York Area. This paper will reflect on the top 50 organizations related to the industry but exclude three organizations with primary NTEE code A6E: Performing Arts Schools and A25: Arts Education, Schools of Art.  The selection will focus on reported primary NTEE codes limited to business industries A61: Performing Arts Centers, A62: Dance, A63: Ballet, A65: Theater, A68: Music, A69: Symphony Orchestras, and A6A: Opera. Thus, the selection will be 41 organizations with the latest revenue from 207.7 million USD to 5 million USD.

The selection also excludes three organizations and is finalized as 41 organizations. The excluded organizations are Royal National Theatre,  The Perelman Center (PACWTC), and Lincoln Center for the Performing Arts (LCPA). Royal National Theatre, which is a British organization that has operations in the New York area, does not have an individual website or social media accounts for local management. The data will be affected by London’s audience largely, which is a unique case compared to other selections. The Perelman Center (PACWTC), the cultural keystone in the Master Plan for rebuilding the World Trade Center site, is in a status of preparing for opening in September 2023, based on its official website. Some of its social media channels can’t be found or are still in the early stage of development, and the website’s data is too new to be calculated.  Lincoln Center for the Performing Arts (LCPA), Also known as Lincoln Center Development Project, LCPA is a subordinate organization under Lincoln Center for the Performing Arts, and it does not have a separate website or independent social media channels.

The reason for the selection of these non-profit organizations is because of the limited research resources compared to the number of nonprofits in New York State. In the meantime, to avoid the significant difference in results for different business models, the focus of business program types, the overall structure of the organizations, and competition of different locations of the organizations, which might impact the weight of fact of budget, and results on SMM. The narrower niche of the selection of industry, location, and similar business model will contribute to the higher confidence level of the data analysis.

And also, to advance the result of the accuracy, the selections focused on top organizations in the latest reported revenue, but no focus on the smaller organizations because of the finding of the situation of some organizations in the latter group might have abnormal operation status, and the significantly limited resources, which could lead to unstable performance.  The larger revenue and asset can potentially indicate relatively stable operations and might have more resources and balanced and tested investment in communication strategy innovation.

The collection of the organizations’ financial data that is used to identify the performance of the organizations includes the most recently reported revenue, the revenue changes from the previous year, the most recently reported total assets, and the changes in total assets compared to the previous year’s reports.

Selection of Media Channels

The website data collected through the platform, a data provider Similarweb provides insight into the total monthly traffic in March, February, and January 2023, the website bounce rate (Average percentage of visitors who view only one page before leaving the website,) pages per visit, average visit duration (Average duration of time spent on the site), gender and age distribution,  organization websites’ audiences interests (The distribution of the categories most visited by the analyzed website's users,) and Social Media Traffic (The top social media networks sending traffic to the analyzed website on desktop.)

This paper will focus on organizations’ Instagram, Meta Ads Library from Meta Business Manager, and the owned website. Organization’s Instagram profile is an owned channel that is actively used by all organizations from the selection. Instagram supports various formats of content, including static pictures and the rapidly growing short-video reels. Also, as a Meta product, the Meta Business Manager is a major platform allowing organizations to advertise on Facebook, Instagram, Messenger, and Audience Network, as a paid media channel. Lastly, an organization's website traffic can be an indicator of the audience it attracts for the middle to lower funnel of marketing.

The obtained organizations’ Instagram data that is subject to analysis in this paper includes the numbers of total followers, average likes per post, average comments, average views per video post, and average interactions which means the total number of reactions, comments, and shares from an Instagram profile divided by the number of the posts. However, I chose to focus on the Average Interaction Counts as the primary metric because it provides a more comprehensive view of engagement that combines the quality of social media creative strategy with the audience size of the profiles. Due to the initial data collected, sometimes extremely small follower sizes of social media profiles could have unusually high engagement rates, because of the fact that data can not achieve stabilization for small audience sizes.  On other occasions, the number of followers cannot be used as a trustworthy indicator, because it weighted less in content engagement. The average interaction count takes into account both post engagement and the organization's social media presence, making it a more reliable metric for our analysis.

Meta Ads Library will show the paid media effort that was initiated directly from organizations’ Facebook pages. The data will show the counts of all ads on Meta’s placements from the organizations.

Table 1. Descriptive analytics of Performing Art Nonprofit Organizations 

Data Collection Limitations

The results of the study were used to gain insight into the effectiveness and usability of online social media presence using a few media channels’ data that include Instagram followers, likes, engagement, paid media effort on Meta, website traffic, and organizations’ revenue performance.

The limitation of data collection is unaligned and limited media data and financial data. The access to website data on social media performance and website traffic are restricted to recent and current data that is opened to the public. The available financial reports from organizations’ form 990 can only reflect the fiscal year of 2020 or 2021 due to the tax report time frame. The correlation of these factors and the growth of the company which is based on recent years of revenues, are not aligned, but only based on the assumption of the continuous organizations’ attention and resources on social media that is reflected by the latest data. The social media platform’s channels are also limited to a few and could be affected by the unalignment between the different organization’s media focus, the channels’ own audience demography, and the organizations’ audience.  

This study only focuses on a few digital media channels the organizations use. Website traffic can be affected by many other social media channels. Similarweb shows that some websites have major traffic from multiple sources, such as Twitter, Reddit, and Youtube. These are not assessed in this research.

The data focuses on the limited industries to reflect the potential use for non-profit organizations. However, it does not include all sizes of organizations or all types of organizations. The sampling size is still relatively small compared to all non-profit organizations, and the location of the selections still needed scaled research for different areas for a result that can be applied.  

Hypotheses

The purpose of this study is to explore the relationship between social media engagement and financial revenue and website traffic for non-profit organizations. The study aims to test nine hypotheses:

Hypothesis 1 (H1): There is a positive correlation between website traffic and financial revenue for non-profit organizations.

Hypothesis 2 (H2): There is a positive correlation between website traffic and total asset for non-profit organizations.

Hypothesis 3 (H3): There is a positive correlation between social media follower number (Instagram)  and financial revenue for non-profit organizations.

Hypothesis 4 (H4): There is a positive correlation between social media follower number (Instagram)  and total assets for non-profit organizations.

Hypothesis 5 (H5): There is a positive correlation between average social media post interaction (measured by likes, comments, and shares) and social media follower number (Instagram) for non-profit organizations.

Hypothesis 6 (H6): There is a positive correlation between social media video post views and total followers.

Hypothesis 7 (H7): There is a positive correlation between social media total post interaction and total followers.

Hypothesis 8 (H8): There is a positive correlation between the amount of social media posts and total followers.

Hypothesis 9 (H9): There is a positive correlation between the amount of social media follower number (Instagram)  and website traffic.

All hypotheses H1 to H9 are designed according to Figure 1 below. The total number of interactions is a metric assessing a social media profile in both quality and quantity aspects. The total engagement activity is contributed by the number of posts updated by the organization and also how engaging the content results in attracting interactions for every post. It is also needed to know if post accounts or average post interaction benefits the follower size individually. Besides the relatively traditional format of posts, the new format of social media is videos. The biggest difference in video content is the

nature of hyper-targeting short-video application’s algorithm. A short video is a relatively new form of communication. Due to its higher requirement of production skills and time frame, most New York organizations are still in the early stage of forming media teams specializing in it. Short videos can generate organic growth in audience size with the help of the platform’s hyper-target algorithm. Thus, I also choose to assess the correlation between video views and follower numbers. These aspects of social media can provide insights for organizations that are developing their social media.

To answer questions that some organizations have about how social media engagement from the followers can do, I also choose to test if social media followers that are attracted by the content posted can benefit website traffic and even more directly have a correlation with organizations’ assets and revenue which indicates organizations’ performance.

Since it is a research gap that few studies directly connect the social media and digital communication efforts with an organization’s assets and revenue, thus I used STATA to examine the cause-effect to test correlations. This process provides systematic qualitative studies with big data in the context of the themes as presented. There are 41 observations (see Appendix) used in the regression analysis.

Figure 2. Hypothesis Relationship between Social Media Engagement, Followers, Website Traffic, and Organizational Performance

The increasing use of social media by non-profit organizations has brought new challenges in terms of determining the effectiveness of social media strategies. This study aims to provide insights into the role of social media engagement in driving financial revenue and website traffic for non-profit organizations. By examining the relationships between these variables, this study can help non-profit organizations better understand the effectiveness of their social media strategies and make informed decisions in their future social media efforts.

Statistical Analysis and Results

Hypothesis 1 (H1): There is a positive correlation between average website traffic and financial revenue for non-profit organizations.

The regression results show that there is a statistically significant positive correlation between website traffic (measured by average monthly traffic in thousands) and financial revenue for non-profit organizations. The R-squared value of 0.1425 indicates that the model explains approximately 14.25% of the variation in financial revenue.

The coefficient for Average_Monthly_Traffic_K (0.1164377) is positive and statistically significant at the 5% level (P>|t|: 0.015), suggesting that an increase in website traffic is associated with an increase in financial revenue. Specifically, a 1,000-unit increase in average monthly traffic is associated with an increase of approximately $116.44 in financial revenue.

These results provide evidence supporting Hypothesis 1, which posits that there is a positive correlation between website traffic and financial revenue for non-profit organizations. Non-profit organizations should consider the potential benefits of increasing website traffic, as it may positively impact their financial performance.

Table 2. Regression analysis for H1

Hypothesis 2 (H2): There is a positive correlation between website traffic and total assets for non-profit organizations.

Hypothesis 2 examines the relationship between website traffic and total assets for non-profit organizations. The regression results indicate a positive correlation between these two variables.

The F-statistic is 11.54 with a p-value of 0.0016, which is statistically significant at the 5% level. This suggests that the model is a good fit for the data, and there is a significant relationship between website traffic and total assets for non-profit organizations.

The R-squared value is 0.2284, and the adjusted R-squared value is 0.2086, which implies that about 22.84% of the variance in total assets can be explained by the average monthly website traffic.

The coefficient for average monthly website traffic (Average_Monthly_Traffick_K) is 0.6864 with a standard error of 0.2020. The t-statistic is 3.40 with a p-value of 0.002, indicating a statistically significant positive correlation between average monthly website traffic and total assets for non-profit organizations. The 95% confidence interval for this coefficient ranges from 0.2777 to 1.0951.

In conclusion, the results support Hypothesis 2, suggesting that there is a positive correlation between website traffic and total assets for non-profit organizations. This implies that an increase in website traffic may lead to an increase in total assets for these organizations.

Hypothesis 3 (H3): “Total Followers” of Performing Art Nonprofit Organizations affect the “Revenue” variable.

Hypothesis 3 investigates the impact of "Total Followers" on the "Revenue" variable for performing art non-profit organizations. The regression results provide some evidence of a relationship between these two variables.

The F-statistic is 3.50 with a p-value of 0.0687, which is close to the 5% significance level. This suggests that there may be a relationship between the "Total Followers" and the "Revenue" variable, although it is not statistically significant at the 5% level.

The R-squared value is 0.0824, and the adjusted R-squared value is 0.0589, indicating that approximately 8.24% of the variance in revenue can be explained by the total number of followers on the non-profit organization's social media page.

The coefficient for "Total Followers" (Total_Followers_K) is 0.0689 with a standard error of 0.0368. The t-statistic is 1.87 with a p-value of 0.069, which is close to the 5% significance level but not statistically significant. The 95% confidence interval for this coefficient ranges from -0.0055 to 0.1433.

In conclusion, the results provide some evidence supporting Hypothesis 3, indicating that the "Total Followers" of performing art non-profit organizations may affect the "Revenue" variable. However, the relationship is not statistically significant at the 5% level. It is important to note that this result may still be useful for non-profit organizations to consider as they plan their social media strategies, but more research is needed to confirm the strength of this relationship.

Hypothesis 4 (H4): “Total Followers” of Performing Art Nonprofit Organizations affect the “Asset” variable.

Hypothesis 4 examines the impact of "Total Followers" on the "Asset" variable for performing art non-profit organizations. The regression results show evidence of a relationship between these two variables.

The F-statistic is 6.03 with a p-value of 0.0186, which is statistically significant at the 5% significance level. This suggests that there is a relationship between the "Total Followers" and the "Asset" variable.

The R-squared value is 0.1340, and the adjusted R-squared value is 0.1117, indicating that approximately 13.4% of the variance in the total asset can be explained by the total number of followers on the non-profit organization's social media page.

The coefficient for "Total Followers" (Total_Followers_K) is 0.4087 with a standard error of 0.1664. The t-statistic is 2.46 with a p-value of 0.019, which is statistically significant at the 5% significance level. The 95% confidence interval for this coefficient ranges from 0.0721 to 0.7453.

In conclusion, the results provide evidence supporting Hypothesis 4, indicating that the "Total Followers" of performing art non-profit organizations affect the "Asset" variable. The relationship is statistically significant at the 5% level. These findings suggest that non-profit organizations may benefit from growing their social media presence to positively impact their total assets.

Hypothesis 5 (H5): “Average Interaction Counts” of Performing Art Nonprofit Organizations affect the “Total Followers” variable.

Hypothesis 5 investigates whether the "Average Interaction Counts" of performing art non-profit organizations affect the "Total Followers" variable. The regression results provide evidence of a significant relationship between these two variables.

The F-statistic is 49.49 with a p-value of 0.0000, which is statistically significant at the 1% significance level. This suggests that there is a strong relationship between "Average Interaction Counts" and "Total Followers."

The R-squared value is 0.5593, and the adjusted R-squared value is 0.5480, indicating that approximately 55.93% of the variance in the total followers can be explained by the average interaction counts on the non-profit organization's social media page.

The coefficient for "Average_Post_Interation_K" is 12.7327 with a standard error of 1.8099. The t-statistic is 7.03 with a p-value of 0.000, which is statistically significant at the 1% significance level. The 95% confidence interval for this coefficient ranges from 9.0717 to 16.3937.

In conclusion, the results provide strong evidence supporting Hypothesis 5, indicating that the "Average Interaction Counts" of performing art non-profit organizations affect the "Total Followers" variable. The relationship is statistically significant at the 1% level. These findings suggest that non-profit organizations may benefit from increasing engagement on their social media pages to grow their total number of followers.

Hypothesis 6 (H6): “Average Video Views” of Performing Art Nonprofit Organizations affect the “Total Followers” variable.

Hypothesis 6 examines whether the "Average Video Views" of performing art non-profit organizations affect the "Total Followers" variable. The regression results provide evidence of a significant relationship between these two variables.

The F-statistic is 41.66 with a p-value of 0.0000, which is statistically significant at the 1% significance level. This suggests that there is a strong relationship between "Average Video Views" and "Total Followers."

The R-squared value is 0.5165, and the adjusted R-squared value is 0.5041, indicating that approximately 51.65% of the variance in the total followers can be explained by the average video views on the non-profit organization's social media page.

The coefficient for "Average_Videoviews_K" is 1.7275 with a standard error of 0.2676. The t-statistic is 6.45 with a p-value of 0.000, which is statistically significant at the 1% significance level. The 95% confidence interval for this coefficient ranges from 1.1862 to 2.2688.

In conclusion, the results provide strong evidence supporting Hypothesis 6, indicating that the "Average Video Views" of performing art non-profit organizations affect the "Total Followers" variable. The relationship is statistically significant at the 1% level. These findings suggest that non-profit organizations may benefit from increasing the views of their videos on their social media pages to grow their total number of followers.

Hypothesis 7 (H7): “Total Interaction” of Performing Art Nonprofit Organizations affects the “Total Followers” variable.

Hypothesis 7 examines whether the "Total Interaction" of performing art non-profit organizations affects the "Total Followers" variable. The regression results provide evidence of a significant relationship between these two variables.

The F-statistic is 49.23 with a p-value of 0.0000, which is statistically significant at the 1% significance level. This suggests that there is a strong relationship between "Total Interaction" and "Total Followers."

The R-squared value is 0.5580, and the adjusted R-squared value is 0.5466, indicating that approximately 55.80% of the variance in the total followers can be explained by the total interaction on the non-profit organization's social media page.

The coefficient for "Total_Interaction_K" is 0.0052 with a standard error of 0.0007. The t-statistic is 7.02 with a p-value of 0.000, which is statistically significant at the 1% significance level. The 95% confidence interval for this coefficient ranges from 0.0037 to 0.0067.

In conclusion, the results provide strong evidence supporting Hypothesis 7, indicating that the "Total Interaction" of performing art non-profit organizations affects the "Total Followers" variable. The relationship is statistically significant at the 1% level. These findings suggest that non-profit organizations may benefit from increasing their total interactions on their social media pages to grow their total number of followers.

Hypothesis 8 (H8): “Total Posts Counts” of Performing Art Nonprofit Organizations affects the “Total Followers” variable.

Hypothesis 8 examines whether the "Total Posts Counts" of performing art non-profit organizations affects the "Total Followers" variable. The regression results provide evidence of a significant relationship between these two variables.

The F-statistic is 8.93 with a p-value of 0.0048, which is statistically significant at the 1% significance level. This suggests that there is a strong relationship between "Total Posts Counts" and "Total Followers."

The R-squared value is 0.1864, and the adjusted R-squared value is 0.1655, indicating that approximately 18.64% of the variance in the total followers can be explained by the total posts count of the non-profit organization's social media page.

The coefficient for "Total_Post_Number_K" is 74.39956 with a standard error of 24.89328. The t-statistic is 2.99 with a p-value of 0.005, which is statistically significant at the 1% significance level. The 95% confidence interval for this coefficient ranges from 24.04815 to 124.751.

In conclusion, the results provide evidence supporting Hypothesis 8, indicating that the "Total Posts Counts" of performing art non-profit organizations affects the "Total Followers" variable. The relationship is statistically significant at the 1% level. These findings suggest that non-profit organizations may benefit from increasing their total posts count on their social media pages to grow their total number of followers.

Hypothesis 9 (H9): “Total Followers” of Performing Art Nonprofit Organizations affects the “Average Monthly Website Traffic” variable.

Hypothesis 9 examines whether the "Total Followers" of performing art non-profit organizations affects the "Average Monthly Website Traffic" variable. The regression results provide some evidence of a relationship between these two variables, although it is not strong enough to be statistically significant at the conventional 5% level.

The F-statistic is 3.41 with a p-value of 0.0724, which is just above the 5% significance level. This suggests that there is some relationship between "Total Followers" and "Average Monthly Website Traffic," but it's not strong enough to be statistically significant at the 5% level.

The R-squared value is 0.0804, and the adjusted R-squared value is 0.0568, indicating that approximately 8.04% of the variance in average monthly website traffic can be explained by the total followers of the non-profit organization's social media page.

The coefficient for "Total_Followers_K" is 0.2204541 with a standard error of 0.1193858. The t-statistic is 1.85 with a p-value of 0.072, which is just above the 5% significance level. The 95% confidence interval for this coefficient ranges from -0.0210264 to 0.4619347.

In conclusion, the results provide some evidence supporting Hypothesis 9, indicating that the "Total Followers" of performing art non-profit organizations may affect the "Average Monthly Website Traffic" variable. However, the relationship is not statistically significant at the conventional 5% level. These findings suggest that non-profit organizations may see some benefits in increasing their total number of followers on their social media pages to increase their average monthly website traffic, but the impact is not strong enough to conclude with certainty.

Additional Test

Besides the main hypotheses H1-H9, additional tests were conducted to examine the relationship between 'Average Monthly Website Traffic' and other potential explanatory variables, including 'Total Interaction,' 'Total Post Counts,' 'Average Interaction,' and 'Average Video Views' for performing art non-profit organizations. The regression results for these tests were all positive, indicating a potential positive relationship between these independent variables and 'Average Monthly Website Traffic.' However, the Prob > F values for all these tests were higher than the conventional 0.05 threshold, implying that these relationships were not statistically significant.

These additional tests, along with the results from Hypothesis 9, suggest that while there might be some positive relationships between 'Average Monthly Website Traffic' and various social media engagement metrics, these relationships are not strong enough to be considered statistically significant at the 5% level. Consequently, further research might be required to identify other factors that have a more substantial impact on the 'Average Monthly Website Traffic' for performing art non-profit organizations.

Figure15. Scattered Points and Fitted Value Graph For H1 to H9

Findings

The study revealed significant positive correlations for Hypotheses H1 through H8, suggesting strong relationships between the respective variables. In summary, the findings indicate that:

1. A positive correlation exists between website traffic and financial revenue for non-profit organizations (H1). This suggests that higher website traffic can potentially lead to increased financial revenue for non-profit organizations.

2. A positive correlation exists between website traffic and total assets for non-profit organizations (H2). This indicates that increased website traffic is associated with larger asset holdings for these organizations.

3. A positive correlation exists between the number of social media followers on Instagram and total assets for non-profit organizations (H4). This indicates that organizations with larger Instagram followings tend to have larger asset holdings.

4. A positive correlation exists between social media average post interaction (measured by likes, comments, and shares) and the number of social media followers on Instagram for non-profit organizations (H5). This suggests that organizations with higher average post engagement rates tend to have larger Instagram followings.

5. A positive correlation exists between social media video post views and total followers (H6). This indicates that higher video post views are associated with a larger number of social media followers for non-profit organizations.

6. A positive correlation exists between social media total post interaction and total followers (H7). This suggests that higher total post engagement is linked to a larger number of social media followers for non-profit organizations.

7. A positive correlation exists between the amount of social media posts and total followers (H8). This indicates that organizations that post more frequently tend to have a larger number of social media followers.

However, Hypothesis H3, which postulated a positive correlation between the number of social media followers on Instagram and financial revenue for non-profit organizations, showed a positive correlation but could not be relied upon due to the low confidence level of the regression result. This suggests that the relationship between the number of social media followers on Instagram and financial revenue remains inconclusive and requires further research.

Additionally, Hypothesis H9, which postulated a positive correlation between the amount of social media interactions and website traffic, showed a positive correlation but could not be relied upon due to the low confidence level of the regression result. This suggests that the relationship between social media interactions and website traffic remains inconclusive and requires further research as well.

Figure 10. Correlation Analysis Result of Social Media Engagement, Followers, Website Traffic, and Organizational Performance

The study's findings highlight the importance of social media engagement for non-profit organizations. By understanding the relationships between social media metrics, website traffic, and financial outcomes, non-profit organizations can make more informed decisions about their social media strategies and potentially improve their financial performance and online visibility.

Limitations

The study has several limitations that should be acknowledged. First, the data collection is unaligned and limited in terms of media data and financial data. Access to website data on social media performance and website traffic is restricted to recent and current data that is open to the public. The available financial reports from organizations' Form 990 can only reflect the fiscal year of 2020 or 2021 due to the tax report time frame. The correlation between these factors and the growth of the company based on recent years of revenues are not aligned but are only based on the assumption of continuous organizations' attention and resources on social media reflected by the latest data. The social media platform's channels are also limited to a few and could be affected by the unalignment between the different organization's media focus, the channels' own audience demography, and the organizations' audience.

Second, this study only focuses on a few digital media channels the organizations use. Website traffic can be affected by many other social media channels. The Similarweb database shows that some websites have major traffic from multiple sources, such as Twitter, Reddit, and YouTube. These channels are not assessed in this research.

Lastly, the data focuses on limited industries to reflect the potential use for non-profit organizations. However, it does not include all sizes of organizations or all types of organizations. The sampling size is still relatively small compared to all non-profit organizations, and the location of the selections still needs scaled research for different areas for a result that can be widely applied.

Despite these limitations, the study represents a significant breakthrough in understanding the relationship between social media engagement, website traffic, and financial performance for non-profit organizations. The findings offer valuable insights and shed light on the potential benefits and impacts of investing in effective social media strategies for nonprofits across various industries. By emphasizing the importance of a strong online presence, the study encourages non-profit organizations to explore innovative and creative approaches to harness the power of social media platforms, and ultimately, enhance their financial performance and impact in their respective fields. This research serves as a stepping stone for further studies and investigations, potentially opening the door to a deeper understanding of the intricate relationship between digital media channels and non-profit success. The lessons learned from this study can be used as a foundation for non-profit organizations to build upon, as they adapt and evolve in the rapidly changing digital landscape.

Discussion

The positive correlations found in the study suggest that non-profit organizations can potentially benefit from investing in their social media presence. By adopting more effective social media strategies, non-profit organizations can improve their online visibility and potentially increase their financial performance. Based on the study's findings, the following practical recommendations can be made for non-profit organizations:

1. Focus on creating engaging content: With a strong positive correlation between social media engagement metrics (average post interaction, video post views, total post interaction) and the number of social media followers, non-profit organizations should prioritize creating content that resonates with their target audience. This may include sharing stories, images, videos, and other content that generates likes, comments, shares, and other forms of interaction.
2. Post frequently and consistently: The positive correlation between the number of social media posts and total followers suggests that non-profit organizations should maintain a consistent posting schedule to keep their followers engaged and attract new followers. By posting regularly, organizations can ensure their content remains visible and relevant to their audience.
3. Utilize video content: As the study found a positive correlation between video post views and the number of followers, non-profit organizations should consider incorporating more video content into their social media strategies. This could include creating short videos that showcase their work, share success stories, or provide educational content that aligns with their mission.
4. Invest in social media advertising: While the study did not specifically assess the impact of social media advertising on financial performance, the positive correlations found between social media metrics and financial outcomes suggest that non-profit organizations can benefit from investing in targeted advertising campaigns to increase their reach and attract new followers, donors, and supporters.
5. Monitor website traffic: With a positive correlation found between website traffic and both financial revenue and total assets, non-profit organizations should closely monitor their website traffic and work to improve their online presence. This may involve optimizing their website for search engines, enhancing their website's user experience, and linking their website to their social media profiles to drive more traffic.

By implementing these recommendations, non-profit organizations can harness the power of social media to improve their online visibility, increase engagement with their target audience, and potentially enhance their financial performance. However, further research is needed to fully understand the relationship between social media engagement and financial performance for non-profits, particularly considering the limitations of this study. As the digital landscape continues to evolve, it is crucial for non-profit organizations to stay up-to-date with the latest trends and best practices in social media marketing to remain competitive and effectively achieve their mission.

Future Research Directions

The findings of this study open up multiple avenues for future research. Some potential directions for further investigation include:

1. Addressing data alignment: Future research could focus on aligning data collection for both social media metrics and financial data to ensure a more accurate representation of the relationship between these factors and the growth of non-profit organizations.
2. Expanding the scope of the study: Future research could focus on a wider range of non-profit organizations, including those from different industries, geographic locations, and varying sizes. This would provide a more comprehensive understanding of the relationship between social media engagement and financial performance across the non-profit sector.
3. Assessing the impact of additional social media platforms: This study focused on a limited number of social media platforms. Future research should explore the impact of other popular platforms, such as Twitter, Reddit, and YouTube, on non-profit organizations' financial performance and online visibility.
4. Analyzing the effects of specific social media strategies: By examining the impact of specific social media strategies and tactics, future research could provide more actionable insights for non-profit organizations seeking to improve their online presence and financial performance.
5. Investigating the role of influencers and partnerships: Collaborations with influencers and other organizations can significantly impact a non-profit's social media presence. Future studies could explore the effects of these collaborations on both social media engagement and financial outcomes.
6. Exploring the impact of social media advertising: Although this study did not specifically assess the impact of social media advertising on financial performance, future research could explore this relationship, helping non-profit organizations make more informed decisions about their advertising budgets and strategies.
7. Longitudinal studies: Long-term studies tracking the social media engagement and financial performance of non-profit organizations over several years could provide valuable insights into the sustainability and long-term effects of social media efforts on financial outcomes.

By building on the findings of this study and addressing its limitations, future research can help non-profit organizations better understand and leverage the potential benefits of social media engagement. As the digital landscape continues to evolve, it is essential for non-profit organizations to stay informed and adapt their strategies to effectively reach their target audience, achieve their mission, and remain competitive in the digital age.

Acknowledgments

My sincere thanks go to Dr. Richard Maloney, NYU MPAA program director, for accepting me into the program and providing continuous encouragement and inspiration throughout my graduate study. I appreciate the guidance and expertise of my instructor, Dr. Ruby Yu, who generously offered advice and direction in the construction of this paper. I express my heartfelt gratitude to Yuri Yuxuan Wen from the Chinese University of Hong Kong for her invaluable insights and support in data analysis, which significantly contributed to this research.

Appendix

Table. Summary Statistics of Performing Art Nonprofit Organizations in New York City

Endnotes

1.  Dencheva, V. (2023a, January 6). Social media marketing penetration in the U.S. 2013-2022. Marketing Insights. Statista, https://www.statista.com/statistics/203513/usage-trands-of-social-media-platforms-in-marketing/

2.  Dencheva, V. (2023b, January 6). Usage of social media platforms for B2C content marketing in North America 2021.Statista, https://www.statista.com/statistics/331884/b2c-content-marketing-social-media-usage/

3.  Dencheva, V. (2023c, February 24). Social media types used by B2B marketers worldwide 2022. Statista, https://www.statista.com/statistics/245131/social-media-used-by-b2b-marketers-in-north-america/

4.  Kenton, W. (2022, December 22). What is nonprofit marketing? Definition, how it works, and types. Investopedia. https://www.investopedia.com/terms/n/nonprofit-marketing.asp

5.  Goswami, R. (2021, May 29). Social media marketing best practices for nonprofits. Statusbrew. https://statusbrew.com/insights/social-media-marketing-best-practices-for-nonprofits/

6. Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., Kumar, V., Rahman, M. M., Raman, R., Rauschnabel, P. A., Rowley, J., Salo, J., Tran, G. A., & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. https://doi.org/10.1016/j.ijinfomgt.2020.102168

7.  Murdough, C. (2009). Social media measurement: It’s not impossible. Journal of Interactive Advertising, 10, 94-99. https://doi.org/10.1080/15252019.2009.10722165

8.  Dublino, J. (2023, October 31). 5 Marketing challenges only nonprofits understand. Business.com.https://www.business.com/articles/4-marketing-challenges-only-non-profits-understand/

9.  Scaife, W. (2011). The Networked Nonprofit: Connecting with social media to drive change, by B. Kanter & A. H. Fine. Journal of Nonprofit & Public Sector Marketing, 23, 209-211. https://doi.org/10.1080/10495142.2011.572720

10.  Igarová, K., Kádeková, Z., & Košičiarová, I. (2022). A miracle of nowadays affecting consumers’ behaviour: The outstanding influence of social media. Communication Today, 13(2).

11.  Li, F., Larimo, J., & Leonidou, L. C. (2021). Social media marketing strategy: Definition, conceptualization, taxonomy, validation, and future agenda. Journal of the Academy of Marketing Science, 49, 51–70.

12.  Harmeling, C. M., Moffett, J. W., Arnold, M. J., & Carlson, B. D. (2017). Toward a theory of customer engagement marketing. Journal of the Academy of Marketing Science, 45(3), 312–335.

13.  Vivek, S. D., Beatty, S. E., & Morgan, R. M. (2012). Customer engagement: Exploring customer relationships beyond purchase. Journal of Marketing Theory and Practice, 20(2), 127–145.

14.  Valos, M. J., Maplestone, V. L., Polonsky, M. J., & Ewing, M. (2017). Integrating social media within an integrated marketing communication decision-making framework. Journal of Marketing Management, 33(17-18), 1522–1558.

15.  Malthouse, E. C., Calder, B., Kim, S. J., & Vandenbosch, M. (2016). Evidence that user-generated content that produces engagement increases purchase behaviors. Journal of Marketing Management, 32(5-6), 427-444. https://doi.org/10.1080/0267257X.2016.1148066

16.  Schultz, D., & Peltier, J. (2013). Social media's slippery slope: Challenges, opportunities and future research directions. Journal of Research in Interactive Marketing, 7, 86-99. https://doi.org/10.1108/JRIM-12-2012-0054

17.  Vivek, S. D., Beatty, S. E., & Morgan, R. M. (2012). Customer engagement: Exploring customer relationships beyond purchase. Journal of Marketing Theory and Practice, 20, 122-146. https://doi.org/10.2753/MTP1069-6679200201

18.   Sakas, D. P., Reklitis, D. P., Terzi, M. C., & Vassilakis, C. (2022). Multichannel digital marketing optimizations through big data analytics in the tourism and hospitality industry. Journal of Theoretical and Applied Electronic Commerce Research, 17, 1383–1408.

19.  Kanter, B., & Fine, A. (2010). The networked nonprofit: Connecting with social media to drive change. John Wiley & Sons.

20.  Gordon, A. (2017). Social media marketing strategies in nonprofit professional membership organizations (Publication No. 4520). [Walden University Dissertations and Doctoral Studies]. https://scholarworks.waldenu.edu/dissertations/4520

21.  Makgosa, R., Botha-Ravyse, C., & Van der Merwe, A. (2019). An integrated social media communication view on content marketing by South African non-profit sectors. South African Journal of Information Management, 21(1), a1007. https://doi.org/10.4102/sajim.v21i1.1007

22.  Tweneboah-Koduah, E. Y., & Coffie, I. S. (2022). Influencing behavior change through corporate social marketing: Evidence from Ghana. Journal of Nonprofit & Public Sector Marketing. https://doi.org/10.1080/10495142.2022.2133064

23.  Suh, J., & Hoang, T. (2021). Nonprofit external communications: General management, public relations, or fundraising tool. Journal of Public and Nonprofit Affairs, 7(2).

24.  Hackler, D. & Saxton, G. (2007). The strategic use of information technology by nonprofit organizations: Increasing capacity and untapped potential. Public Administration Review, 67, 474–487.

25.  Levine, H., & Zahradnik, A. G. (2012). Online media, market orientation, and financial performance in nonprofits. Journal of Nonprofit & Public Sector Marketing, 24(1), 26-42. https://doi.org/10.1080/10495142.2012.652908

26.  Duong, H. T. (2017). Fourth generation NGOs: Communication strategies in social campaigning and resource mobilization. Journal of Nonprofit & Public Sector Marketing, 29(2), 119-147. https://doi.org/10.1080/10495142.2017.1293583

27.  Li, Y., & Voida, A. (2022). Nonprofit organizations’ dialogic use of social media: Principles and practice. Journal of Nonprofit & Public Sector Marketing. https://doi.org/10.1080/10495142.2022.2133059

28.  Mehrotra, A., & Siraj, S. (2021). Social media marketing - An effective solution for non-profit organizations. In 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence). https://doi.org/10.1109/Confluence51648.2021.9377089

29.  Yue, C. A., Men, L. R., & Hart, E. B. (2022). “Chief engagement officers?” A comparative study between U.S. corporate and nonprofit executive leaders' social media communication strategies. Nonprofit Management and Leadership. https://doi.org/10.1002/nml.21551

30.  Park, J., Chung, T.-L. (D.), Hall-Phillips, A., & Anaza, N. A. (2016). Loyalty to social ventures in social media: The role of social cause involvement, identification, and commitment. Journal of Nonprofit & Public Sector Marketing, 28(3), 185-208. https://doi.org/10.1080/10495142.2015.1015378

31.  CFA Society New York. (2023, March 29). How alternative data is changing the research process [Video file: Part 1]. Retrieved from https://www.cfany.org

32. CFA Society New York. (2023, March 29). How alternative data is changing the research process [Video file: Part 2]. Retrieved from https://www.cfany.org