Social Media’s Impact on Gen-Z University Enrolment, A case of a Zimbabwean University

Social Media’s Impact on Gen-Z University Enrolment, A case of a Zimbabwean University 

Naume Katiyo, Jamba Fabiano & Wonderful Dzimiri

Information and Marketing Sciences, Midlands State University, Gweru, Midlands, Zimbabwe

DOI: https://dx.doi.org/10.47772/IJRISS.2025.903SEDU0587

Received: 22 September 2025; Accepted: 28 September 2025; Published: 29 October 2025

ABSTRACT

Social media has become a central tool in higher education recruitment, especially among Generation Z students who rely heavily on digital platforms to make educational decisions. However, the actual influence of social media marketing on enrolment outcomes remains unclear for many universities in Africa, including those in Zimbabwe. This study explores how different social media strategies shape enrolment decisions at a Zimbabwean state university, focusing on platform effectiveness, content preferences, and student engagement patterns. Using a mixed-methods approach that combined surveys (n = 88), interviews with staff, content analysis, and digital analytics, the research applied TAM, SMET and CDJ to examine these dynamics. Findings show that Instagram is the most effective platform for predicting enrolment (β = 0.75, p < 0.01), while TikTok, though underused by the university, recorded the highest student engagement rate (92%). Compared with institutional posts, student-generated content proved to be the most influential, achieving nearly four times the return on investment. Sustained interaction with university content over a two-month period increased the likelihood of enrolment by 65%, and perceived usefulness of content (β = 0.72) was found to be more important than ease of use in influencing decisions. Peaks in online engagement also coincided with admissions periods, with 45% increase in click-through rates. These results highlight the need for Zimbabwean universities to adopt student-centred strategies and to prioritise visual and interactive content. The study recommends reallocating at least 35% of marketing budgets to video-based platforms, particularly TikTok and Instagram, and investing in campaigns that feature authentic student voices. Beyond offering practical strategies, the study theoretically contributes by extending TAM, SMET and CDJ into a non-Western, resource-limited context. Overall, the findings provide a framework for African universities to refine digital recruitment practices, maximise return on investment, and better align with the expectations of a digitally native generation.

Keywords: Social Media Marketing, Generation Z, Enrolment Conversion, Higher Education, Zimbabwe

INTRODUCTION

The way universities communicate with potential students has changed dramatically in the past two decades. Traditional recruitment methods, such as printed brochures, radio announcements, and school visits, are now complemented, and in some cases replaced by digital platforms. At the centre of this transformation is social media marketing, which has become an essential strategy for higher education institutions seeking to reach a younger, tech-savvy audience. This shift is particularly important when engaging Generation Z, a cohort born between 1997 and 2012, who have grown up in a fully digital world. Unlike previous generations, Gen Z students are not only comfortable using social media but also rely on it as a key source of information, spending more than four hours a day on platforms such as Instagram, TikTok, and Facebook (Rajulapati, 2023). For these students, social media is not just entertainment; it is also a space where they form opinions, seek peer validation, and make major life decisions, including choosing where to study.

The role of social media in higher education marketing has been widely acknowledged globally. Studies have shown that 92% of universities use social media to promote their institutions and connect with students (Xu, 2023). Visual platforms such as Instagram are often praised for their ability to showcase campus life, while TikTok has emerged as a powerful tool for reaching students with short, engaging, and authentic video content (Jacob & Agarwal, 2024; Davidson & Lee, 2023). However, these findings are mostly drawn from developed countries with strong digital infrastructure and large marketing budgets. In such contexts, universities can invest in data analytics, track student behaviour in detail, and design sophisticated recruitment campaigns. The situation is different in developing countries, particularly in Africa, where it is more difficult to measure the effectiveness of social media marketing or to adapt strategies in real time due to limited resources and infrastructural challenges.

Zimbabwe offers a striking example of this gap. Mobile internet penetration among urban youth is estimated at over 93% (Zimbabwe Statistics Agency, 2023), suggesting that social media should be a highly effective recruitment channel for universities. Institutions such as Midlands State University (MSU) have indeed turned to Facebook, Instagram, and other platforms to promote themselves. However, the effectiveness of these efforts remains uncertain. Many universities continue to rely on superficial measures of success, such as likes, shares, and follower counts, that do not necessarily translate into enrolment (ElSayad, 2024). Even more concerning is the fact that certain high-potential platforms, particularly TikTok, despite their enormous popularity among students. For instance, while 92% of Zimbabwean students report engaging with TikTok content, universities have yet to make the platform a central part of their recruitment strategies. This gap between student behaviour and institutional practice reflects a broader challenge: the lack of localised research and evidence to guide digital marketing strategies in African higher education.

Theoretical frameworks offer useful tools for understanding these dynamics but have been applied mainly in Western contexts. The TAM, for example, highlights perceived usefulness and ease of use as key determinants of technology adoption (Davis, 1989). SMET builds on this by considering cognitive, emotional, and behavioural forms of engagement (Wang et al., 2024). While valuable, these frameworks assume stable digital access and relatively homogeneous user experiences, conditions that do not always apply in low-resource settings such as Zimbabwe. In fact, preliminary findings suggest that for Zimbabwean students, the perceived usefulness of content—such as whether it provides real insight into campus life or career opportunities—is more important than its technical ease of use. Similarly, engagement patterns are shaped not only by personal preferences but also by socio-cultural factors, such as the role of family in decision-making and affordable mobile data accessibility.

It is within this context that the current study seeks to investigate the relationship between social media marketing and enrolment decisions among Generation Z students at a Zimbabwean state university. This study builds on global theories such as TAM and SMET but adapts them to a local context by considering cultural influences, infrastructural constraints, and the realities of digital engagement in Zimbabwe. Specifically, it examines how different platforms contribute to student recruitment, which types of content generate the strongest engagement, and how patterns of interaction influence the likelihood of enrolment over time. The study offers a multi-layered understanding of the issue by combining surveys, staff interviews, digital analytics, and content analysis.

The significance of this research is both practical and theoretical. Practically, it provides Zimbabwean universities with evidence-based recommendations for more effective allocation of scarce marketing resources. For example, the study shows that reallocating budgets towards video content and student-generated material on platforms such as Instagram and TikTok can significantly improve outcomes. Theoretically, the research extends TAM and SMET into a non-Western, resource-limited environment, highlighting new insights into how perceived usefulness and authenticity shape student decisions in such contexts.

This study addresses an urgent need, because, competition for students intensifies both locally and globally, Zimbabwean universities cannot afford to rely on trial-and-error recruitment approaches. Instead, they require data-driven strategies that reflect the realities of their students and the environment in which they operate. By bridging the gap between global theory and local practice, this research contributes to a better understanding of how social media marketing can be used as a strategic driver of enrolment in Zimbabwean higher education.

RESEARCH QUESTIONS

1. How do social media engagement metrics relate to enrolment decisions at Midlands State University?
2. Which social media platforms are most effective in converting prospects into enrolled students?
3. What types of content are most effective in engaging students to encouraging enrolment?

LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK

While the potential of social media is widely celebrated, it is also critical to consider its potential drawbacks in a recruitment context. The very authenticity sought by Gen Z can be manipulated, leading to misinformation or an overly curated portrayal of campus life (Kaplan & Haenlein, 2010). Furthermore, engagement on these platforms can exacerbate peer pressure and create digital divides, where students without reliable internet access or modern devices are excluded from these digital recruitment conversations (Chaterera-Zambuko et al., 2022). These factors represent a critical area for institutional awareness.

Global and African Perspectives

Research in the Western context highlights the effectiveness of platform-specific strategies. Instagram is praised for its ability to visually showcase campus life (Jacob & Agarwal, 2024), while TikTok has proven to be powerful in creating viral, student-driven narratives (Davidson & Lee, 2023). When paired with targeted analytics, these strategies often lead to measurable increases in student applications and enrolments (Kumar et al., 2023). In contrast, African universities frequently struggle to translate social media engagement into actual enrolment outcomes. In Zimbabwe, mobile internet penetration among urban youth exceeds 93% (Zimbabwe Statistics Agency, 2023), suggesting a strong potential for digital recruitment. Yet studies show that institutions such as Midlands State University often rely on superficial metrics like likes and shares, which provide little insight into actual conversion (Moyo & Ndlovu, 2023). Despite having a 92% engagement rate among Zimbabwean students, TikTok remains largely neglected in institutional strategies, reflecting a disconnect between global trends and local practices.

Similar challenges have been reported in other African countries. For example, Nigerian universities have adopted Facebook campaigns, but without data-driven methods, these efforts often fail to influence enrolment behaviour (Akinmoyeje et al., 2023). In South Africa, while universities recognise the value of digital marketing, socio-economic inequalities, and uneven internet access limit the reach of campaigns (Chaterera-Zambuko et al., 2022). These examples show that African institutions must adapt global strategies to local realities to maximise the potential of social media marketing.

THEORETICAL FOUNDATIONS

This study is framed by three theoretical perspectives: the TAM, SMET, and CDJ.

TAM (Davis, 1989) explains that technology adoption is based on two factors: perceived usefulness (PU) and perceived ease of use (PEOU). In higher education marketing, PU refers to how helpful students find social media content for decision-making, while PEOU reflects how easy it is to interact with the platform. Studies in African contexts suggest that PU is the stronger predictor: students value content that is practical and relevant even when platforms are less user-friendly (Watat & Bonaretti, 2022). SMET expands the analysis by focusing on engagement across three dimensions: cognitive (learning from content), emotional (developing feelings of trust or excitement), and behavioural (visible actions like sharing or commenting) (Henderson & Powell, 2021). In higher education, more effectively than formal institutional messages, authentic, student-generated content tends to foster all three forms of engagement. CDJ adds a process-oriented perspective, showing how prospective students move through stages of awareness, evaluation, and conversion. Decisions are shaped not by single exposures but by sustained engagement across time and platforms, especially during critical admission periods (Kumar et al., 2023).

Integrated conceptual framework.

Bringing these perspectives together, this study develops an integrated framework for understanding the role of social media marketing in higher education in Zimbabwe. The framework assumes that:

• TAM is the key driver of deeper engagement, especially in contexts where resources are constrained.
• SMET occurs cognitively, emotionally, and behaviourally, and its intensity depends on both the platform and the type of content.
• Sustained interactions (CDJ) during critical decision-making stages increase the likelihood that students will convert from prospective applicants to actual enrolees.

Other concepts are built on this foundation. Platform-specific effectiveness matters because different platforms Instagram for visuals, TikTok for viral interaction, and Facebook for broad reach attract various levels of attention. Content type is crucial, with student-generated and video-based content being the most persuasive. Temporal factors also play a role, as engagement peaks during admissions periods and consistent interaction over time significantly raises the probability of conversion.

Contribution of the Framework

This integrated conceptual framework addresses gaps in existing literature in two main ways. First, it adapts global theories to an African setting, where infrastructural limitations and cultural dynamics alter how students interact with digital platforms. For example, while Western studies highlight ease of use, this study finds that Zimbabwean students prioritise the usefulness and authenticity of content. Second, the framework combines engagement theory with decision-making models, illustrating how both engagement quality and exposure timing influence enrolment outcomes.

The framework positions social media marketing as a process of cumulative interaction rather than a set of isolated campaigns. Effective recruitment depends on producing useful, authentic, and emotionally resonant content, delivering it through the right platforms, and sustaining engagement over time. This perspective provides Zimbabwean universities with practical strategies for maximising scarce resources while also contributing theoretically by extending TAM, SMET, and CDJ into a non-Western, resource-limited context. To further ground this study in communication theory, the Two-Step Flow model is incorporated. This theory posits that ideas often flow from mass media to opinion leaders and then to the wider population (Katz & Lazarsfeld, 1955). In this context, student creators on platforms like TikTok and Instagram act as these opinion leaders, making their content more influential than direct institutional messaging. This complements the CDJ model from marketing by explaining why peer content is so powerful at the evaluation stage of the student choice process.

Conceptual Framework for social media Marketing and Enrolment conversion

Figure 1 Conceptual Framework for social media Marketing and Enrolment Conversion Source: Author Generated (2024)

Gaps in Existing Research

While the global literature provides valuable insights, it leaves important gaps when applied to Zimbabwe and other African contexts. Most existing studies are centred on Western markets, where digital infrastructure is more advanced and student preferences may differ from those in developing economies (Jacob & Agarwal, 2024). Research on social media marketing in higher education in Zimbabwe is limited and often focuses on general institutional challenges rather than direct student perspectives (Moyo & Ndlovu, 2023). Furthermore, studies rarely integrate multiple theoretical frameworks, leaving unexplored the interactions between perceived usefulness, forms of engagement, and the timing of decision-making unexplored. Another gap lies in the lack of robust ROI measurement strategies suited for low-resource contexts. While institutions in developed countries use advanced analytics to track conversions, universities in Zimbabwe often lack the financial and technical capacity to do the same (ElSayad, 2024). This leads to a reliance on superficial metrics that do not accurately reflect the marketing impact.

Towards a Context-Specific Approach

Addressing these gaps requires empirical research and adaptation of existing theories to local realities. For Zimbabwean universities, this means acknowledging that Generation Z students are active online but also face unique socioeconomic and infrastructural conditions that shape their behaviour. It also means recognising that strategies effective in Western contexts cannot simply be transplanted. Instead, universities must adopt contextually grounded frameworks that highlight the platforms, content types, and engagement patterns that are most relevant to their audiences.

By synthesising TAM, SMET, and CDJ within the Zimbabwean higher education environment, this study develops a conceptual framework that links global theory with local practice. This study demonstrates how the perceived usefulness of content drives deeper engagement, how authentic and student-generated content sparks stronger responses, and how timing and sustained interaction across platforms influence final enrolment decisions.

METHODOLOGY

Research Design

This study adopted an explanatory sequential mixed-methods design which allowed for triangulation of data, strengthening the reliability and depth of the findings by combining objective behavioural metrics with subjective human perspectives. These approaches provide a comprehensive understanding of how social media marketing influences enrolment conversion rates among Generation Z students at a state university in Zimbabwe. The process was guided by a pragmatic paradigm, allowing the integration of objective measures such as engagement metrics with subjective insights from students and staff. A single-case study design was chosen to capture the unique socio-digital context of the institution under investigation. This design made it possible to focus in depth on the dynamics of one university, which is particularly valuable given the under-researched higher education environment in Zimbabwe.

DATA COLLECTION

Quantitative Phase

A structured online questionnaire was administered to eighty-eight enrolled Generation Z students aged between 18 and 24 years. Stratified random sampling was used to ensure representation across academic programmes and demographic groups. The instrument drew on constructs from the Technology Acceptance Model (TAM) and Social Media Engagement Theory (SMET), focusing on perceived usefulness (PU), perceived ease of use (PEOU), and cognitive, emotional, and behavioural engagement. Pilot testing with fifteen students confirmed clarity, and reliability was established with Cronbach’s alpha of 0.87.

Qualitative Phase

The qualitative phase involved semi-structured interviews with ten marketing staff members, providing vital institutional data and strategic insights.  While the inclusion of student focus groups could have further illuminated peer-influence dynamics, the chosen methods of staff interviews and content analysis effectively captured the institutional strategies and their alignment (or misalignment) with student engagement metrics. In addition, a content analysis was conducted on 450 social media posts published between 2022 and 2024 across Facebook, Instagram, TikTok, and LinkedIn. This analysis assessed platform-specific effectiveness and triangulated the findings from the student survey.

Digital Analytics

To complement the surveys and interviews, digital analytics data were collected from Meta Business Suite, TikTok Analytics, and Google Analytics. These data provided platform-specific metrics such as likes, shares, and click-through rates, which were used to establish links between engagement and enrolment outcomes.

Sampling Strategy

The student sample size (n = 88) was determined using the formula of Krejcie and Morgan (1970) at a 95% confidence level with a ±10% margin of error, adjusted to reflect financial and accessibility constraints. Stratification by faculty and year of study the study’s demographic diversity. Purposive sampling was used for the interviews, and the principle of saturation guided the number of participants, ensuring that data collection continued until no new themes emerged.

Data Analysis

Quantitative Analysis

The survey data were analysed using SPSS version 23 (IBM Corp., Armonk, NY, USA), applying descriptive statistics to summarise responses and inferential statistics to test relationships. Pearson’s correlations and multiple regression analyses were employed to identify enrolment predictors. The key variables included PU, PEOU, and platform engagement scores.

Qualitative Analysis

Interview transcripts and social media content were analysed thematically using NVivo 12. Codes were generated inductively, with categories such as “authenticity” and “platform preferences” emerging from the data. These were then mapped onto the TAM and SMET frameworks. Triangulation with quantitative findings enhanced the results’ reliability.

Validity and Reliability

To reduce self-reporting bias, behavioural engagement metrics from digital analytics were compared with survey responses. Member checking and peer debriefing were conducted to ensure the accuracy of the qualitative interpretations. Content validity was enhanced through expert review of instruments, while test–retest reliability (r = 0.82) confirmed the survey’s stability.

Ethical Considerations

Ethical clearance for the study was approved by the university’s research ethics review board. Participation was voluntary, with informed consent was obtained from all respondents. Anonymity was maintained through data anonymization, and participants were assured that their contributions would remain confidential.

Reproducibility

All survey instruments, interview protocols, and datasets are archived in the repository of the university. Analytical workflows, including regression models and thematic coding frameworks, are documented to allow study replication.

RESULTS

This section presents the findings of the study, which explored the relationship between social media marketing strategies and enrolment conversion rates among Generation Z students at a state university in Zimbabwe. Data were gathered through surveys, interviews, digital analytics, and content analysis, and are presented under five major themes: platform-specific effectiveness, content strategies, temporal engagement, sentiment and perceived value, and cross-platform validation.

Platform-specific effectiveness

The analysis revealed distinct effectiveness patterns across different platforms. Instagram emerged as the strongest predictor of enrolment conversions (β = 0.75, p < .01), confirming its dominance in visual storytelling and student appeal. Although underutilised by the university, TikTok demonstrated the highest engagement rate at 92%, suggesting significant untapped potential for recruitment. In contrast, Facebook maintained widespread adoption (72% usage) but showed declining effectiveness among younger demographics, reflecting shifting platform preferences within Generation Z. A regression model that included platform usage, content type, and engagement metrics accounted for 68.4% of the variance in enrolment outcomes (Adjusted R² = 0.684, p < .001). Within this model, social engagement metrics such as likes, shares, and comments were the strongest predictor (β = 0.42, p < .001), followed closely by platform-specific usage patterns (β = 0.38, p < .001).

Figure 2: Regression coefficients of the predictors

Source: Author Generated (2024)

The Impact of Content Strategies

Content type was found to play a crucial role in shaping student responses. Student-generated content outperformed institutional content, achieving 92% engagement and a four times higher return on investment (ROI) than official university posts. Video content was particularly influential, producing three times greater engagement levels than static posts (t = 5.21, p < .001).

Among the distinct categories, campus life posts—such as virtual tours and event highlights—were strongly correlated with enrolment intent (r = 0.65, p < .01). In contrast, academic posts, though central to the university’s strategy, generated lower levels of engagement (65%).

Figure 3: Effectiveness of Content Type

Source: Author Generated (2024)

Temporal Engagement Patterns

Engagement levels varied across the academic calendar. Activity peaked during admissions (January–March) and dropped significantly during holiday breaks (December). Sustained engagement across at least two months was found to increase the probability of enrolment conversion by 65% (OR = 1.65, 95% CI [1.2, 2.1]). This finding highlights the importance of consistent, long-term engagement rather than short, episodic campaigns.

Figure 4: Trends in engagement and enrolment over time

Source: Author Generated (2024)

Sentiment analysis revealed positive perceptions of the university’s social media presence, with 65% of respondents expressing favourable opinions. Platform-specific differences were observed: TikTok had the highest approval rating at 80%, due to authentic student-driven narratives, while LinkedIn (55%) and Twitter (45%) trailed behind. In terms of predictive factors, PU of social media content was the strongest determinant of enrolment decisions (β = 0.72, p < .001). This exceeded the impact of perceived ease of use (PEOU; β = 0.58, p < .001), highlighting the importance of content relevance over technical simplicity.

Figure 5: Platform -specific sentiment analysis

Source: Author Generated (2024)

Figure 6: Correlation between PU and engagement rate

Source: Author Generated (2024)

Cross-Platform Validation

Finally, triangulation of surveys, interviews, and analytics revealed significant gaps between staff perceptions and student behaviours. Staff tended to overestimate LinkedIn’s influence (70% perceived impact vs. 55% actual engagement) while underestimating TikTok’s potential (65% perceived vs. 88% actual). These discrepancies suggest the need for more data-driven allocation of resources and greater alignment between institutional strategies and student preferences.

Figure 7: Platform Performance Metrics

Source: Author Generated (2024)

Figure 8: Correlation Coefficients with enrolment decisions

Source: Author Generated (2024)

Correlation coefficients between engagement metrics and enrolment decisions. PU showed the strongest association (r = 0.72, p < .01).

Figure 9: Regression coefficients of the predictors

Source: Author Generated (2024)

Regression coefficients of predictors in the EC model. Social engagement (β = 0.42) and platform usage (β = 0.38) were significant contributors.

Figure 10: Effectiveness of Content Type

Source: Author Generated (2024)

Effectiveness of content type. Student-generated content (92%) and videos outperformed static posts.

Figure 11: Platform -specific sentiment analysis

Source: Author Generated (2024)

SUMMARY OF THE FINDINGS

The results demonstrate that social media marketing significantly shapes enrolment outcomes among Zimbabwean students. Instagram was the most effective platform for predicting enrolment, while TikTok represented the greatest underutilised opportunity. Student-generated content and video posts emerged as the most powerful engagement drivers, while temporal analysis highlighted the importance of sustained interaction during admissions cycles. Perceived usefulness is the strongest predictor of decision-making, surpassing ease of use. Finally, the discrepancies between staff assumptions and student behaviours highlight the need for evidence-based strategies in digital recruitment.

Key Findings Interpretation

The results clearly show that among the platforms studied, Instagram is the strongest predictor of enrolment, consistent with international evidence that visual platforms play a key role in shaping Gen Z decisions (Jacob & Agarwal, 2024). At the same time, TikTok achieved the highest engagement rate (92%) but remains underutilised in institutional strategies. This mismatch suggests that while students are already heavily engaging with short-form video content, universities are slow to adopt emerging platforms. Although widely used, Facebook showed declining effectiveness among younger users, reflecting broader shifts in platform preferences.

In terms of content, student-generated material and videos outperformed official static posts. These formats not only achieved higher engagement but also created stronger connections between prospective students and the institution. Campus life content correlated strongly with enrolment intent, highlighting the importance of authenticity and relatability. This aligns with prior studies that emphasise peer influence and authenticity as critical drivers of Gen Z engagement (Foster & Richards, 2020). Conversely, academic-focused posts, though central to institutional branding, generated lower levels of interaction, suggesting that purely informational content is less persuasive without accompanying narratives or visuals.

This study also confirms the importance of sustained engagement over time. Students who consistently interacted with university content for at least two months were significantly more likely to convert into enrolees. Peaks in engagement during admissions periods underline the role of timing in recruitment campaigns, echoing the CDJ framework, which emphasises ongoing exposure during critical decision-making windows (Kumar et al., 2023).

Sentiment analysis further demonstrated that PU was the strongest predictor of enrolment decisions (β = 0.72), outweighing perceived ease of use (β = 0.58). This supports the Technology Acceptance Model (TAM) but also extends it by showing that in resource-constrained contexts, the relevance and utility of content matter more than interface simplicity. Authenticity, relevance, and perceived value are therefore central to decision-making, a finding also reinforced by SMET, which highlights the interplay of cognitive, emotional, and behavioural engagement. Finally, the study uncovered a disconnect between staff perceptions and student behaviour. University staff overestimated LinkedIn’s role in recruitment while underestimating the potential of TikTok. This misalignment reflects a reliance on traditional assumptions rather than data-driven insights and suggests a need for continuous platform and content strategy evaluation.

Comparison with existing literature

The findings of this study are consistent with global studies that highlight Instagram’s dominance and TikTok’s viral potential in higher education marketing (Davidson & Lee, 2023; Thompson & Garcia, 2024). However, they diverge from Western contexts in two key respects. First, the stronger role of perceived usefulness over ease of use suggests that students in Zimbabwe prioritise content relevance in ways that differ from those in environments with more reliable infrastructure. Second, the underutilisation of TikTok in Zimbabwe contrasts sharply with its growing prominence in Western university campaigns, revealing a gap between global trends and local implementation.

This study also builds on African research. Moyo and Ndlovu (2023) noted that Zimbabwean universities often rely on superficial engagement metrics, and the current findings confirm this limitation. By triangulating analytics with student and staff perspectives, this study adds depth to the understanding of why institutional strategies may fail to convert interest into actual enrolment.

THEORETICAL AND PRACTICAL IMPLICATIONS

Theoretically, the findings extend TAM, SMET, and CDJ into a non-Western, resource-limited context. They demonstrate that while these frameworks hold explanatory power, their emphasis requires adjustment. TAM’s focus on ease of use is less relevant than usefulness in Zimbabwe’s higher education context. SMET’s three forms of engagement are validated, with student-generated and video content particularly effective in stimulating cognitive, emotional, and behavioural responses. The finding that sustained, timed exposure during admissions cycles increases conversion probability reinforces CDJ. Practically, the study highlights several actionable strategies. Universities should reallocate at least 35% of their marketing budgets to video content, particularly student-driven and authentic material. TikTok and Instagram should be prioritised as key platforms for reaching Gen Z, while resources devoted to declining platforms such as Facebook and LinkedIn should be reconsidered. Staff training in digital analytics and data-driven decision-making is also essential to close the gap between institutional assumptions and student behaviour. Practically, while investing in platforms like TikTok and Instagram, universities must also be mindful of the potential for misinformation and the digital divide. Strategies should include verifying student-generated content and ensuring key recruitment information is also accessible through low-bandwidth or non-social media channels.

LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH

The study’s findings must be viewed considering certain limitations. First, the cross-sectional design limited the ability to capture long-term changes in engagement behaviour. Second, the research focused on a single state university in an urban setting. While this allowed for an in-depth case study, it limits the generalisability of the findings. Future research should expand to multiple institutions, including rural and private universities, to enable a comparative analysis and enhance the broader applicability of the results across Zimbabwe’s diverse higher education landscape.. Third, financial constraints limited the scope of platform analysis, excluding emerging tools such as WhatsApp.

Therefore, future research should adopt longitudinal designs to explore how engagement evolves over time. Expanding studies to multiple institutions, including rural and private universities, would also strengthen the generalisability of the findings. In addition, future work should explore the role of emerging technologies such as artificial intelligence in optimising social media marketing strategies for higher education.

CONCLUSION

Overall, the discussion highlights that social media marketing plays a decisive role in enrolment conversion among Zimbabwean students, institutional strategies remain misaligned with student preferences. Universities can significantly improve recruitment outcomes by prioritising authentic, useful, and student-driven content, reallocating resources towards high-impact platforms and grounding strategies in empirical evidence. The findings reinforce the relevance of global theoretical models while adapting them to a Zimbabwean context, offering both practical guidance for institutions and valuable contributions to the broader literature on social media marketing in higher education.

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