Social Media Reporting: How to Do It Right for Strategic Decision Making

Abstract

As social media became essential for communication, organizations collected vast data from platforms like Facebook, Twitter (X), Instagram, and LinkedIn. However, turning this data into actionable insights for strategic decision-making was often inconsistent. This study explored ways to enhance social media reporting to improve strategic outcomes. Through literature review and expert interviews, it identified challenges such as misaligned metrics, low data literacy, siloed departments, and limited integration of insights into planning. Despite investments in dashboards and analytics tools, these resources were often underused due to interpretive gaps and a focus on vanity metrics. The findings highlighted the importance of aligning social media KPIs with organizational goals, fostering cross-functional collaboration, and enhancing interpretive capabilities among staff and executives. Importantly, the study also underscored the broader public value of effective social media reporting, particularly in the public sector, where data-driven communication enhanced transparency, responsiveness, and citizen trust. This research contributed to the growing discourse on data-driven strategy by emphasizing not only the technical and analytical dimensions, but also the often-overlooked human, organizational, and public value factors that influenced the real-world effectiveness of social media reporting.

1. Introduction

The proliferation of digital technologies transformed how organizations interacted with stakeholders, making social media a core channel for communication, branding, and data generation (Kaplan & Haenlein, 2020). As billions of users engaged on platforms like Facebook, Instagram, LinkedIn, and X (formerly Twitter), they generated a vast stream of data that, when properly analyzed, served as a critical input for strategic decision-making (Zeng et al., 2023; Saini et al., 2023). This data-rich environment necessitated systematic and accurate social media reporting to convert digital engagement into meaningful business insight.

Social media reporting referred to the structured process of collecting, analyzing, and interpreting performance data to evaluate the impact of social media strategies and campaigns (Chaffey & Ellis-Chadwick, 2019; Hootsuite, 2023). When done effectively, it allowed businesses to identify patterns, assess audience behavior, and make evidence-based decisions that supported larger organizational goals (Mehr et al., 2025; Hanlon & Tuten, 2022).

Numerous studies emphasized the role of data-driven social media strategies in enhancing firm performance. For instance, Malthouse et al. (2024) found that integrating social media data into marketing dashboards improved agility and responsiveness to consumer feedback. Similarly, Zhang et al. (2018) showed that firms leveraging real-time metrics from social platforms experienced stronger equity value due to better market adaptability. Furthermore, Banerjee and Chua (2023) concluded that the analysis of online engagement and user-generated content helped firms better anticipate crises and adjust communication in dynamic contexts.

In the digital age, social media evolved from a communication tool into a strategic business asset, influencing consumer behavior, brand equity, and executive decision-making. As organizations invested heavily in digital marketing, the ability to track, analyze, and report on social media activity became essential for aligning operations with broader strategic goals (Peters et al., 2024; Zhang et al., 2018). Despite the availability of advanced analytics platforms, many firms struggled to convert raw data into actionable insights that informed high-level decisions.

Moussa et al. (2020) distinguished between vanity metrics such as likes and impressions and actionable metrics that drove evidence-based decision-making. He emphasized that reliance on superficial indicators created a false sense of performance success while overlooking metrics tied to customer conversion, retention, and engagement. Similarly, Sussman et al. (2023) highlighted that social media analytics often failed to influence strategy due to misalignment with core business objectives and limited integration with consumer behavior analysis. Without aligning data collection with desired outcomes, firms risked making decisions based on fragmented or misleading information.

Eriksson et al. (2023) further illustrated that organizational structure and internal communication significantly affected the strategic use of social media reports. Their findings suggested that many firms treated social media reporting as a siloed function within the marketing department, preventing insights from reaching departments like product development, operations, or executive leadership. This limited the potential of social media data as a cross-functional strategic tool.

From a consumer culture perspective, Santos et al. (2023) highlighted that social media interactions were not just transactional but also participatory and identity-forming, suggesting that reporting should have incorporated qualitative insights alongside quantitative measures to fully capture brand-consumer dynamics. This view was complemented by Hayes et al. (2020), who demonstrated that integrating multimodal social data such as images, comments, and user-generated content deepened understanding of consumer sentiment and influenced product innovation and strategic marketing efforts. Organizationally, Eriksson et al. (2023) note that structural barriers and poor cross-departmental communication often hinder the strategic use of social media data. Cristòfol Rodríguez (2024) adds that the complexity of digital ecosystems requires adaptive reporting frameworks that can synthesize diverse data types and deliver insights tailored to decision-makers’ needs.

Several tools have become industry standards. Fanpage Karma offers a unified dashboard for multi-platform metrics and competitor benchmarks (Hesse et al., 2021). Brandwatch provides AI-driven sentiment analysis and trend detection (Nguyen et al., 2020), YouGov Brand Index specializes in brand health tracking across demographics (Jensen & Larsen, 2020), while Talkwalker integrates text and image analytics for deeper social listening). Sprout Social combines management and analytics for cross-team collaboration (Kim & Park, 2023), and SimilarWeb complements social media data with digital market intelligence (Singh & Patel, 2021).

The rise in infodemics underscores the need for advanced monitoring. Meltwater has proven effective in research across public health and policy. Studies show its role in tracking misinformation during COVID-19 (Kant et al., 2021), analyzing vaccine discourse (Jiang et al., 2021), capturing pandemic fatigue narratives (White et al., 2024), assessing public sentiment on AI in agriculture (Sanders et al., 2021), and evaluating reactions to UK bTB policy shifts (Dicks et al., 2021). Collectively, these cases highlight Meltwater’s ability to capture real-time discourse, filter engagement, and map sentiment—crucial for policy and communication strategies.

Overall, sophisticated platforms like these transform raw social media data into actionable intelligence, strengthening decision-making and public communication (Cristòfol Rodríguez, 2024; Sussman et al., 2023). Yet, effective use still depends on aligning tool capabilities with organizational objectives, skilled interpretation, and integrated processes (Robertson et al., 2023).

Together, these insights underscore that successful social media reporting must transcend simplistic metrics and siloed analysis. It requires a holistic, dynamic approach that integrates consumer culture understanding, advanced data interpretation, and organizational alignment to fully leverage social media as a driver of strategic advantage. Below comparison table of each social media analytics tools (

Table 1. Comparison of The Social Media Analytics Tools.

Software Tool	Key Features	Primary Use Case	Strengths	Limitations	Source
Fanpage Karma	Multi-platform dashboard, engagement metrics, competitor analysis	Social media performance tracking	Comprehensive cross-channel analytics; user-friendly interface	Lacks advanced AI-driven analysis capabilities	(Hesse et al., 2021)
Brandwatch	AI-driven sentiment analysis, trend detection, consumer insights	Social listening and brand monitoring	Powerful sentiment and trend analytics; highly scalable	High cost; requires skilled analysts	Nguyen et al. (2020)
YouGov Brand Index	Brand health tracking, consumer perception, demographic insights	Measuring brand reputation and perception	Rich consumer perception data; strong demographic segmentation	Less suitable for real-time tracking; survey-based data only	Jensen and Larsen (2020)
Talkwalker	Image recognition, text analytics, multimedia monitoring	Discovering narratives and sentiment in content	Advanced multimedia analytics; wide platform coverage	Complex setup; steep learning curve	Buus Lassen (2023)
Sprout Social	Social media management, team collaboration, reporting tools	Social media account management and workflow coordination	Integrated analytics and collaboration tools; scheduling capabilities	Limited data visualization features	Kim and Park (2023)
SimilarWeb	Web traffic intelligence, digital behavior metrics	Competitor analysis and digital market insights	Complements social data with website traffic metrics	Not focused on social-specific engagement or sentiment	Singh and Patel (2021)
Meltwater	Real-time social listening, sentiment tracking, influencer analysis, dashboarding	Infodemic response, crisis communication, policy advocacy	Broad platform coverage; engagement filtering; customizable dashboards; strong integration tools	Subscription-based; needs integration with tools like MAXQDA for deeper analysis	Kant et al. (2021); White et al. (2024)

):

The comparison highlights six prominent social media analytics tools, each with distinct strengths. Fanpage Karma offers a user-friendly dashboard for multi-platform tracking and competitor benchmarking but lacks advanced AI-driven analytics (Hesse et al., 2021). Brandwatch excels in sentiment analysis and trend detection, with features like historical data archives for longitudinal insights, though its complexity and high cost limit accessibility for smaller firms (Nguyen et al., 2020).

YouGov Brand Index focuses on brand health and consumer perceptions across demographics, providing reputation insights but less real-time analysis (Jensen & Larsen, 2020). Talkwalker combines text and image analytics, enabling analysis of multimedia content and deeper consumer narratives. Its merger with Brandwatch enhances strategic value, though both complexity and resource demands remain high (Buus Lassen, 2023).

Sprout Social integrates management, reporting, and collaboration, supporting operational efficiency but offering less sophisticated analytics (Kim & Park, 2023). SimilarWeb contextualizes social media insights with web traffic and audience behavior, although its focus on web metrics limits detail on platform-specific engagement (Singh & Patel, 2021).

Meltwater distinguishes itself in real-time monitoring across social media, news, blogs, and forums. It has been used effectively in public health, crisis communication, and policy research (Kant et al., 2021; White et al., 2024). Its broad coverage, influencer tracking, and issue mapping make it valuable, but subscription costs and reliance on complementary tools can be barriers.

In practice, leading agencies rarely rely on a single platform. Instead, insights are synthesized from multiple tools—covering monitoring, trend detection, competitive intelligence, and audience behavior—into professional reports for brand stakeholders (Nguyen et al., 2020; Buus Lassen, 2023). These reports often lead to the creation of a Social Playbook, which translates data into strategic guidelines on tone, campaigns, and engagement, ensuring alignment between business goals and social media execution.

1.1. Social Media Reporting and Strategic Decision-Making: The Link

Research shows that structured social media analytics help organizations anticipate market shifts, tailor strategies, and improve customer satisfaction. Rita et al. (2023) found that predictive analytics enhance campaign targeting and ROI, while Luo et al. (2013) demonstrated that integrating social media metrics with traditional KPIs boosts agility and innovation. Increasingly, marketers are expected to justify expenditures with data, turning reports into strategic dashboards that inform budgeting, brand positioning, and content planning (Leeflang & Addink, 2023; Margetts, 2024).

This approach is especially relevant in the public sector, where real-time sentiment tracking supports public health, crisis communication, and citizen engagement. By monitoring hashtags, keywords, and reactions, agencies can detect misinformation, assess trust, and adapt messaging. However, many institutions still rely on vanity metrics—likes, views, and follower counts—without linking them to meaningful outcomes (Hanlon & Tuten, 2022).

To be effective, social media reporting must focus on outcome-based KPIs such as conversion rates, sentiment trajectories, and multi-touchpoint journey mapping (Zhang et al., 2018). This deeper analysis is critical for public initiatives in disaster response, health communication, transport, and consultations, where understanding perceptions and behaviors directly improves policy design and delivery.

Effective social media reporting fosters strategic alignment, linking digital performance to broader goals such as citizen satisfaction, public trust, program participation, and return on investment. As Leeflang and Addink (2023) note, the ability to measure and justify performance is increasingly crucial, while Goh et al. (2013) highlight how feedback loops influence not only marketing but also service design, customer care, and long-term reputation. For the public sector, advanced analytics can support policy refinement, community engagement, and digital transformation.

Yet many organizations still rely on vanity metrics, lack contextual interpretation, or operate in silos where insights fail to inform leadership (Margetts, 2024; Fisher et al., 2021). This is especially problematic in government, where bureaucratic structures and limited analytic capacity slow responses to emerging sentiment or misinformation. Without real-time frameworks, agencies risk reputational damage from delayed or reactive communication.

To address this, public institutions must invest in systems that move beyond superficial metrics toward outcome-based, insight-driven action. Embedding social media reporting into strategic processes can enhance policy agility, strengthen trust, and ensure proactive engagement in the digital sphere. This paper examines how organizations can achieve this by reviewing key metrics, best practices, and integration frameworks. It positions social media reporting not as a routine marketing task but as a core strategic tool—essential for shaping strategy, strengthening relationships, and improving decision-making in the digital era.

1.2. Social Media Metrics and Analytics Frameworks

Foundational research underscores the need for relevant metrics in performance evaluation. Peters et al. (2024) classify metrics into activity, interaction, and return, yet note that firms often remain fixated on vanity measures such as likes or follower counts. Rita et al. (2023) argue for predictive analytics to anticipate consumer behavior, while Malthouse et al. (2024) propose integrating social media data into CRM systems for continuous improvement. Similarly, Zeng et al. (2023) identify three layers of analytics—descriptive (what happened), diagnostic (why it happened), and predictive (what will happen)—stressing the importance of connecting surface metrics with deeper strategic insights.

This layered approach is especially critical in the public sector, where decisions affect large populations. Without diagnosing sentiment drivers or anticipating future trends, institutions risk misalignment with citizen expectations and reputational damage. Multi-layered analytics enable earlier course correction, more efficient resource allocation, and greater transparency in decision-making.

Effective reporting turns raw data into actionable insights. Chaffey and Ellis-Chadwick (2019) recommend dashboards aligned with organizational goals, while Heath et al. (2013) show that consistent reporting routines help identify underperforming campaigns early. However, many organizations rely too heavily on automated reports without qualitative interpretation (Margetts, 2024). As Hsu et al. (2021) note, balancing quantitative engagement data with sentiment and contextual analysis allows for richer understanding of consumer intent and stronger alignment between strategy and communication.

1.3. Strategic Integration and Decision-Making Impact

The literature strongly supports the integration of social media reporting into broader strategic decision-making processes. Hsu et al. (2021) found that firms that use social media intelligence effectively tend to enjoy higher market valuations due to improved adaptability and responsiveness. Likewise, Leeflang and Addink (2023) identified that performance measurement systems directly influence strategic alignment in digital marketing, pushing firms toward evidence-based planning.

Saini et al. (2023) note that reporting not only supports marketing optimization but also informs strategic domains such as product development, customer support, and crisis communication. Their analysis of top-performing firms reveals a common trait: the ability to translate social media analytics into decisions that affect the entire value chain.

Moreover, the use of machine learning and natural language processing (NLP) to mine user-generated content is on the rise. Recent studies show that advanced analytics tools provide a competitive advantage by extracting deeper meanings from social conversations—offering insights that traditional methods might miss (Janssen et al., 2020). Ideally, all market sectors should access such data on a regular basis to support continuous strategic analysis and direction-setting. However, public sector institutions often appear slower to respond strategically, partly because they lack timely access to this kind of data—leading to delayed reactions in policy or service delivery adjustments (Zuiderwijk et al., 2021; Valle-Cruz et al., 2022).

1.4. Synthesis and Gaps

The reviewed literature establishes that while social media reporting can be a strategic asset, its impact is contingent on the metrics selected, interpretation skills, and cross-departmental collaboration. Yet, there is still a research gap in operationalizing these insights consistently across organizations. Many studies recommend frameworks but stop short of detailing implementation methods suitable for different business sizes or industries. Additionally, few articles address how reporting routines influence long-term strategic shifts, especially in volatile digital environments.

1.5. Synthesis of Key Findings

In conclusion, while the academic consensus affirms the value of social media reporting in strategic decision-making, the literature also reflects a growing awareness of its implementation challenges, organizational limitations, and skills gaps. Bridging these gaps will require more than better tools—it will demand better integration, training, and alignment across departments and leadership levels. Future studies must move beyond conceptual models to offer practical roadmaps and tested interventions for organizations seeking to elevate social media reporting from a reactive activity to a strategic asset.

1.6. Metric Selection Determines Strategic Relevance

Some scholars emphasize that the value of reporting lies in choosing metrics aligned with business objectives. Firms that rely solely on surface-level indicators like likes or shares often miss deeper behavioral and attitudinal trends that drive strategic insights. Conversely, companies that adopt predictive analytics and sentiment analysis tools tend to have greater agility in product development, customer service, and crisis management (Chatterjee et al., 2021).

1.7. Integration with Strategic Planning Is Inconsistent

Research by Gao and Luo (2021) and Leeflang and Addink (2023) demonstrates a clear link between robust social media reporting practices and stronger market performance. Yet, many firms treat reporting as a post-campaign evaluative exercise rather than as a real-time input into strategic decision-making cycles. This disconnect often stems from organizational silos, where marketing insights are not communicated effectively to top-level decision-makers (Margetts, 2024).

1.8. Real-Time Dashboards Enhance Agility

Studies by Chaffey and Ellis-Chadwick (2019) and Heath et al. (2013) show that real-time dashboards and integrated reporting platforms increase an organization’s ability to respond quickly to emerging trends. However, even with advanced dashboards, the interpretive capability of staff becomes the limiting factor. Without training in data literacy and contextual analysis, firms risk making decisions based on misunderstood metrics (Hsu et al., 2021).

1.9. Strategic Value Varies by Industry and Maturity Level

Literature indicates that industries such as retail, media, and hospitality are more mature in their use of social media reporting, whereas sectors like manufacturing or B2B services lag behind (Saini et al., 2023). Moreover, firm size and digital maturity affect how well social data is incorporated into high-level strategy, with smaller firms lacking the resources to implement complex analytics systems (Zeng et al., 2023).

1.10. Research Purpose, Questions, Objectives, and Gap

1.10.1. Research Purpose

The primary purpose of this study is to investigate how organizations—both in the business and public sectors—can enhance their social media reporting practices to better support strategic decision-making. This research aims to bridge the gap between the availability of advanced social media analytics tools and their effective integration into organizational strategy. By synthesizing insights from academic literature and expert interviews, the study seeks to identify best practices, align reporting with organizational goals, and enhance interpretive capacity across departments.

1.10.2. Research Questions

Drawing on gaps identified in prior literature (Margetts, 2024; Sussman et al., 2023; Zeng et al., 2023), this study addresses the following research questions:

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RQ1: How can social media reporting frameworks be designed to align with organizational strategic objectives in both public and private sectors?

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RQ2: What role do advanced analytics tools (e.g., Brandwatch, Meltwater, Sprout Social) play in improving the interpretive and strategic value of social media reports?

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RQ3: What organizational, cultural, and technical barriers hinder the integration of social media reporting into strategic decision-making processes?

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RQ4: How can qualitative insights (e.g., sentiment analysis, narrative mapping) be combined with quantitative metrics to create actionable intelligence for decision-makers?

These questions are grounded in recent calls for more actionable, outcome-oriented social media reporting (Banerjee & Chua, 2023; Santos et al., 2023; Leeflang & Addink, 2023).

1.10.3. Research Objectives

To address the above questions, the study is guided by the following objectives:

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O1: To evaluate existing social media reporting practices and their alignment with strategic objectives.

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O2: To examine the capabilities and limitations of leading analytics tools in generating actionable insights.

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O3: To identify organizational factors that facilitate or inhibit the strategic integration of social media reporting.

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O4: To propose a practical framework for outcome-based social media reporting that combines quantitative and qualitative insights.

1.10.4. Research Gap

Although existing research acknowledges the strategic potential of social media analytics (Zeng et al., 2023; Peters et al., 2024), most studies:

• Focus on either technical tool capabilities or marketing outcomes, without integrating organizational processes and decision-making frameworks (Robertson et al., 2023).
• Address predictive analytics or sentiment analysis in isolation, rather than as part of a cohesive, multi-layered framework (Janssen et al., 2020; Rita et al., 2023).
• Pay limited attention to public sector applications, despite evidence that timely, insight-driven reporting can significantly improve policy responsiveness and citizen trust (Mergel, 2019; Kant et al., 2021).

This study responds to these gaps by providing a cross-sector, integration-focused perspective.

2. Materials and Methods

This study adopts a qualitative dominant mixed-methods research design, combining a systematic literature review with semi-structured expert interviews. The rationale behind this dual approach is to integrate theoretical insights from existing scholarship with practical, real-world experiences from professionals actively engaged in social media reporting and strategic planning. This design enables both exploration and triangulation of themes related to social media data usage in strategic contexts.

Data collection using a systematic review of academic and industry literature was conducted using databases including Scopus, Web of Science, Google Scholar, and EBSCOhost. The following search terms were used: “Social media reporting”, “Social media analytics”, “Strategic decision-making and social media”, “Social media KPIs”, and “Digital marketing metrics”. Inclusion criteria: Peer-reviewed journal articles, conference papers, and white papers published between 2020 and 2024; studies with a focus on the strategic implications of social media metrics and literature offering frameworks, models, or case studies. Findings from the literature and interviews were triangulated to ensure validity and reliability. For example, concepts like “strategic misalignment” and “data literacy gaps” were present in both sources, reinforcing their credibility and significance in the study. Quantitative data analysis (e.g., metric performance correlations) was outside the scope and may be addressed in future work.

2.1. Sampling Strategy

The study employed purposive sampling to select organizations and participants most relevant to the research objectives. Public sector institutions were prioritized due to their increasing reliance on social media for citizen communication and engagement. Within these institutions, participants were drawn from communication teams, digital strategy units, and policy divisions, ensuring a mix of operational and strategic perspectives. This approach allowed the research to capture both technical reporting practices and higher-level decision-making processes.

2.2. Interview Design

Semi-structured interviews were conducted to balance consistency across respondents with the flexibility to probe deeper into emerging themes. The interview guide included questions on current reporting practices, perceived challenges, integration of analytics into decision-making, and perceptions of social media’s strategic role. Open-ended prompts were used to encourage participants to share concrete examples, while follow-up questions clarified terminology and explored nuances in organizational context. Each interview lasted between 45 and 60 min and was audio-recorded with participant consent.

2.3. Analytical Procedures

Data were transcribed verbatim and analyzed thematically using a hybrid deductive–inductive approach. Initial coding was guided by the theoretical framework of public value (transparency, trust, and citizen engagement), while inductive coding allowed new themes to emerge from the data. Codes were iteratively refined through constant comparison, and patterns were synthesized into higher-level categories that linked individual insights to broader organizational practices. To enhance reliability, coding was reviewed by a second researcher, and discrepancies were resolved through discussion. Triangulation with secondary sources (e.g., organizational documents, public reports) further strengthened validity.

3. Results and Discussion

3.1. YouGov Brand Index: Integrating Consumer Perception with Strategic Brand Tracking

The YouGov Brand Index is a globally recognized tool for tracking brand health, offering continuous insights into consumer perceptions through large-scale panel-based survey data. It provides marketers and strategists with real-time information across brand metrics such as awareness, consideration, satisfaction, reputation, and purchase intent, all segmented by demographics, geographies, and behavioral patterns (Jensen & Larsen, 2020).

Several scholars have emphasized its strategic value. Similarly, Smith (2019) highlight YouGov’s ability to fill perceptional gaps often missed by purely behavioral or social media-based tools, enhancing a brand’s understanding of how it is viewed among different audience groups. Martínez and López (2021) further explore the platform’s practical utility in the FMCG sector, where brand loyalty is critical. By identifying evolving brand sentiment and emerging preference shifts, YouGov supports decision-makers in product positioning and innovation strategies. The platform’s depth allows for highly targeted interventions based on user-generated insight.

The integration of survey data with digital sentiment is another strength noted by Kim et al. (2022), who suggest that combining YouGov with social listening tools provides a more holistic picture of a brand’s real-time and long-term performance. This hybrid model allows brands to not only react to immediate crises but also plan long-term reputation strategies grounded in quantitative evidence.

However, Rodriguez and Chen (2023) critique YouGov’s relatively slower reaction time due to its reliance on structured surveys, which can limit its effectiveness during high-speed media crises or rapidly evolving social movements. Nevertheless, the data generated remains invaluable for strategic planning, where long-term shifts in public sentiment and perception are more relevant than transient social commentary. The YouGov Brand Index, in particular, serves as a bridge between reactive digital metrics and long-term brand management strategies, offering marketing executives and policymakers a reliable compass for making informed decisions grounded in how real audiences think and feel over time.

In the public sector, YouGov’s capabilities are increasingly leveraged for a wide range of applications, especially where policy perception, public trust, and civic engagement need to be understood in depth. Government agencies and ministries have used YouGov surveys to measure public satisfaction with government programs, track perception of political figures or policy directions, and assess voter attitudes ahead of elections or referendums. Because of its methodologically rigorous sampling and longitudinal tracking, YouGov is particularly valuable in providing evidence-based insights that support democratic governance, policy refinement, and citizen-centric public service design.

For example, in the context of public health, YouGov data has been employed to analyze public willingness to follow vaccination programs or trust in health institutions. In environmental policy, it has helped governments assess public concern over climate change and tailor communication strategies accordingly. While not designed for real-time crisis monitoring, YouGov complements faster tools like social listening platforms by offering deeper, statistically validated insights that support long-term narrative framing and strategic decision-making in the public sphere.

3.2. Brandwatch: Data-Driven Social Listening for Strategic Brand Decisions

Brandwatch is one of the most advanced AI-powered social listening platforms currently available, widely utilized for sentiment analysis, trend detection, and competitor benchmarking. It enables organizations to monitor conversations across millions of online sources in real time—including blogs, forums, news outlets, and social media—providing a comprehensive understanding of public perception (Chong et al., 2021). Brandwatch’s capacity to process vast datasets allows decision-makers to extract consumer insights that directly inform marketing, branding, and communication strategies. From a strategic decision-making perspective, Brandwatch empowers organizations to adapt swiftly to shifts in public sentiment and emerging issues. Jiang et al. (2021) emphasized that Brandwatch’s dashboard provides customizable KPIs (e.g., sentiment scores, share of voice, topic clouds) that help leadership teams align messaging with market expectations and prevent reputational crises.

Furthermore, Brandwatch is particularly effective in competitive analysis. According to Nguyen et al. (2020), the software enables companies to benchmark against competitors by analyzing how rival brands are discussed online, which helps in refining pricing, positioning, and promotional strategies. This directly supports market differentiation, as brands can identify their strengths and weaknesses in the eyes of the public and adjust their value propositions accordingly. Notably, this kind of benchmarking is also highly relevant for the public sector, where agencies can evaluate how citizens perceive competing programs, policies, or service providers—enabling data-driven improvements in public service delivery.

Real-time intelligence from Brandwatch also enhances product innovation. By analyzing consumer feedback on features, usability, and pain points, companies can tailor product development to customer needs. This approach, as demonstrated by Cheng and Liu (2022), not only minimizes the risk of product-market misalignment but also accelerates time-to-market with higher confidence in demand validation. In addition, Brandwatch’s “Total History” feature provides access to extensive longitudinal data, allowing both businesses and public institutions to track sentiment and issue evolution over time. This capability is especially useful for identifying recurring patterns, measuring the long-term impact of past campaigns or policies, and informing future strategic planning.

However, while Brandwatch excels in digital coverage, its focus on online discourse means it may underrepresent offline consumer sentiment, such as those gathered through in-person surveys or panels. As such, many scholars recommend integrating Brandwatch data with panel-based platforms like YouGov or Fanpage Karma for more rounded strategic insights (Park & Lee, 2020).

Table 2. Summary of Strategic Contributions of Brandwatch.

Strategic Area	Brandwatch Contribution
Crisis Management	Early detection of negative sentiment and emerging issues
Competitive Intelligence	Tracks competitor mentions, sentiment, and share of voice
Brand Positioning	Reveals consumer associations and emotional tone of conversations
Product Development	Informs feature design and refinement based on consumer feedback
Campaign Optimization	Monitors real-time campaign performance and public reception
Trend & Historical Analysis (Total History)	Leverages extensive historical data to identify long-term trends and evaluate past strategic impacts

Source: (Park & Lee, 2020); Nguyen et al. (2020). Brandwatch in the Public Sector: Enhancing Public Communication and Policy Responsiveness.

below Summarized Strategic Contributions of Brandwatch:

While Brandwatch is widely recognized for its commercial and marketing applications, its utility in the public sector has been increasingly acknowledged. Government agencies, NGOs, and public institutions have begun to employ Brandwatch to monitor public discourse, track sentiment about policies, and respond to crises with data-driven communication strategies. According to Batrinca and Treleaven (2014), social media analytics tools like Brandwatch can help public sector bodies detect real-time sentiment shifts regarding controversial issues such as healthcare reform, education policy, or public safety initiatives. This can support strategic decision-making by revealing how the public interprets and reacts to proposed or implemented policies. For instance, during the COVID-19 pandemic, multiple governments used social listening platforms (including Brandwatch) to monitor citizen concerns, misinformation trends, and vaccine sentiment.

Additionally, Brandwatch aids in crisis communication by flagging emerging public grievances or misinformation. Real-time dashboards allow public affairs teams to rapidly intervene and correct narratives before they escalate. This contributes to transparency and trust, two pillars of effective public governance (Mergel, 2019). In terms of policy design, public sentiment analysis through Brandwatch can help policymakers incorporate citizens’ voices into legislative discussions. For example, monitoring opinions about public transport systems or environmental reforms enables local governments to prioritize actions aligned with citizens’ preferences, fostering participatory governance. Despite these advantages, scholars like Sandoval-Almazan and Gil-Garcia (2020) note that public institutions often face challenges in interpreting large-scale social data without bias, highlighting the need for training and ethical frameworks when adopting tools like Brandwatch in government settings. Examples of Brandwatch Use in the Public Sector are described in

Table 3. Examples of Brandwatch Use in the Public Sector.

Application Area	Use Case Example
Public Health	Monitoring sentiment on vaccines, health campaigns, or misinformation trends
Crisis Communication	Detecting and mitigating public backlash during emergencies
Urban Policy Feedback	Understanding citizen responses to infrastructure projects
Misinformation Management	Identifying and responding to false narratives on social platforms
Strategic Communication	Tailoring messages to specific groups based on sentiment and engagement trends

Source: Mergel (2019); Sandoval-Almazan and Gil-Garcia (2020).

:

One of Brandwatch’s most prominent features is the Total History function, which enables comprehensive and in-depth access to historical social media data. In the context of the public sector, this feature plays a highly strategic role, particularly in supporting data-driven decision-making and the formulation of more responsive public policies. Through the Total History feature, government institutions can conduct long-term sentiment analysis, allowing them to understand how public perception of specific policies has evolved over time. For example, when evaluating national vaccination programs or social assistance policies, governments can trace the dynamics of public opinion from the implementation phase to the present day, providing valuable insights into the effectiveness of past communication efforts.

Furthermore, this feature facilitates the identification of recurring public issues, such as dissatisfaction with administrative services, spikes in discussion following natural disasters, or public sentiment toward national leaders. This information can be used to map communication risk and anticipate potential future opinion crises. Total History also plays a key role in evaluating government communication performance over time, by comparing the effectiveness of digital strategies across periods and platforms. The insights gained from this historical analysis can serve as the foundation for developing strategic documents such as a Social Media Playbook tailored to public institutions. This playbook may include data-driven communication guidelines, including tone of voice, optimal publishing schedules, and best practices for responding to sensitive topics.

Moreover, having well-documented historical data strengthens transparency and government accountability to the public. By demonstrating how the government has consistently responded to public issues, institutional trust can be reinforced. Therefore, the Total History feature in Brandwatch is not only relevant for commercial sectors but also holds strong potential for enhancing the quality of public sector communication governance, ensuring it is data-based and responsive to societal needs.

3.3. Fanpage Karma: Engagement-Centric Social Media Management

Fanpage Karma is primarily known for tracking engagement metrics such as likes, comments, shares, and follower growth across platforms like Facebook, Instagram, X (Twitter), and LinkedIn. Its strengths lie in content performance analysis, competitor benchmarking, and social media scheduling. In business contexts, Fanpage Karma is instrumental for SMEs and digital marketing teams aiming to optimize their organic social media strategies. The platform’s emphasis on engagement makes it ideal for understanding what content resonates with target audiences (Arora & Sanni, 2018). The automated reports and benchmarking tools aid in performance improvement and campaign adjustments. Public sector bodies such as municipalities or government health departments can use Fanpage Karma to monitor citizen engagement with campaigns, track which types of posts generate the most public interaction, and adjust outreach tactics accordingly. This helps in designing inclusive, responsive communication strategies (Mergel, 2019).

3.4. Talkwalker: Deep Listening and Predictive Analytics

Talkwalker is a robust AI-powered platform offering image recognition, voice analytics, predictive trend analysis, and cross-channel sentiment tracking. It analyzes both owned and earned media and is often used by enterprise-level brands. Talkwalker allows large corporations to track brand mentions across global news and social media, and even analyze visual brand exposure using image recognition. Its predictive analytics help marketing teams anticipate consumer behavior and tailor campaigns proactively (Grajales et al, 2014). The platform supports crisis detection, influencer discovery, and multilingual monitoring, enabling strategic brand protection. Talkwalker’s strength in trend prediction and sentiment analysis makes it ideal for governments and NGOs managing sensitive issues like elections, public protests, or disaster response. For instance, tracking misinformation or citizen sentiment during election cycles enables early detection of discontent and targeted civic education.

3.5. SimilarWeb: Digital Market Intelligence and Competitive Benchmarking

SimilarWeb specializes in web traffic analytics, offering insights on website performance, audience demographics, user journeys, bounce rates, and keyword performance. It is frequently used for SEO, digital strategy, and competitive intelligence. In business, SimilarWeb helps companies understand their digital market positioning, identify referral traffic sources, and evaluate online behavior of both competitors and their own audience (Chaffey & Ellis-Chadwick, 2019). This data is crucial for refining content strategies, choosing the right platforms for advertising, and improving website UX for conversion optimization. Governments and public institutions use SimilarWeb to analyze traffic to public service websites, monitor public interest in policy issues, and ensure accessibility and usability of digital government services. For example, ministries of health can evaluate whether public information websites on health campaigns are effectively reaching intended audiences (OECD, 2020).

Each tool contributes to strategic decision-making by offering data-backed insights. In business, this means profitability and market responsiveness. In the public sector, it supports policy agility, transparency, and citizen satisfaction. Marketing Managers: Can choose tools that align with specific KPIs (e.g., Fanpage Karma for engagement, Talkwalker for brand health, SimilarWeb for SEO). Policy Makers: Gain real-time feedback on public initiatives and detect disinformation early. Data Analysts: Use cross-tool integration for deeper insights and long-term trend reporting.

3.6. Sprout Social: Unified Social Media Management and Strategic Decision Support

Sprout Social is a robust social media management platform that integrates publishing, engagement, analytics, and customer care in one interface. It is known for its intuitive dashboards, real-time monitoring, and collaborative workflow tools, making it ideal for both commercial and governmental communication strategies. Core Features of Sprout Social: (1) Smart Inbox for unified message tracking across platforms (Facebook, X, LinkedIn, Instagram) (2) Social listening for sentiment and keyword trends (3) Detailed analytics and reporting (performance benchmarking, engagement metrics) (4) CRM integration for tracking audience profiles and conversation history.

According to Sussman et al. (2023), centralized platforms like Sprout Social facilitate cross-functional collaboration, allowing organizations to align marketing, PR, and customer service goals more efficiently. Sprout Social offers real-time, consolidated data that helps firms: (1) Track campaign performance by visualizing engagement trends. (2) Improve customer interaction quality through timely responses and sentiment detection. (3) Support brand strategy adjustments based on listening insights and KPI tracking. As noted by Hayes et al. (2020), platforms with integrated social listening and analytics drive real-time strategic agility, enabling firms to optimize brand narratives and crisis response. Example: A retail company can use Sprout Social to identify customer pain points during a product launch and adjust messaging or logistics in real time, improving both customer experience and revenue impact.

In the Public Sector, Sprout Social is highly relevant for government agencies managing citizen engagement via social media. Public health departments analyzing sentiment toward health policies or crises. City councils or municipal bodies improving transparency and digital governance. According to Mergel (2019), such tools empower digital service teams to maintain citizen trust by ensuring fast response times and aligning digital communication with policy effectiveness. Example: A city government can monitor public sentiment about transportation projects or policy changes (e.g., toll adjustments), then use Sprout Social dashboards to adjust outreach strategies and community education campaigns accordingly.

Table 4. Summary Table: Practical Uses in Business and Public Sector.

Tool	Business Application	Public Sector Application
Fanpage Karma	Social media engagement analysis; campaign content testing	Public outreach monitoring; campaign engagement tracking
Talkwalker	Sentiment analysis, crisis detection, predictive insights	Misinformation tracking; public sentiment on policies
SimilarWeb	Market intelligence, competitor web analytics	Monitoring traffic to public portals; optimizing e-government sites

Sources: Cristòfol Rodríguez (2024).

integrates the integration tools.

3.7. Media Intelligence in Governance: Meltwater’s Contributions to Public Sector Strategy

Meltwater plays a strategic role in the public sector by enabling real-time media intelligence, social listening, and narrative tracking across digital platforms. Public institutions utilize Meltwater to monitor citizen sentiment, detect misinformation, evaluate communication impact, and respond promptly to crises. Its capacity to aggregate data from news outlets, blogs, forums, and social media (e.g., Twitter/X, Facebook, Instagram, TikTok) makes it especially valuable for policy feedback loops and infodemic control (Kant et al., 2021).

One of Meltwater’s key advantages is its real-time alerting system and keyword-based tracking, which allow public health agencies, ministries, or government communication departments to anticipate public reactions and proactively tailor their outreach. For instance, Meltwater was used effectively by the Indian Council of Medical Research (ICMR) during the COVID-19 pandemic to counter misinformation, measure public trust, and refine health messaging (Kant et al., 2021). It also supports advocacy-based monitoring, as seen in Germany’s use of Meltwater to detect unauthorized tobacco product advertising on platforms like Instagram and TikTok, despite formal bans (Wüllner et al., 2024).

Moreover, Meltwater’s engagement analytics and influencer mapping are instrumental in identifying which messages are resonating and through which actors. This allows governments to partner with credible voices in civil society or public health to amplify campaigns and correct false narratives. Its application is especially relevant during elections, health emergencies, environmental disasters, and vaccine rollout initiatives (Wüllner et al., 2024).

Despite its strengths, Meltwater requires skilled interpretation and integration with broader communication strategies. It does not offer survey-based insights (as YouGov Brand Index does), but it excels in observational data collection and discourse mapping, which are crucial in complex or fast-changing policy environments (Kant et al., 2021; Wüllner et al., 2024) (see

Table 5. Strategic Comparison of Social Listening and Intelligence Tools. in Business and Public Sector Contexts.

Tool	Key Strengths	Strategic Value in Business	Strategic Value in Public Sector
Sprout Social	Unified publishing, listening, CRM integration	Enhances customer engagement & content timing	Informs policy messaging & citizen response tracking
Fanpage Karma	Benchmarking, competitive analysis	Content and performance optimization	Tracking community engagement
Talkwalker	AI sentiment, image/audio analytics	Crisis detection and trend forecasting	Monitoring misinformation and public risk
SimilarWeb	Web traffic, user journey, SEO/PPC insights	Conversion optimization and market expansion	Digital accessibility and service optimization
Brandwatch	Deep listening, trend prediction, topic clusters	Consumer behavior insights, brand strategy	Monitoring societal feedback on regulations
YouGov Index	Consumer perception, brand equity monitoring	Longitudinal brand performance	Public perception of government services
Meltwater	Real-time listening, influencer mapping, media monitoring	Reputation management, influencer strategy, market pulse	Infodemic management, early risk detection, crisis response

Sources: Sussman et al. (2023); Hayes et al. (2020).

).

Below is a Visual Model Structure describing the integration social media tools: The visual model in Figure 1 illustrates the strategic utilization of various social media intelligence tools across business and public sector domains. It begins with the aggregation of digital tools, including Sprout Social (SPRS), Brandwatch (BRDW), Talkwalker (TLKW), Fanpage Karma (FPK), YouGov Brand Index (YG), SimilarWeb (SW), and Meltwater (MLTW), which collectively function to gather real-time data from diverse digital channels. These tools enable the systematic collection of information related to sentiment analysis, trend monitoring, and key performance indicators (KPIs).

Once data is collected, it enters the processing and analytics phase, where insights are extracted through artificial intelligence algorithms, thematic categorization, and sentiment scoring. This processed data becomes a critical input for strategic decision-making. At the strategic level, the outputs serve two primary pathways: business use and public sector use. In the business context, tools such as Brandwatch and SimilarWeb support customer engagement, market forecasting, and brand positioning. Meanwhile, in the public sector, platforms like Meltwater and YouGov facilitate the tracking of public opinion, policy reception, and crisis response—especially during events like pandemics or environmental incidents.

Overall, this flow demonstrates how social listening and digital monitoring tools bridge the gap between unstructured online data and actionable insights that inform both commercial strategies and public communication initiatives. This stage shows how analysis leads to targeted action in organizational strategy. At the bottom of the model is the Decision Layer, where leadership teams or departments make evidence-based decisions: Reallocating budgets, Rewriting public service messages, Innovating based on unmet needs, and Enhancing customer or citizen experience. Arrows looping upward may also appear here, symbolizing a feedback loop new data is constantly re-collected to refine future strategies. They flow from:

Tools → Analysis → Strategic Areas → Informed Decisions

Illustrates how modern social media tools support organizational agility, improve communication, and drive better outcomes in both business and government environments.

These findings not only corroborate and extend prior research on social media analytics but also tie directly into the broader public value framework guiding this study. The continued reliance on vanity metrics may limit strategic foresight, yet in the public sector, they also serve as visible signals of responsiveness, thereby contributing to perceptions of transparency. At the same time, the absence of diagnostic and predictive layers—despite their emphasis in the literature (Zeng et al., 2023; Rita et al., 2023)—risks eroding trust, as institutions may appear reactive rather than proactive in addressing citizen concerns. Finally, where organizations fail to integrate sentiment and contextual analysis into reporting (Margetts, 2024; Hsu et al., 2021), opportunities for meaningful citizen engagement are lost, reducing alignment between public expectations and institutional action.

By situating the findings within this framework, the study highlights how social media analytics are not merely technical practices but essential mechanisms for building transparency, strengthening trust, and deepening citizen engagement—the core components of public value.

4. Conclusions

In an era where data-driven decision-making was increasingly vital, social media reporting emerged as a critical enabler of both business growth and public sector responsiveness. This research explored how advanced social media analytics tools—including Brandwatch, Sprout Social, Talkwalker, Fanpage Karma, YouGov Brand Index, SimilarWeb, and Meltwater—facilitated deeper insights into audience behavior, public sentiment, brand perception, and market dynamics. Each tool offered unique strengths: Brandwatch excelled in sentiment tracking and trend forecasting, proving ideal for both corporate reputation management and public communication monitoring. Sprout Social supported agile content strategies and team collaboration. Fanpage Karma and Talkwalker provided actionable engagement metrics and competitor benchmarking. YouGov Brand Index contributed survey-backed opinion tracking, which was valuable for government and corporate branding efforts. SimilarWeb added value with detailed web traffic analytics for campaign effectiveness evaluation. Meltwater, notably, strengthened media monitoring and real-time social listening capabilities. It enabled institutions to detect crises early, map influencers, and address misinformation—a crucial component in both brand protection and infodemic management.

Together, these platforms formed a robust ecosystem that transformed fragmented social data into strategic intelligence. By integrating these tools within a structured framework—as proposed in this study—organizations were able to better align their social media efforts with broader strategic goals, enhancing decision-making and stakeholder engagement. Moreover, the practical implications across both the business and public sectors revealed that social media reporting was no longer just a marketing function but a strategic necessity. For public institutions, these tools offered new pathways for transparency, responsiveness, and citizen-centric policy design. For businesses, they empowered proactive brand positioning, risk management, and customer-centric innovation.

In conclusion, effective social media reporting—when grounded in the right tools and a clear analytical framework—not only supported tactical campaign decisions but also served as a cornerstone for long-term strategic success in a connected digital world. Future research was recommended to further explore integration with AI-based predictive analytics and cross-sector collaboration models to enhance its strategic value.

Foundational research stresses the importance of using relevant metrics to evaluate performance. Consistent with Peters et al. (2024), the findings show that many organizations continue to prioritize vanity metrics such as follower counts and likes. While these metrics are accessible and easy to communicate, they offer limited insight into strategic outcomes. However, in contrast to Peters et al.’s corporate-focused findings, this study reveals that public institutions often rely on vanity metrics as a means of demonstrating accountability and visibility to citizens, suggesting a context-specific adaptation of such practices.

Rita et al.’s (2023) advocacy for predictive analytics highlights a significant gap in practice. While the data confirm that predictive models are rarely implemented, this underutilization reflects a broader organizational hesitancy to invest in forward-looking analytics, particularly within the public sector. This aligns with Zeng et al.’s (2023) three-layer model: descriptive metrics dominate (tracking what has happened), diagnostic analysis is inconsistently applied, and predictive analytics are nearly absent. Thus, the findings corroborate both Zeng et al.’s framework and Rita and Alfonso’s call for greater emphasis on predictive insights, underscoring a persistent imbalance across analytical layers.

Integration challenges also emerge in light of Malthouse et al.’s (2024) Social CRM House model. Whereas the model emphasizes embedding social media data into wider CRM systems to enable strategic foresight, this study finds that many organizations, especially public institutions, operate in silos where social media insights remain disconnected from broader decision-making frameworks. This divergence highlights an implementation gap between conceptual models and practical realities.

In terms of reporting practices, the findings support Chaffey and Ellis-Chadwick’s (2019) recommendation for goal-oriented dashboards, as organizations with structured reporting routines demonstrate greater agility in detecting underperforming campaigns. However, the results also echo Margetts’s (2024) concern that many institutions rely heavily on software-generated reports without sufficient contextual interpretation. This tendency diminishes the value of analytics, as surface-level engagement numbers are often presented without diagnostic or qualitative insights. In line with Hsu et al. (2021), the findings suggest that balancing quantitative data with sentiment and contextual analysis provides a richer understanding of stakeholder intent and enables more precise alignment between messaging and expectations.

Overall, the study reinforces the literature’s consensus on the need for multi-layered, integrated, and context-sensitive social media analytics. Yet it also extends existing debates by showing that in public sector contexts, vanity metrics may function less as superficial indicators and more as symbolic tools for demonstrating responsiveness, even if they fall short of fostering deeper strategic insights.

5. Limitations, Future Research Directions, and Implications

5.1. Limitations

This study has several limitations:

• Scope: The analysis is based on a qualitative dominant mixed-methods approach, limiting statistical generalizability.
• Tool Selection: Only a subset of widely used analytics tools was examined; emerging platforms may offer additional functionalities not covered here.
• Sectoral Focus: While both public and private sectors are considered, the diversity within each sector means findings may not apply universally.
• Data Type: The study focuses on digital social media data and does not integrate offline sentiment or ethnographic observations.

5.2. Future Research Directions

Future studies could:

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Employ longitudinal designs to measure the sustained strategic impact of improved reporting frameworks.

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Investigate integration with AI-driven predictive analytics to forecast public sentiment and market shifts.

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Explore cross-sector collaborations to develop standardized public–private reporting protocols.

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Conduct experimental studies testing decision-making outcomes before and after the adoption of proposed frameworks.

5.3. Implications

Theoretical Implications: This research contributes to the literature by framing social media reporting as an integrated strategic tool, linking technical capabilities to organizational decision-making.

Practical Implications: The findings offer managers, policymakers, and communication professionals a framework for selecting tools, structuring reports, and aligning insights with strategic objectives.

Policy Implications: For the public sector, the study underscores the role of social media reporting in enhancing transparency, responsiveness, and public trust, particularly in health, crisis, and policy communication contexts.