Big Data Analytics Boosts Political Campaigns, Ghana Study Finds

In the sprawling machinery of a modern election campaign, data has become as important as the stump speech. A new study from Ghana now offers some of the clearest evidence yet that the analytical muscle behind big data is not just a corporate asset but a political one, particularly in the developing democracies where such research has been scarce. The work, published in SN Social Sciences by Philip Siaw Kissi, Isaac Brako and Opoku Gyabaah, examines how a political party’s capacity to collect, process and act on large volumes of data translates into measurable campaign performance, and it arrives at conclusions that are both encouraging and subtly cautionary for strategists hoping to replicate the data-driven playbook of campaigns in the United States and Europe.

The researchers set out to fill a conspicuous gap. Big data analytics capability, often abbreviated as BDAC in the management literature, has been studied extensively in business contexts, where firms that can harness analytics are repeatedly shown to outperform rivals in innovation, marketing agility and risk management. Yet the political sphere, especially in African democracies, has remained largely unexamined territory. The authors note that while data-driven campaigning is well established in advanced democracies, its dynamics in developing democracies have gone largely unexplored, despite the fact that political parties in countries such as Ghana face many of the same pressures to modernize that transformed corporate marketing a decade earlier.

To build their theoretical scaffolding, the team drew on Institutional Theory, a framework that explains how organizations adopt structures and practices in response to pressures from their environment, whether coercive rules, normative expectations or the mimetic pull of copying successful peers. Applied to politics, the theory suggests that parties do not adopt analytics in a vacuum; they respond to institutional pressures, including the visible successes of digitally sophisticated competitors and the growing expectation that campaigns will be professional, responsive and technologically current. This framing allowed the researchers to treat analytics capability not merely as a technical resource but as an organizational adaptation shaped by the political ecosystem in which a party operates.

The study employed an explanatory research design, gathering data from 331 political campaign actors in Ghana through a structured questionnaire. Ghana makes a compelling laboratory for this kind of inquiry. The country’s Fourth Republic has held successive competitive elections, its parties operate within a vibrant media environment, and its recent campaigns have increasingly migrated onto social media platforms where digital engagement and data collection intersect. The researchers then analysed the survey data using Partial Least Squares Structural Equation Modelling, or PLS-SEM, a statistical technique well suited to testing networks of hypothesized relationships among latent constructs that cannot be directly observed, such as analytical capability or voter engagement. The method estimates both the measurement model, which checks that survey items reliably capture the underlying concepts, and the structural model, which tests the paths connecting them.

The headline findings are straightforward. Big data analytics capability showed a significant positive association with both voter engagement and political campaign performance. In other words, campaign organizations with stronger analytical capacity tended to report more engaged voters and better campaign outcomes. Voter engagement itself was also positively associated with campaign performance, confirming the intuitive chain in which analytics helps a campaign connect with citizens, and that connection in turn supports electoral success. For the authors, these results extend Institutional Theory into the political arena and provide empirical evidence from a developing democracy, a context where the mechanisms linking technology to political effectiveness have rarely been quantified.

But the study’s most interesting results lie in what did not hold. The researchers hypothesized that voter engagement would mediate the relationship between analytics capability and campaign performance, meaning that analytics would improve performance primarily by energizing voters. The data did not support this. Voter engagement did not significantly mediate the BDAC-performance relationship, suggesting that analytics capability may improve campaign performance through channels other than voter enthusiasm, such as better resource allocation, sharper targeting of messages, or more efficient ground operations. This null result is a useful corrective to the popular narrative that data-driven politics works mainly by micro-targeting persuasive content at individual voters. The Ghanaian evidence hints that the operational advantages of analytics may matter at least as much as its persuasive ones.

The second moderating variable, digital opportunism, produced a similarly nuanced picture. Digital opportunism refers to an organization’s propensity to sense and seize emerging opportunities in digital environments, whether new platforms, viral moments or shifting online conversations. The study found that digital opportunism strengthens the relationship between big data analytics capability and voter engagement. A campaign that can both analyze data and act quickly on digital openings appears to convert its analytical capability into genuine voter connection more effectively than one that merely crunches numbers. However, digital opportunism did not moderate the other paths in the model, including the link between analytics and campaign performance itself. The opportunity-sensing mindset, in other words, amplifies the engagement side of the equation but does not change how analytics translates directly into performance.

These findings carry practical weight for political strategists, particularly in emerging democracies where campaign budgets are constrained and every investment must be justified. The results suggest that building analytics capability, encompassing the technology, the skilled personnel and the management processes needed to turn raw data into decisions, is associated with better campaign outcomes. But they also suggest that analytics alone is not a silver bullet. Campaigns that want to deepen voter engagement should pair their analytical investments with a culture of digital opportunism, staying alert to the fast-moving rhythms of online political conversation. And campaigns expecting engagement to be the sole bridge between data and victory may need to look elsewhere, since the study found no significant mediating role for engagement in that relationship.

The research also speaks to a broader scholarly conversation about the digital transformation of democratic politics. Scholars have documented how social media reshape political participation, how platform affordances alter the ways citizens engage with campaigns, and how data-driven campaigning has evolved into a systematic field of study in Western democracies. By testing these ideas in Ghana, the study joins a growing body of work examining how digital tools function in contexts with different institutional arrangements, media ecosystems and levels of connectivity. The authors argue that extending Institutional Theory into the political sphere in this way advances theoretical understanding while offering actionable insights for practitioners, a dual contribution that reflects the study’s position at the intersection of information systems research and political science.

The study was reviewed and approved by the Ghana Communication Technology University Research Ethics Committee, with voluntary participation and written informed consent from all respondents, and the authors declare no funding or conflicts of interest. Like all survey-based research, it has limits that readers should keep in mind: the data capture the perceptions of campaign actors at a single point in time, and associations identified through structural equation modelling do not by themselves prove causation. Even so, the message is timely. As elections across Africa and the wider developing world become increasingly digital contests, the question is no longer whether campaigns will adopt big data analytics but how they will do so effectively. This study suggests that the answer lies not in technology alone, but in the combination of analytical capability, an opportunistic digital culture and a clear-eyed understanding of which pathways actually lead from data to votes.

Subject of Research: The association between big data analytics capability and political campaign performance in Ghana

Article Title: Unveiling the association between big data analytics capability and political campaign performance: the role of voter engagement and digital opportunism

Article References: Kissi, P. S., Brako, I., & Gyabaah, O. (2026). Unveiling the association between big data analytics capability and political campaign performance: the role of voter engagement and digital opportunism. SN Social Sciences, 6(9), Article 433. https://doi.org/10.1007/s43545-026-01734-9

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01734-9

Keywords: big data analytics, political campaigns, voter engagement, digital opportunism, Ghana, PLS-SEM, Institutional Theory, political communication, developing democracies, campaign performance, social media, political marketing