The Role of Campaign Descriptions and Visual Features in Crowdfunding Success: Evidence from Africa

Abstract

Crowdfunding has gained popularity among entrepreneurs who seek funding for their business projects on crowdfunding platforms. The success of these campaigns largely depends on the ability to attract and convince backers to support the fundraising initiative. Drawing on signalling, persuasion, and attribution theories, this study examines how campaign descriptions and visual features specifically word description length, spelling errors, images, frequently asked questions (FAQs), number of backers, funding target, flexible funding, and campaign duration. The study utilised econometric techniques such as ordinary least squares and logistic regression models on a dataset consisting of 854 small and medium enterprises and entrepreneurial projects collected from Kickstarter, Indiegogo, and Fundraised databases. The probability of success is significantly increased by the length of project descriptions, the inclusion of images, and an increased number of backers. On the other hand, higher funding targets and flexible funding models decrease the probability of success. These results support the attribution and persuasion theories, indicating that detailed project descriptions can address information gaps and improve the project’s credibility and trustworthiness. This study contributes to the literature by providing an empirically grounded understanding of how textual and visual elements influence crowdfunding outcomes in the African context and offers practical guidance for entrepreneurs and investors on designing effective campaigns.

1. Introduction

The significance of the length of the project description in promoting engagement and helping project creators to reach their goals cannot be overstated. Effective persuasion requires communicating in a way that resonates with and is understandable to the audience. This is pertinent for entrepreneurs who use crowdfunding platforms to create project presentations that attract investors or backers to fund their projects. Crowdfunding platform fraudsters represent a severe risk to backers and investors (Cumming et al., 2023). These con artists perform various fraudulent acts, including fabricating platforms, misrepresenting campaigns, spending funds to their advantage, and making untrue promises to backers (Mbarek & Trabelsi, 2020). Nowadays, advanced description text analysis may reveal the secrets behind the power of words and assist in exposing the dishonesty of con artists (Perez et al., 2022). By providing potential individuals with more information about the campaign and its creator, the length of the word description can reduce fraud in crowdfunding by enabling them to make more informed decisions about whether or not to contribute (S. Lee et al., 2022).

In the context of the fourth industrial revolution, crowdfunding has become a popular financing option due to the constraints associated with conventional methods. Entrepreneurs needing substantial funding have traditionally relied on venture capital or bank loans to secure the required capital (Mamaro & Sibindi, 2023). The crowdfunding market experienced significant growth, doubling its size with a 101.5% increase in 2018. However, the African market share of this market was minimal, accounting for just 0.07% at the end of 2018 (Adjakou, 2021). Forecasts suggest a steady growth rate of 5.45% annually from 2024 to 2028, culminating in a market volume of USD 1.83 m in 2028 (Statista, 2024). Despite its increasing popularity and growth, crowdfunding activities still need to be more frequent in Africa (Mamaro & Sibindi, 2022). Consequently, the study explored how the wording of descriptions affects the success of crowdfunding campaigns. The general goal of this research is to investigate the function of campaign descriptions and visuals in deciding the success of African crowdfunding campaigns. Specifically, the research seeks to achieve the following:

• Examine the role of campaign language and tone of narrative (e.g., word, length, and emotional intensity) on crowdfunding success and thus explain the way textual accounts are used as quality project signals.
• Evaluate the impact of visual content (e.g., video and image content) on the chances of campaign success, in terms of how visual cues build confidence and credibility on crowdfunding platforms.
• Describe how text and image signals combine to construct backers’ perceptions and decisions, utilising signalling theory to frame a theoretical explanation of their efficacy.

This research builds on previous studies that have examined factors affecting crowdfunding success such as social networks, videos, images, the presence of spelling errors, the amount of funding targeted, and the number of backers supporting the campaign, as investigated by scholars (Y. Liu et al., 2024; Jiang et al., 2021; Šarić, 2021), as well as focusing on the broader determinants of crowdfunding success (Zribi, 2022; Cascino et al., 2019; Zhou et al., 2018). Liang and Hu (2018) and Liang et al, (2020) found that readability has a negative impact on crowdfunding success, although word count, picture count, video count, and updates had positive benefits. Adamska-Mieruszewska et al. (2024), along with P. D. Singh (2021), found that that the strategic use of language in the campaign’s brief and enhanced readability were linked to successful outcomes. Additionally, the experience of campaign creators has been shown to positively affect crowdfunding success (Jiang et al., 2021; Mamaro & Sibindi, 2022).

While numerous studies have explored the effect of project description length on crowdfunding success, most originate from developed nations and often focus on a single crowdfunding platform for data collection. However, there is a noticeable gap in research on the impact of project description length on crowdfunding success in African countries. This lack of representation is significant, given the unique socio-cultural dynamics of African crowdfunding environments. Therefore, this study’s investigation into the impact of word description on crowdfunding success in Africa is particularly noteworthy due to its contribution to this field.

In contrast to previous studies, it provides a specific understanding of the diverse linguistic and cultural environment of the area by delving extensively into the linguistic and cultural nuances of word choice and storytelling techniques unique to African crowdfunding campaigns (Anglin & Pidduck, 2022; Peng et al., 2022; Babayoff & Shehory, 2022). Given that entrepreneurs use crowdfunding as a platform for project marketing and a source of capital, this is a significant research gap.

The study analysed 854 crowdfunding initiatives from African nations to address the research goals, sourced from Kickstarter, Indiegogo, and other fundraising platforms. The analysis employed ordinary least squares (OLS) and logistic regression models. The study was guided by two research questions: (1) How does word description length influence crowdfunding success? (2) To what extent does the length of the description of the word influence the success of crowdfunding? The study drew on attribution theory by Heider (1958) and the persuasive communication model by Petty and Cacioppo (1986) to explore the motivations of crowdfunding backers and how they influence their decisions, ultimately affecting the success of crowdfunding campaigns.

The remainder of the paper is structured as follows: Section 2 outlines the literature review and formulation of the research hypothesis; Section 3 describes the research method and materials used; Section 4 discusses the findings; and Section 5 concludes the paper.

2. Literature Review

Entrepreneurs and would-be funders are divided by an information gap in crowdfunding. Project creators possess information on the feasibility and quality of their ideas, while backers have to rely on observable signals to make an educated guess on the credibility and likelihood of success. Signalling theory (Spence, 1973) is applicable in the explanation of the roles played by word description length, images, videos, spelling errors, and FAQs as uncertainty-reducing as well as trust-eliciting signals. Entrepreneurs communicate unobservable campaign attributes (competence, preparedness, and commitment) through campaign attributes which the backers interpret before supporting the projects.

Moreover, project attributes like the target amount and project duration also frame motivation as well as feasibility, which are dealt with in goal-setting theory (Locke & Latham, 1990). Project goals and the selected flexible funding model are also campaign features which are intended to signal feasibility as well as influence the backers’ readiness to support the projects. Lastly, the visual and narrative elements are crucial in shaping emotional involvement and attitudes toward the campaigns as suggested by the persuasion theory (Petty & Cacioppo, 1986). Length of description, video, and pictures offer central and peripheral cues to prospective donors and therefore influence their willingness to donate. All of these theories provide an explanation of the campaign design features and how they signal trust, perceived feasibility, and crowdfunding success.

Petty and Cacioppo (1986) developed the elaboration likelihood model (ELM) of persuasion, which offers a framework for understanding how entrepreneurs might use narratives to influence the attitudes of potential backers. Entrepreneurial narratives, such as those on crowdfunding platforms, contain contextual and relevant information for the venture’s attraction to investors (Allison et al., 2017). Several factors persuade potential backers, including videos, pictures, FAQs, and word description length (Yang et al., 2020).

Under the attribution theory, people examine internal versus external, stable versus unstable, and controllable versus uncontrolled factors when evaluating what led to successful and unsuccessful events or circumstances (Weiner, 1985). Attribution theory explains the success of crowdfunding, as people attribute their achievement of financing goals to external factors, like funding mechanism design and community support, and their hard work (C. H. Lee & Chiravuri, 2019). The length of the project description is used to overcome the issue of information asymmetry between project creators and backers.

2.1. Campaign Description Features

A well-written project description is a mark of diligence and reliability (Adamska-Mieruszewska et al., 2025; D. P. D. Singh & Poonawala, 2021). The empirical findings are inconclusive (Moy et al., 2018; Lasschuijt, 2019). Based on signalling theory (Spence, 1973), entrepreneurs can mitigate this asymmetry, signalling to potential backers with different knowledge levels. Research by Adamska-Mieruszewska et al. (2024), Moradi and Badrinarayanan (2021), and Liang and Hu, (2018) shows that a more extended project description correlates positively with crowdfunding success. The detailed description discloses information, conveying trustworthiness and credibility (D. P. D. Singh & Poonawala, 2021; M. Zhang et al., 2023; Zihagh et al., 2024; Jiang et al., 2021). In contrast, Moy et al. (2018) and Lasschuijt (2019) observed a negative link between the length of the description and the success of crowdfunding efforts. Consequently, the effect of the project description’s word count on the success of crowdfunding campaigns is not unanimously agreed on. Nevertheless, numerous empirical studies have demonstrated a positive impact of the description’s length on the likelihood of the campaign’s success. For backers, the extent of the description is a crucial indicator of the project’s thoroughness, aiding them in assessing its potential. This detailed description can act as a beacon of confidence, enhancing the probability that the campaign will succeed. The hypotheses are presented as follows:

H₁. 

The length of the word description in a project campaign is positively associated with crowdfunding success.

Spelling errors can signal a lack of preparation and incompetence, beating patron support trust (C. S. R. Chan et al., 2020; Mamaro & Sibindi, 2022). Mamaro and Sibindi (2022) and X. Zhang et al. (2023b) demonstrated that although readability indicators show the level of education needed to read campaign materials, the public perceives the number of spelling mistakes as a sign of errors. Spelling errors on a crowdfunding campaign page are often interpreted as a sign of unreliability, unpreparedness, and untrustworthiness (C. S. R. Chan et al., 2020). Thus, it is evident that spelling errors within a project’s description can influence fundraising campaigns, although their impact might be less pronounced compared to other textual features; in line with signalling theory, spelling errors can discourage investors from supporting the project idea. Thus, the hypothesis formulated is as follows:

H₂. 

The presence of spelling errors in a campaign description is associated with crowdfunding success.

2.2. Visual Features

Images convey quality and commitment by making campaigns more professional and emotionally appealing (Ma, 2023; Blanchard et al., 2022), irrespective of the scenario because other studies show mixed findings (Liang et al., 2020). From a signalling and persuasion point of view, attractive images diminish uncertainty and convince sponsors that the project is viable. Visual presentation on the crowdfunding campaign page is crucial in attracting many supporters. Ma (2023), Blanchard et al. (2022), and H. Li and Cao (2023) found that the availability of images on the crowdfunding website signals quality and hence, increases the likelihood of success. According to persuasion theory, crowdfunding and financing enable entrepreneurs to present their projects to possible investors and funders to persuade them of the viability of their business idea (X. Zhang et al., 2023a; Dey et al., 2023). On the contrary, Liang et al. (2020) found a negative association between images and crowdfunding success. Given the mixed results from research on the impact of images on crowdfunding campaigns, it is recognised that images can affect a campaign’s success by eliciting specific emotions (Hou et al., 2020). Appealing images indicate an initiator’s commitment to provide a superior reward. A higher number of quality images allows backers to understand the project’s primary goals and details more efficiently, especially the benefits offered. Hence, the third hypothesis is formulated as follows:

H₃. 

The existence of an image on the crowdfunding campaign is positively associated with crowdfunding success.

2.3. Structural and Funding Features

Funding arrangements are defined as risk and commitment sharing. All-or-nothing (fixed) signalling theory demands accountability to donors, which increases trust, whereas flexible funding will annihilate it (Predkiewicz & Kalinowska-Beszczyńska, 2021).

There is a shortage of literature on using fixed versus flexible funding mechanisms in this field, particularly in Africa. In the fixed funding mechanism, potential backers are refunded their contributions if the project does not reach the target (all-or-nothing approach). On the contrary, in the flexible funding model, the backers and investors do not get their money back, irrespective of whether or not the targeted amount has been reached (winner-takes-all-all). Bi et al. (2019) highlighted the advantages of both models, noting that flexible funding is preferred when the cost of pledging is low. However, flexible funding can negatively affect the likelihood of a project’s success (Predkiewicz & Kalinowska-Beszczyńska, 2021). As a result of inflated target numbers, the flexible fundraising mechanism destroys backers’ trust, which in turn lowers the campaign’s success rate. As a result, the flexible funding mechanism was found to have a detrimental impact on the success of crowdfunding. Hence, the fourth hypothesis is formulated as follows:

H₄. 

Flexible funding campaigns are negatively associated with crowdfunding success.

In line with the goal-setting theory, it is recommended that the project creator target an achievable amount. Goal-setting theory further contends that feasible and realistic goals activate support. Highly challenging goals can be perceived as overly demanding, and thus, the perceived feasibility decreases (Martínez-Gómez et al., 2020; Pinkow, 2023). A crucial aspect of a campaign’s overall success is how the goal amount affects crowdfunding success. According to studies, a crowdfunding project’s ability to succeed depends on choosing a target amount that is both acceptable and appealing to backers (Mamaro & Sibindi, 2023; Martínez-Gómez et al., 2020). The leading focus group also plays a vital role in drawing in a larger audience and generating excitement for the project, improving the chances of surpassing the funding goals. There, the targeted amount signals potential backers about the credibility and feasibility of the project (Pinkow, 2023). Thus, the research hypothesis is as follows.

H₅. 

A higher target amount is negatively associated with crowdfunding success.

Using the frequently asked questions section and its contributions regularly shows the public that the individual initiating the project is ready, willing, and able to increase transparency in the fundraising process (Shneor & Vik, 2020). Transparency mechanisms such as FAQs show that an organisation is willing and prepared to listen to stakeholder concerns (Shneor & Vik, 2020). It is vital to close information gaps; FAQs are positive indicators to backers. Using FAQs helps potential backers assess information to make an informed decision. The investigation does not explicitly address the relationship between the number of FAQ entries on a project site and the project’s success. However, several studies provide information on factors that may affect the success of a project (Song et al., 2019; Koch & Siering, 2019). Camilleri and Bresciani (2024) examine what is needed for project success and the elements that go into it, such as satisfying stakeholder demands and influencing them. There is a need for good communication and collaboration with project stakeholders (Awotunde et al., 2021). These studies highlight the significance of many project management techniques and criteria, even though they do not explicitly support the hypothesis that additional FAQ entries correlate with project success. Furthermore, backers can address frequent questions and problems more effectively through FAQs than individual conversations. We hypothesise:

H₆. 

The number of Frequently Asked Questions on the project site increases, and the probability of project success rises.

2.4. Backer Engagement and Campaign Dynamics

A greater number of fans is social proof and signifies popularity and trustworthiness (Shneor et al., 2020; St John et al., 2022).

Backers have a significant and diverse impact on the success of crowdfunding. In contrast to traditional investors, who are often driven by risk aversion and the possibility of profit, backers play an active and essential role in crowdfunding (St John et al., 2022). Developing trust among supporters is crucial to increasing the probability that a crowdfunding campaign will succeed. Research has indicated that trust is linked to the design of campaigns, the dynamics of their success, and the intent of individuals to contribute (Shneor et al., 2020). Considering that several studies show a positive relationship between backers and crowdfunding success, the following hypothesis is tested:

H₇. 

A large number of backers is positively associated with crowdfunding success, increasing the likelihood of crowdfunding success.

Length of campaign is an indicator of strategy. While a long length signifies stick-to-itiveness, excessively long campaigns signal ambiguity or an inability to catch an early momentum (Jáki et al., 2022). The length of time of a crowdfunding campaign, typically 30 and 90 days, is a crucial factor to consider, though the optimal duration remains contentious. The impact of duration on the success of crowdfunding is a complex and diverse subject, and the study has inconsistent findings. Comparable studies by Jáki et al. (2022), and Y. Liu et al. (2024) found a negative impact on crowdfunding success. While most believe that more extended campaign periods may negatively affect the project’s stability, others argue that crowdfunding has a compounding effect where initial contributions can spur further donations. The hypothesis is formulated as follows:

H₈. 

Longer durations are associated with crowdfunding success.

2.5. Conceptual Model

The theoretical model combines signalling, goal-setting, and persuasion theories. Independent variables (length of campaign description, spelling mistakes, pictures, funding option, target level, FAQ items, number of people backing, and time) are hypothesised as signals that determine the success of crowdfunding (the dependent variable).

Figure 1 below shows the conceptual model that relates theoretical foundations, campaign variables (independent variables), and successful crowdfunding (dependent variable).

3. Research Methods and Materials

The research methodology outlines the data collection approach and provides a detailed account of data collected from 54 African countries.

3.1. Dataset Description

The study gathered secondary data from Kickstarter, Indiegogo, and Fundraised, prominent reward-based crowdfunding platforms worldwide. The data included crowdfunding projects from the African continent, spanning January 2019 to December 2020. The 2019–2020 period is particularly important. It includes both pre-pandemic and pandemic conditions, offering insights into how campaign descriptions and visual features affected project success during a time of increased digital engagement and financial uncertainty. The dataset contained comprehensive details, including project description length (word count), spelling mistakes, image number, funding model (fixed or flexible), target amount, campaign length (in days), number of backers, and availability of FAQ entries. To refine the collected data, the researcher performed various preprocessing tasks mainly focused on eliminating duplicate entries and removing any incomplete or irrelevant data. Additionally, incomplete projects and those still in progress were excluded to reduce the possibility of errors. In the end, the study included 850 projects.

The original dataset had 1247 project records. The data cleaning and validation process that followed aimed at preserving accuracy and reliability: elimination of duplicates—efforts that showed up multiple times on platforms were distinguished depending on the campaign name, creator name, and launch date, and one was kept only; incomplete records—projects lacking the required variables (e.g., description, target funding or project length) were not included; active campaigns that were still ongoing when the data was extracted were excluded to prevent outcome measures bias; and lastly irrelevant cases—non-reward campaigns such as equity donations were excluded to make the specificity of the study consistent with reward-based crowdfunding. Figure 2 below illustrates the sampling process.

OLS is an estimate of the independent variable relationship with the continuous ratio of success (proportion of funds raised to target), while logistic regression is an estimate of the probability of binary campaign success (success or failure). Different dimensions of success are captured by the models, and different significance across variables may be a result of that. For instance, a variable can influence the level of funds raised (OLS) but not necessarily the probability of successfully raising the funding level (logistic). Section 3.2 presents the model estimation for ordinary least squares and the logit regression model.

3.2. Estimation Models

Model 1: Ordinary least squares (completion ratio)

The regression equation is given by:

$$\begin{gathered} Completionratio={\beta }_0+{\beta }_{1}Descriptionlength+{\beta }_{2}Spellingerror+ \\ {\beta }_{3}Image+{\beta }_{4}Flexiblefunding+{\beta }_{5}Targetedamount+ \\ {\beta }_{6}frequentlyaskedquestions+{\beta }_{7}Backers+{\beta }_{8}Duration+\epsilon \end{gathered}$$

(1)

Model 2: Logit regression (success)

The regression equation is given by:

$$\begin{gathered} Success={\beta }_0+{\beta }_{1}Descriptionlength+{\beta }_{2}Spellingerror+ \\ {\beta }_{3}Image+{\beta }_{4}Flexiblefunding+{\beta }_{5}Targetedamount+ \\ {\beta }_{6}frequentlyaskedquestions+{\beta }_{7}Backers+{\beta }_{8}Duration+\epsilon \end{gathered}$$

(2)

Variable measurement

• The dependent variable in question is determined by the percentage of the funding goal that has been met. The project is deemed successful if the rate is 100% or higher. The project is classified as unsuccessful if it is less than 100%. Alternatively, the dependent variable can be defined as success, measured by a binary indicator where 1 signifies a successful project, and 0 indicates an unsuccessful one.
• Dependent variable: The dependent variable is defined as success, evaluated using a binary system where 1 indicates a successful project, and 0 signifies an unsuccessful one.

Independent variables:

• The independent variables are word description length, spelling errors, images, flexible funding, videos, and duration.

  Table 1. The measurement of variables.

  Dependent Variables	Measurements
  Completion ratio (CR)	Ratio of the amount raised over the amount of money requested
  Success (SC)	The binary variable of 1 if the targeted amount was obtained and 0 otherwise
  Independent variables
  Description length (DL)	Total number of words written on the crowdfunding campaign (transformed into a log)
  Spelling errors (SPR)	A dummy variable of 1 if the spelling error is available on the campaign and 0 otherwise
  Image (IM)	A dummy variable of 1 if the image is available on the website and 0 otherwise
  Flexible funding (FXF)	A dummy variable of 1 if the crowdfunding campaign is flexible and 0 if it is a fixed funding model
  Frequently Asked Questions (FAQs)	The number of frequently asked questions on the crowdfunding platform (transformed as a log)
  Targeted amount (TA)	A binary variable of 1 if the target amount is achieved and 0 otherwise
  Backers (BCK)	The number of supporters who contributed to the project (transformed into a log)
  Duration (DRN)	The number of days for a campaign to raise funds (transformed into a log)

  Source: EViews output version 12.

  below explains all the variables.

4. Findings and Discussion of the Results

This section presents an analysis of the study’s findings, starting with an overview of the statistics followed by a correlation matrix and regression analysis to discuss the results in detail.

Table 2. Descriptive statistics.

Variables	Observation	Mean	Standard Deviation	Minimum	Maximum	Median	Kurtosis	Skewness
Completion ratio	850	0.161	0.735	0.000	14.585	0.000	215.66	12.588
Description length	850	572.19	550.18	0.000	5779.000	446.50	16.0082	2.5246
Spelling errors	850	0.282	0.4504	0.000	1.000	0.000	1.93510	0.9670
Image	850	0.6858	0.4644	0.000	1.000	1.000	1.64149	−0.8009
Flexible funding	850	0.7612	0.4266	0.000	1.000	1.000	2.50094	−1.2251
Targeted amount	850	4.0735	0.8037	1.699	7.477	4.000	3.67432	0.5179
Frequently asked questions	850	0.1000	0.9135	0.000	13.000	0.000	120.091	10.533
Backers	850	19.662	118.54	0.000	2438.00	0.000	234.548	13.604
Duration	850	44.530	17.242	2.000	67.000	46.00	1.94235	−0.4966
Success	850	0.0835	0.2768	0.000	1.000	0.000	10.0629	3.0104

Source: EViews output.

below presents descriptive statistics.

The average length of the project description is 572.19, with a standard deviation of 550.18, ranging from a minimum of 0 to a maximum of 5779.000 words. The data shows a high kurtosis of 16.0082, indicating a sharp peak and skewness of 2.5246, suggesting that, on average, 28.2% of projects contain spelling errors with a mean error rate of 0.282 and a standard deviation of 0.4504, ranging from 0.000, and the maximum is 1.000. The mean number of images is 0.6858, meaning 68.58% of projects include images with a standard deviation of 0.4644 and values ranging from 0.000 to 1.000. Moreover, the distribution has a positive kurtosis of 1.64149 and a negative skewness of −0.8009. For flexible funding, the mean is 0.7612, indicating that 76.12% of projects use this option with a standard deviation of 0.4266, ranging from 0.000 to 1.000. The median is 1.000, indicating that half of the projects offer flexible funding. The distribution has a positive kurtosis of 2.50094 and a negative skewness of −1.2251.

On average, the project funding target is 4.0735 (mean value) with a standard deviation of 0.8037, indicating variability in target amounts set by different projects. The targets range from a low of 1.699 to a high of 7.477, showing a slight tilt towards higher levels of positive kurtosis of 3.67432 and positive skewness of 0.5179. Regarding frequently asked questions, the average number in project descriptions is 0.1000 (mean value) with a standard deviation of 0.9135, ranging from 0.000 to 13.000. The distribution has a positive kurtosis of 120.091 and a skewness of 10.533. The mean number of backers per project is 19.662, showing a wide range between projects with no backers and those with up to 2438 backers. The positive kurtosis is 234.548, and the skewness is 13.604, indicating that most projects have a small number of backers, with a few exceptions having a large number. Lastly, the average campaign duration is 44.530 days (mean value), with a standard deviation of 17.242, ranging from 2 to 67 days. The kurtosis is 1.94235, suggesting a moderately peaked distribution and skewness of −0.4966, indicating a light preference for shorter campaign durations.

The correlation results are presented in

Table 3. Correlation matrix.

	CR	DL	SPR	IM	FXF	TA	FAQ	BCK	DRN	SC	VIF
CR	1.000										DP
DL	0.2252 ***	1.000									1.231
SPR	−0.0283	0.13148 ***	1.000								1.045
IM	0.099 ***	0.302 ***	0.1035 ***	1.000							1.115
FXF	−0.2098 ***	−0.184 ***	0.0934 *	−0.1056 ***	1.000						1.140
TA	−0.107 ***	0.153 ***	−0.0097	0.0507	0.080**	1.000					1.131
FAQ	0.151 ***	0.158 ***	−0.0258	0.074 **	−0.1955 ***	0.0195	1.000				1.083
BCK	0.422 ***	0.205 ***	−0.0467	0.026590	−0.1475 ***	0.0583 *	0.195 ***	1.000			1.102
DRN	−0.1027 **	0.002148	0.02072	0.041281	0.201 ***	0.29 ***	−0.0496	−0.113 ***	1.000		1.15
SC	0.6053 ***	0.208 ***	−0.057 *	0.122 ***	−0.2896 ***	−0.123 ***	0.246 ***	0.444 ***	−0.162 ***	1.000	DP

Notes: Standard errors in parentheses, * p < 0.1, ** p < 0.05, *** p < 0.01. Source: EViews output.

showing a low correlation between most independent variables. In Table 3 below, the length of the word description was transformed into a logarithm to normalise the final descriptive statistics before hypothesis testing. The correlation matrix was tested and provided a good benchmark of less than 0.70; therefore, there is no problem with multicollinearity (Doud, 2017). It suggests that no strong correlation exists between independent variables; hence, multicollinearity does not exist. Additionally, the study utilised the Variance Inflation Factor (VIF) test. VIF identifies the extent to which the variance of a regression coefficient is being inflated as a result of linear relationships among explanatory variables (O’brien, 2007). A common threshold suggests that centred VIF scores greater than 10 might be a sign of severe multicollinearity problems, but more stringent cut-offs (e.g., 5) are also recommended in the literature (Kalnins & Praitis Hill, 2025).

Table 4. Regression analysis.

Hypothesis Variables	OLS Regression (Completion Ratio)	Logistic Regression (Success)
H1: Description length (DL)	0.001 *** (0.04)	0.0005 (0.0004)
H2: Spelling errors (SPR)	−0.046 (0.051)	−0.772 (0.051)
H3: Image (IM)	0.0811 (0.051)	0.5957 (0.001)
H4: Flexible funding (FXF)	−0.173 *** (0.056)	−1.012 ** (0.462)
H5: Targeted amount (TA)	−0.134 *** (0.0293)	−2.841 *** (0.5159)
H6: Frequently asked questions (FAQs)	0.0272 (0.025)	0.0839 (0.188)
H7: Backers (BCK)	0.0023 *** (0.001)	0.0760 *** (0.009)
H8: Duration (DRN)	0.0001 (0.001)	0.0010 (0.0013)
C	0.6228 *** (0.126)	5.8782 *** (0.077)
Pseudo $R^2$ (McFadden)		0.6723
$R^2$	0.23862
DW test	2.03
Number of observations	849	849

Notes: Standard errors in parentheses, ** p < 0.05, *** p < 0.01. Source: EViews output.

presents the regression results for the OLS and logit models.

The regression models analysis—OLS regression using completion ratio as the dependent variable and logistic regression using success as the dependent variable—analysing the role of campaign description and visual element features in crowdfunding campaign success is justified. The OLS model produced an R² value of 0.2386, suggesting that 23.9 per cent of the variation in the completion ratio is explained by the independent variables: description length, spelling errors, an image, flexible funding, targeted amount, FAQs, number of backers, and campaign duration. While this is not a particularly strong result, the social sciences often work with much lower explanatory power due to the multitude of unobserved influences on behaviour (Hair et al., 2019). Also, the Durbin–Watson statistic (DW = 2.03) falls within the acceptable range of 1.5–2.5, suggesting that there is no serious autocorrelation in the residuals (Gujarati & Porter, 2009). This lack of explanatory power is somewhat balanced by the robustness of the results in the OLS regressions.

In contrast, the logistic regression model shows a McFadden’s pseudo-R² of 0.6723. This means that the model is a substantially better fit than the previous one. In logistic regression, values between 0.2 and 0.4 are generally considered indicative of an excellent fit (Louviere et al., 2000). Therefore, a pseudo-R² of 0.67 suggests the following:

• OLS regression results

Based on Hypothesis 1, the length of the word description would be associated with a higher project success rate, a higher total pledge amount, and a higher number of project backers. The data supports this hypothesis, showing a positive and significant relationship between the description length and the project’s success with a beta coefficient of β1 = 0.001 and a significance level of p < 0.01). This suggests that a detailed description can draw more potential backers to a campaign by describing the word on the crowdfunding page. Drawing from Spencer’s signalling theory (1973), a thorough word description mitigates the issue of information asymmetry by allowing entrepreneurs to guide less informed backers, the crowd. Studies by H. Li and Cao (2023), Ahlers et al. (2015), and Moy et al. (2018) support these findings, indicating that a more comprehensive description of a crowdfunding campaign is a critical factor in its success. Thus, the amount of detail provided in the campaign’s description helps backers and investors gain a clear understanding, enabling them to make well-informed decisions.

According to Hypothesis 2, we expected a negative association between spelling errors and crowdfunding success. The findings reported a negative effect on crowdfunding success (β2 = −0.046) but was insignificant. The findings suggest that spelling errors in a crowdfunding campaign indicate a lower likelihood of success. Such errors may convey a lack of trustworthiness to potential backers, deterring them from investing. Research conducted by Davies and Giovannetti (2018), T.-L. Yeh et al. (2019), and H. F. Chan et al. (2021) supports this conclusion, indicating that spelling errors are perceived as signs of low quality and lack of preparation, which negatively affect the campaign’s chance of success.

Hypothesis 3 anticipates that showcasing images in a crowdfunding campaign will positively influence its success. Although the positive impact on success is positive, with a beta coefficient of β2 = 0.0811, it is not statistically significant. Images convey a sense of readiness and reliability, which, in turn, encourages potential investors to support the crowdfunding campaign. According to Hootsuite (2020) and Ma and Palacios (2021), a visual display in a crowdfunding campaign can communicate more effectively than text alone, potentially enhancing a project’s success. Presenting images overcomes the problem of information asymmetry by providing backers with trustworthy information, as Bui and Bui (2022) and T. Liu et al. (2021) noted. It is, therefore, recommended that project creators include visuals on their crowdfunding pages to attract more potential investors.

Hypothesis 4 predicts a negative correlation between the use of flexible funding options and the success of crowdfunding campaigns. The data reveals that flexible funding significantly negatively impacts crowdfunding success with a beta coefficient of β4 = −0.173 and a significance level of p < 0.01. This suggests that campaigns with flexible funding are less likely to be successful than those with fixed funding models. This aligns with the signalling theory, which posits that flexible funding may signal a lack of confidence in the backers (Bi et al., 2019). Therefore, fixed funding models, which operate on an all-or-nothing basis, are preferred.

Hypothesis 5 suggests an inverse relationship between the funding target and the crowdfunding campaign’s success. The campaign indicates a significant negative correlation with a beta coefficient of β5 = −0.134 and a significance level of p < 0.01. This implies that a high funding goal can deter potential backers from contributing. This finding is particularly pertinent in scenarios involving regular interaction with investors, where setting realistic funding goals and a suitable funding duration is crucial (Zhou et al., 2018). The goal-setting theory proposes that while ambitious funding targets may expand the project’s scope, modest targets could lead to better resale outcomes and less fluctuation in pricing (Xu & Ni, 2022). Therefore, setting a realistic target to avoid a failed crowdfunding campaign is advisable.

According to Hypothesis 6, we anticipated that there would be a beneficial link between the presence of a frequently asked questions (FAQ) section and the success of crowdfunding campaigns. The analysis showed a positive influence of frequently asked questions on crowdfunding success, as indicated by a beta coefficient of β5 = 0.0272, although this was not statistically significant. Furthermore, frequently asked questions on the crowdfunding campaign page will likely enhance the probability of success. According to asymmetry theory, frequently asked questions help clarify doubts and reduce misunderstandings. By addressing common queries, entrepreneurs can effectively fill the gaps, potentially boosting crowdfunding success.

Hypothesis 7 posits that more backers increase the likelihood of a crowdfunding campaign’s success. The research confirmed these hypotheses, demonstrating a statistically significant positive correlation between backers and the success of a crowdfunding campaign with a beta coefficient of β6 = 0.0023 and a significance level of p < 0.01. Essentially, campaigns with more supporters are more likely to succeed. The findings are consistent with principles of attribution and signalling theories, which suggest that the motivations of a large supporter base positively influence a campaign’s outcome. It is essential to attract a substantial number of potential backers for the success of the crowdfunding initiative.

Hypothesis 8 anticipated that a more protracted campaign duration would negatively affect crowdfunding success. However, the data indicated a positive, albeit statistically insignificant, relationship between campaign duration and success, with a beta coefficient of β7 = 0.0023. This suggests that campaigns extending over more days may have a higher chance of success. Therefore, the campaign’s length plays a significant role in its success, with an optimal duration being crucial for achieving the best funding outcomes, as supported by the research of Sal Jin et al. (2020), and dos Santos Felipe et al. (2022).

• Logistic regression results

Hypothesis 1 suggests that a detailed description of a crowdfunding campaign’s page positively correlates with its success—the campaigns. The findings in Table 4 show a positive link; the association is not statistically significant, with a beta coefficient of β1 = 0.0005. This is in line with the findings of Moy et al. (2018) and Zhou et al. (2018), who found that a comprehensive description of the crowdfunding campaign page can lessen the problem of information asymmetry. Therefore, providing a brief yet informative description of the crowdfunding campaign page is essential. Hypothesis 2 predicted that spelling errors would negatively affect crowdfunding success. The findings indicated a negative impact, as spelling errors on the campaign page seem to reduce the chances of crowdfunding success; this was not statistically significant, with a beta coefficient of β2 = −0.772. This implies that project creators should be meticulous in avoiding spelling errors to minimise the risk of a failed campaign. Hypothesis 3 expected a positive relationship between the use of images and crowdfunding success. The findings supported the null hypothesis, indicating no significant impact with a beta coefficient of β3 = 0.5957. However, images on the campaign page are believed to enhance success. Hence, entrepreneurs need to include pictures to attract more backers.

Hypothesis 4 predicted that flexible funding options would be detrimental to crowdfunding success. The results confirmed this prediction, finding a significant negative correlation between flexible funding and crowdfunding success with a beta coefficient of β4 = −1.012 and a significance level of p < 0.05. This supports the theories of signalling and information asymmetry, favouring a fixed funding approach over a flexible one. A negative relationship was expected between flexible funding and crowdfunding success. The results reported a negative and significant relationship between flexible funding and crowdfunding success (β4 = −1.012; p < 0.05). Consistent with signalling and information asymmetry theories, a fixed funding mechanism is preferred over flexible funding.

In Hypothesis 5, a negative relationship between the targeted amount and the success of the crowdfunding was expected. The study results reported a negative association between the target amount and the success of the crowdfunding (β5 = −2.841; p < 0.01). Therefore, the null hypothesis was not rejected, which implies that a higher targeted amount discourages potential backers from supporting the crowdfunding campaign. The research findings conform to the signalling theory and are consistent with studies by Pinkow (2023), Mamaro and Sibindi (2023), and T. Liu et al. (2021). Hypothesis 6 anticipated a positive effect of frequently asked questions on crowdfunding success. The results revealed a positive but not statistically significant relationship with a beta coefficient of β5 = 0.0839. This means that the study did not find enough evidence to reject the null hypothesis, suggesting that FAQs might increase the likelihood of success. These results are consistent with information asymmetry and signalling theories, which argue that FAQs can enhance a campaign’s credibility and trustworthiness, as noted by Lu et al. (2024), J.-Y. Yeh and Chen (2022).

Hypothesis 7 proposed that more backers would correlate with more tremendous crowdfunding success. The results confirmed a positive and highly significant impact on crowdfunding with a beta coefficient of β5 = 0.0760 and a significance level of p < 0.01. According to signalling theory, a more extensive base of backers significantly boosts the likelihood of a campaign’s success (Ma, 2023; Herd et al., 2022; Efrat et al., 2020). Contrary to Hypothesis 8, which anticipated a negative impact of longer campaign durations on success, the study found a positive but not statistically significant relationship. This led to the rejection of the null hypothesis, suggesting that campaigns with extended durations provide a longer window for the results, which is supported by Pan and Dong (2023), Lagazio and Querci (2018), and Dikaputra et al. (2019). However, this does not align with the findings of Jáki et al. (2022) and Regner and Crosetto (2021).

5. Conclusions

The study makes several contributions as follows.

5.1. Management Implications

For campaign designers and operators of crowdfunding platforms in Africa, the findings hold considerable relevance. H1 and H3, the positive and significant effects of description length and image use, respectively, demonstrate that the visual elements and richer narratives greatly enhance the likelihood of campaign success. This means that managers should encourage entrepreneurs to use striking visuals and detailed, error-free descriptions. On the other hand, H5 and H4’s negative and significant effects of target amount and flexible funding models suggest that unreasonably high targets, alongside flexible funding, hurt credibility. This has been noted in earlier work (G. Li & Wang, 2019; Wessel et al., 2019). For campaigners, this emphasises the need to set realistic targets along with precise funding models.

The insights from this study can benefit both platform owners and entrepreneurs. Platform owners can use this analysis to advise entrepreneurs on their campaign strategies. This study also expands existing knowledge by focusing on the impact of word description length on crowdfunding success in Africa, as previous research was largely limited to developed countries (Adamska-Mieruszewska et al., 2025; Moradi & Badrinarayanan, 2021; Liang & Hu, 2018). Additionally, our study utilised cross-country data from multiple crowdfunding platforms, broadening the scope compared to previous studies that were confined to a single platform (Liang et al., 2020; Peng et al., 2022; dos Santos Felipe et al., 2022).

5.2. Practical Implications

On a more practical level, the findings emphasise engaging metrics to be controlled and monitored by campaign designers. Since the number of backers (H7) has a significant positive relation with both the completion ratio and overall success of the campaign, strategies to engage backers early in the cycle, like rallying their personal circles, are vital. H2 and H8’s findings regarding the significance of spelling errors and duration, in the African context, are striking. They stand in stark contrast to Mollick’s (2018) research, which found that linguistic quality correlated with the success rate of crowdfunding campaigns.

5.3. Theoretical Implications

The study advances crowdfunding theory in three ways:

• It extends signalling theory (Spence, 1973) into the African context, showing that not all signals (e.g., spelling or FAQs) are equally valued across cultural or institutional settings. Instead, visual and quantitative signals (images, backers, and achievable targets) carry more weight.
• The negative effect of flexible funding challenges the assumption (common in Western studies) that flexibility attracts more participation (Steigenberger, 2017). In Africa, rigidity may be interpreted as commitment, reinforcing the credibility of the entrepreneur.
• The study uses multiple campaign-related variables simultaneously through OLS and logistic regression, and the study empirically demonstrates that determinants of success ratio and binary success can differ, adding nuance to crowdfunding performance measurement.

5.4. Empirical Implications

Empirically, the study is original in that it uses a large dataset (N = 849) from Africa, a region underrepresented in crowdfunding scholarship (Shneor et al., 2020). The robustness of the results across OLS (R² = 0.2386) and logistic regression (Pseudo R² = 0.6723) highlights the consistency in the findings, particularly the strength of images, backers, and funding models. This provides a reliable evidence base for future comparative studies. Additionally, the insignificant results for FAQs and duration suggest that contextual contingencies—what matters in one ecosystem (e.g., the U.S. or Europe)—may not be as critical in Africa, thereby inviting further cross-regional empirical investigations.

5.5. Limitations and Suggestions for Future Research

However, our research has certain limitations that could pave the way for future investigations. Specifically, we only focused on rewards-based crowdfunding platforms and did not consider other investment-based methods like lending and equity crowdfunding. This means that the findings might not be universally applicable. Furthermore, our study was limited to crowdfunding projects in 54 African countries, so the results may not directly apply to developed nations. Therefore, future research could explore data from other crowdfunding platforms, especially those using investment-based methods, and compare various factors influencing crowdfunding success.

Overall, this study is original in situating crowdfunding success factors within Africa, providing new insights into how campaign descriptions and visual features operate in this context. Its managerial implications help entrepreneurs and platforms design more effective campaigns; its practical insights guide day-to-day decision making; its theoretical contributions extend signalling theory and challenge Western-centric assumptions; and its empirical strength lies in providing much-needed evidence from an African sample. By doing so, the research makes a multi-dimensional contribution to both academia and practice, while opening doors for future comparative and longitudinal studies.