Evaluating the Impact and Perception of Influencer Marketing Among Romanian Consumers—Insights from Quantitative Research

Abstract

Currently, one of the most widely used marketing techniques is influencer marketing, but is its true impact on Romanians truly understood? This article aims to establish the perception of influencer marketing activities by Romanian consumers. A quantitative study was conducted, gathering 618 responses through an online questionnaire. It was found that 92% of the respondents made at least one purchase based on content creator recommendations, with Instagram being perceived as the most impactful platform for such campaigns. However, the success of these campaigns relies on several strategic elements. These include selecting content creators who align with the product or service being promoted and ensuring that the influencer’s audience demographics match the target audience. Companies must also prioritize transparency and the seamless integration of products into influencers’ daily lives, as well as considering factors like content type, the frequency of posts, and budget. The results indicate that well-structured influencer partnerships, particularly on Instagram, enhance consumer trust and enhance marketing impact. These insights offer valuable guidance for developing effective digital marketing strategies emphasizing to specific business needs.

1. Introduction

The behavior of consumers has changed significantly due to technological innovation and the ubiquitous adoption of wearable devices, directly contributing to how people interact and use social platforms to make decisions and shop online. The increasing use of digital marketing and social networks has positively influenced consumers’ attitudes toward online shopping, with a growing market share for e-commerce-focused organizations (Sarwar-A Alam et al. 2019).

The widespread utilization of social media platforms in contemporary times has resulted in a notable surge in individuals employing these channels for the acquisition of information conducive to informed purchasing decisions. The perspectives of both subject matter experts and non-specialists, colloquially termed as amateurs, have become increasingly sought after. This inclination arises from the perceived sincerity inherent in these viewpoints, readily accessible across diverse social media platforms (Hu et al. 2020; Jacobson et al. 2020). Hence, the inclination of individuals to peruse diverse reviews and numerous earnest feedback in the online milieu has motivated certain individuals to articulate their opinions via social networks in a professional capacity (Audrezet et al. 2020). These individuals, referred to as “influencers”, represent third parties and independent actors distinguished by their capacity to systematically influence the attitudes of their audiences within the realm of social media (Belanche et al. 2021).

The aim of this article is to elucidate how consumers perceive the activities of influencers and, more importantly, their attitudes toward influencer marketing campaigns conducted across various social media platforms. The research findings are extremely valuable as they can serve as a foundation for future marketing strategies. Collaborative campaigns with content creators are becoming increasingly prevalent, highlighting the relevance and utility of the subject matter. The research was conducted to obtain responses to the following inquiries:

• To what extent do users of social media platforms place trust in the recommendations put forth by content creators?
• What are the determinants influencing the credibility of an influencer marketing campaign?
• How frequently do respondents engage in the purchase of products advocated by influencers?
• On which social media platforms do influencer marketing campaigns exhibit a more pronounced impact?
• What constituent elements of an influencer marketing campaign have induced respondents to discontinue following specific content creators on social media platforms?

The present work is structured into six sections, commencing with the introduction, followed by the literature review in the Section 2, while the methodology is expounded within Section 3. The results of the quantitative research are outlined in the Section 4 and elaborated upon in Section 5. The article concludes with sections on conclusions, managerial and academic implications, limitations, and future research directions.

2. Literature Review

Social media networks represent an opportunity for entrepreneurs to achieve fast, cost-effective, and direct communication with target markets (Pakura and Rudeloff 2023). They can be used in marketing strategies to create commitment and represent an “intangible benefit related to marketing communication objectives” (Rosário and Dias 2023). Advertisements disseminated on social networks are defined as “any promotional content published through social media platforms to reach customers” (Adetunji et al. 2018). Therefore, advertisements conducted on platforms such as Facebook, Twitter, Instagram, and YouTube are referred to as social media advertisements (Taylor et al. 2011). Companies are using social networks to achieve additional value for companies and their brands (Okazaki and Taylor 2013; Wang et al. 2021), strengthening their brand image and enhancing consumer feedback (Khaleeli 2020).

Through social networks, companies can communicate both product information and details about future events, campaigns, or contests. Social media platforms have a significant impact on online sales. According to Suprapto et al. (2020), companies with online stores could increase sales and market share through promotion on social media platforms. Dabbous and Barakat (2020) highlighted how the quality of content provided on social networks strongly influences brand awareness and serves to mediate consumers’ purchase intent.

With the advent of new technologies and the widespread use of social media tools, promotional activities have become increasingly effective. Among the most prevalent are visual elements, as these tend to imprint more strongly in the minds of consumers, facilitating a more seamless association of the visual image with the brand. According to a study conducted by Aytan and Telci (2014) marketing activities carried out by a company through the medium of social media platforms yield significant results, exerting a strong impact on brand image. Similar conclusions were drawn by Saydan and Dülek (2019) in their research, stating that “advertising practices on social media platforms of brands have been an effective factor in establishing brand awareness”.

Among the most widely utilized social networks are Facebook, Instagram (a photo-sharing application), Snapchat (an instant photo messaging application), Twitter (a microblogging platform), LinkedIn (a career and business-oriented social networking service), and Pinterest (a “catalog of ideas” or a photo-sharing website). All the aforementioned social platforms have different features (Van Dijck 2013; Vandenbosch et al. 2022).

The COVID-19 pandemic period has led to the growth of digitization in marketing strategies as well, with many companies turning more and more to influencers in their marketing strategies (Khurshid et al. 2024) or even micro-influencers with greater influence (Gerlich 2022) or a new type of influencer: the virtual influencer (Gerlich 2023). Even if the importance of digital marketing is recognized, consumers’ skepticism towards these potential techniques is noted, with researchers highlighting realism and trust as particularly important (Gökerik 2024). Studies show that there are fraudulent influencers who can become very credible and misinform consumers (Bahar and Hasan 2024), and there are four motivations for following influencers on Instagram, with each one having effects on trust and buying: “authenticity, consumerism, creative inspiration, and envy” (Lee et al. 2022).

According to a survey conducted by datareportal.com in January 2023, there were 17.82 million internet users in Romania, representing 88.9% of the total population. A total of 13.50 million individuals were users of social networks, accounting for 67.3% of the overall population. As per Meta’s data at the beginning of 2023, Facebook had 9.55 million users in Romania, while Instagram had 4.90 million. During the same period, TikTok had 7.58 million users aged 18 and above in Romania, according to ByteDance. Other social media platforms used by Romanians at the beginning of 2023 include LinkedIn (3.6 million), Youtube (13.50 million), Snapchat (2.55 million), Twitter (1.25 million), and Pinterest (2.01 million) (DATAREPORTAL 2023).

Influencer marketing has existed for decades and, until recently, involved engaging individuals with significant social impact (such as journalists with well-regarded restaurant columns or celebrities) to authentically advertise products. However, the advent of social media networks has profoundly altered the way marketing information is employed to promote products and to stimulate, shape, or generate new consumer demand (Goanta and Ranchordás 2020).

Influencers have been characterized as individuals perceived to be situated somewhere between friends and celebrities. Much like friends sharing common interests, values, and lifestyles on their Instagram accounts, using a common language, influencers disseminate information and advice to their followers on specific topics of mutual interest, aiming to establish enduring relationships (Jin and Ryu 2020). The career of influencers is cultivated on social networks, where they build and sustain direct relationships with numerous users with the purpose of informing, entertaining, and potentially influencing their thoughts, attitudes, and behaviors, especially in terms of purchasing behaviors (Dhanesh and Duthler 2019).

3. Materials and Methods

This quantitative research was grounded in two qualitative studies conducted among experts and consumers, respectively. A focus group study was conducted among Romanian consumers, and a series of individual interviews were carried out among influencers in Romania. The findings from these two qualitative investigations yielded information that served as the foundation for the objectives and hypotheses formulated in the present study.

To conduct the quantitative research providing answers to the five questions formulated in Section 1, a survey-type questionnaire was employed, as it offers the advantage of formulating highly diverse questions that aid in gaining insights into various aspects of the studied population (Lefter et al. 2006; Murphy 2023). The data collection instrument is a questionnaire, administered in an online environment. The questionnaire comprises 29 questions (Appendix A), which are based on the information obtained from the analysis of the results of the two qualitative studies conducted earlier, as well as the questions posed by the researcher in the initial phase of the research. The questionnaire was pretested beforehand, and minor modifications were subsequently made regarding the wording of the questions. This process was conducted to ensure that all questions were correctly understood, to ensure that the terms used were familiar to the Romanian respondents, to assess the time required to complete the questionnaire, and to identify any potential issues that may arise. Pre-testing is a specific step in the questionnaire development process.

The questionnaire was formulated based on the objectives set by the researchers:

(O1) Assessing the level of trust that subjects place in recommendations from social media content creators;

(O2) Determining the factors influencing the credibility and authenticity of influencer marketing campaigns;

(O3) Identifying the frequency with which Romanians purchase products recommended by content creators in the online environment;

(O4) Identifying the social media platform where influencer marketing campaigns have the greatest impact on users;

(O5) Understanding the elements within influencer marketing campaigns that may lead Romanians to cease following a content creator online.

Numerous phenomena related to the researched topic in this study can be elucidated through research hypotheses. These were defined by researchers in the initial phase of the process, with statistical hypotheses subsequently tested and either validated or rejected, while general hypotheses can be affirmed or negated based on the analysis of the collected data.

Hypothesis 1 (H₁):

A majority of respondents believe that the authenticity and credibility of influencer marketing campaigns are influenced by how content creators incorporate products into their daily lives. Furthermore, it is crucial for there to be alignment between the product and their field of activity.

Hypothesis 2 (H₂):

The percentage of Romanians who have made at least one purchase based on an influencer’s recommendation is different from 60%.

Hypothesis 3 (H₃):

There is no correlation between the agreement level with the statement “I believe that influencers’ suggestions help me make purchasing decisions” and the respondents’ background.

Hypothesis 4 (H₄):

The social media platform where influencer marketing campaigns have the greatest impact on subjects is Instagram.

Hypothesis 5 (H₅):

The reason the majority of Romanians have stopped following a specific influencer is that the influencer conducted a marketing campaign for a product not aligned with their field of activity.

The studied population comprises individuals aged 18 and above from Romania who have an account on at least one social media platform and are familiar with the term “influencer marketing”. According to data published in August 2023 on the website of the National Institute of Statistics, the population of Romania aged 18 and above as of 1 January 2023 was 19051562 individuals (INSSE 2024), with minors numbering 3820097 individuals (UNICEF 2023).

In March 2023, there were 12.243 million Facebook users in Romania (STATISTA 2023). According to figures published by Meta, Instagram had 4.90 million users in Romania at the beginning of 2023, with the company’s recently revised figures suggesting that the coverage of Instagram advertisements in Romania equated to 24.4% of the total population at the beginning of the year (DATAREPORTAL 2023).

To determine the sample size, a 95% confidence interval was considered, with a precision level of estimation (permissible error), α, set at ±5%. The coefficient z was identified as 1.96, as obtained from the normal distribution table for a 95% confidence interval and a ±5% error (α = 0.05).

Therefore, the sample size “n” was calculated as follows:

$$\mathrm{n}={\displaystyle \frac{{\mathrm{z}}^2\times \mathrm{p} \times \mathrm{q}}{{\mathrm{E}}^2}},$$

where:

• E = permissible error (%);
• z = the value from the distribution table for α = 0.05, i.e., 1.96;
• p = the estimation of the percentage in case of success;
• q = 1 − p, the estimation of the percentage in case of failure;

“p” and “q” are unknown, and the authors considered the maximum level they could attain;

• p = 50%;
• q = 50%;
• z = 1.96;
• E = ±3%.

Thus, the following was obtained:

$$\mathrm{n}={\displaystyle \frac{{1.96}^2\times 50\times 50}{3^2}}=1067$$

The sample size (n) is 1067 subjects; however, due to time and material constraints, a sample of 618 individuals was obtained.

In this situation, the error was calculated as follows:

$$\mathrm{E}=\sqrt{{\displaystyle \frac{{\mathrm{z}}^2\times \mathrm{p}\times \mathrm{q}}{\mathrm{n}}}}=\sqrt{{\displaystyle \frac{{1.96}^2\times 50\times 50}{618}}}=\sqrt{{\displaystyle \frac{9604}{618}}}=\sqrt{15.54}=3.942\%$$

The accepted error level for the sample size of 618 individuals was 3.942%.

In this research, a non-random sampling method was employed, with sample selection and data collection conducted through the internet. The questionnaire was distributed for completion through social media platforms such as Facebook and Instagram, networks that allowed for the identification of communities consisting of individuals representing the research’s target audience. Simultaneously, a snowball sampling approach, also known as the snowball method, was employed. This technique involves requesting individuals to recommend others they know to participate in the research, rather than selecting them randomly. As a result, participants in the study enlist future subjects from their network of friends and acquaintances (Hossan et al. 2023).

Adults who completed the questionnaire further distributed it to others. Among these individuals were content creators who contributed to the questionnaire’s dissemination in the online environment.

Data collection took place over a period of five weeks, commencing on 21 August 2023. The Google Forms platform facilitated data collection, as well as the download of the database containing all 618 responses. From the total of 618 completed questionnaires, after the initial filter question, 568 subjects remained eligible to complete the survey. Following question number 3, an additional 48 respondents were redirected to the section containing demographic questions.

The final section of the questionnaire comprises demographic questions, which will be subsequently analyzed. The first question pertains to the identification of respondents’ gender. In Figure 1, the percentage of individuals identifying as female is evident, accounting for 64.26% of the 568 sampled participants, specifically 365 women, while males constitute 203 individuals, representing 35.74% of the sample.

The second question aims to identify the sample’s structure based on age categories. Thus, in Figure 2, delineations can be made from the total of 568 respondents: 286 individuals aged between 18 and 29 years (constituting 50.35% of the total sample), 198 persons aged between 30 and 39 years (representing 34.87% of the overall subjects), and 56 individuals aged between 40 and 49 years (amounting to 9.88% of the total respondents). Additionally, 2.80% of the questionnaire’s total members fall within the 50–59 age range, numbering 16 individuals, while 2.10% of the sample (12 subjects) are individuals aged over 60 years (including 60).

Of the total 568 members of the sample, 26.76% originate from rural areas (152 individuals), while the remaining 73.24%, comprising 416 subjects, are drawn from urban environments.

Based on the participants’ latest completed level of education, this study categorizes individuals as follows: 18 individuals who have completed primary school (3.17%), 6 subjects with either 10 years of education or vocational school completion (1.06%), 92 respondents who are high school graduates (16.20%), and 10 members of the sample (1.76%) who have completed post-high school education. The highest percentage of respondents holds advanced degrees; specifically, 40.14% of the total respondents (228) have completed master’s-level education. A total of 208 respondents, representing 36.62% of all subjects, have completed undergraduate studies. Only 6 individuals (1.06%) possess doctoral degrees among the total of 568 study participants.

The final question within the demographic category pertains to the monthly net income of the sampled individuals. According to Figure 3, 62 individuals (10.92%) out of the total 568 have no income, 20 subjects (3.52%) earn monthly net incomes below RON 1000, and 22 individuals (3.87%) have monthly net incomes between RON 1000.01 and 2000. Within the income range of RON 2000.01–3000, 62 respondents fall, constituting 10.92% of the total sample, followed by 84 individuals (14.79%) falling within the RON 3000.01–4000 income interval. A total of 88 individuals, members of the sample, have a monthly net income ranging between RON 4000.01 and 5000, representing 15.49% of the total respondents, while 40.49% of all study participants (230 individuals) report monthly net incomes exceeding RON 5000.

4. Results

This section presents a brief overview of the results obtained through the analysis of primary data, as well as the testing of statistical hypotheses. The analysis was conducted using Excel and IBM SPSS Statistics 26.

A portion of content creators’ activity focuses on promoting various goods; therefore, this research aimed to identify the extent to which respondents trust product recommendations made by the influencers they follow on social media platforms. Of the 520 respondents, 258, precisely 49.62%, provided a neutral response, opting for the “Neither distrust nor trust” option. Meanwhile, 36.96% of subjects trust the recommendations of content creators, while the “Distrust” response was chosen by 40 individuals (7.69% of valid responses). The least common responses were attributed to the options of “A lot of trust” (5.38%) and “Total distrust” (0.38%) (Figure 4).

The indicators of descriptive statistics corresponding to this question are presented in

Table 1. Indicators of descriptive statistics.

What level of trust do you have in the product recommendations made by the influencers you follow?	N		Mean	Median	Mode	Std. Deviation
	Valid	Missing
	520	98	3.39	3.00	3	0.724

Source: Created by authors based on the SPSS output.

. Thus, the respondents’ average ratings regarding the level of trust in the recommendations made by the influencers they follow on social media are 3.39 points on a scale from 1 to 5 (1—complete distrust; 5—complete trust). The median and mode each have a value of 3, with the response option “Neither distrust nor trust” being most frequently selected by the sample members. The standard deviation is 0.724 points, indicating a high homogeneity of the population regarding the analyzed variable as it is below 1 point.

In order to better identify the factors contributing to the increased credibility of influencer marketing campaigns, the authors included the following question in the questionnaire: “For you, does the number of followers of a content creator influence the credibility of the marketing campaigns they undertake?”

The responses to this question are presented in Figure 5, where it can be observed that, for 61.90% of the 520 respondents, the number of followers a content creator has does not influence the credibility of the marketing campaigns they are part of. The remaining 38.10% believe that this aspect does influence the credibility of influencer marketing campaigns.

The following figure (Figure 6) presents the types of campaigns that inspire trust among the respondents. Specifically, 358 individuals believe that the most credible campaigns are those created on social media, where the influencer seamlessly integrates the promoted product into their daily activities. The next type of campaigns that instill trust for 54.60% of respondents are those carried out on social networks featuring content creators followed by the subjects online. A total of 162 respondents, representing 31.2% of the subjects, perceive the disclosure of paid partnerships in social media campaigns as credible. The least credible promotion techniques for the sampled members are television commercials featuring influencers (6.9%) and campaigns conducted on social platforms by influencers, regardless of whether they are among the individuals followed by respondents (5%).

Often, content creators convey information about various products or brands. Sometimes, these types of posts prompt internet users to make purchases. Consequently, the researchers aimed to identify the number of individuals who have bought a product at least once because it was recommended by an influencer on social media. As seen in the graph below (Figure 7), 476 people, or 92% of respondents, have made a purchase at least once based on information provided by a content creator on social media. Only 8% of subjects have never made a purchase considering online opinion leaders.

The perception of consumers regarding the impact of a content creator campaign also depends on the platform on which it is conducted. Respondents were asked to rank social media platforms in ascending order, assigning rank 1 to the platform with the highest impact campaigns, rank 2 to the second-highest impact, and so on, up to rank 5 for the platform with the least impact. Since an ordinal scale was used—specifically, the ranking scale of response alternatives in relation to a specific criterium—the average score was calculated for each platform. Due to this type of scale, the lowest score represents the first place, indicating that the platform where influencer marketing campaigns have the greatest impact is Instagram, with an average score of 1.61 points (Figure 8). In the second place is TikTok with an average score of 2.52 points, followed by Facebook (2.98 points), YouTube (3.43 points), and lastly, Snapchat (4.46 points), indicating that influencer marketing activities on this platform have the least impact.

Another relevant aspect for the research is represented by the various reasons that led people to stop following certain influencers online. For this, the questionnaire included a dichotomous nominal scale question: “Have you stopped following a particular influencer because of the campaigns they conducted online?”. As can be seen in Figure 9, out of a total of 520 respondents, 66% have stopped following certain influencers on social media because of the campaigns they have carried out. The remaining 34% of subjects answered negatively to this question.

The exact reasons why 344 members of the sample removed various influencers from their list are presented in Figure 10. Aggressive campaigns and the lack of consistency between the promoted product and the influencer’s activity are the most frequently mentioned causes, both chosen by 154 individuals, representing 44.80% of the 344 respondents. For 38.40% of the subjects, the product promoted by the influencer led to their removal from the following list. Additionally, the brand with which the content creator collaborated for the marketing campaign was a reason to stop following the influencer for 23.30% of those who completed the questionnaire. Sponsored campaigns were mentioned by 11% of study participants, and 8.70% of the 344 respondents cited other reasons, including the influencer’s insincerity, running multiple campaigns with brands in the same sphere, promoting very different products, and focusing more on promotions than on the influencer’s life.

Statistical hypothesis testing is carried out with the aim of extrapolating results from the sample level to the level of the researched population. Therefore, a series of statistical tests will be applied to the hypotheses, aiming to identify statistically significant differences in various parameters, differences that may exist between two or more groups within the population, or even connections and relationships between variables (

Table 2. Descriptive statistics indicators at the sample level.

One-Sample Statistics
	N	Mean	Std. Deviation	Std. Error Mean
Acquisition based on the endorsement of an influencer.	520	0.92	0.279	0.012

Source: Created by authors based on the SPSS output.

and

Table 3. Student’s t-test for verifying Hypothesis 2.

One-Sample Test
	Test Value = 0.6
	t	df	Sig. (2-Tailed)	Mean Difference	95% Confidence Interval of the Difference
					Lower	Upper
Acquisition based on the recommendation of an influencer	25.817	519	0.000	0.315	0.29	0.34

Source: Created by authors based on the SPSS output.

).

Hypothesis 2 (H₂).

The percentage of Romanians who have made at least one purchase based on an influencer’s recommendation is different from 60%.

At the level of the 520 respondents, the mean of the binary characteristic is 0.92, indicating that 92% of the respondents have made at least one acquisition based on the recommendation of an influencer. The standard deviation is 0.28 (28%).

The hypothesis was tested using Student’s t-test, and the results are presented in Table 3.

It can be observed that the calculated t-value is 25.817, which is greater than the theoretical t-value of 1.96, thereby accepting H2. Under these conditions, we can ensure with 95% probability that at the population level under investigation, the percentage of individuals who have made at least one purchase based on the recommendation of a content creator is different from 60%.

The second statistical hypothesis to be tested is as follows. By using absolute and relative frequencies, contingency table was generated (

Table 4. Contingency table based on absolute and relative frequencies.

I Believe That Influencer Recommendations Assist Me in Making Purchasing Decisions Place of Origin Crosstabulation
			Place of Origin		Total
			Rural	Urban
“I am of the opinion that influencer recommendations assist me in making purchasing decisions”	Complete disagreement	Count	8	16	24
		% within place of origin	6.2%	4.1%	4.6%
	Disagreement	Count	12	36	48
		% within place of origin	9.2%	9.2%	9.2%
	Neither agreement nor disagreement	Count	44	128	172
		% within place of origin	33.8%	32.8%	33.1%
	Agreement	Count	44	158	202
		% within place of origin	33.8%	40.5%	38.8%
	Complete agreement	Count	22	52	74
		% within place of origin	16.9%	13.3%	14.2%
Total		Count	130	390	520
		% within place of origin	100.0%	100.0%	100.0%

Source: Created by authors based on the SPSS output.

).

Hypothesis 3 (H₃).

There is no correlation between the agreement level with the statement “I believe that influencers’ suggestions help me make purchasing decisions” and the respondents’ background.

Considering that the percentage of subjects from rural areas (33.8%) who agreed with the statement “I believe that influencer recommendations assist me in making purchasing decisions” differs from the percentage of urban subjects (40.5%) who expressed the same level of agreement on this matter, it can be stated that there is a correlation between the two variables. Another distinction is noticeable regarding those who completely disagree with the aforementioned statement. Individuals from rural areas account for 6.2%, whereas those from urban areas represent 4.1%.

To assess the significance of this relationship at the level of the studied population, the Kolmogorov–Smirnov test was be employed, as the test variable is measured on an ordinal scale, and the grouping variable consists of two groups.

To make a decision regarding this hypothesis, a primary approach involves comparing the values of Dcalc and Dα. The value of Dcalc can be obtained by applying the formula Dcalc = max k|F1(k) − F2(k)| or by identifying it in the table generated by SPSS (

Table 5. Contingency table based on absolute and relative frequencies.

Test Statistics a
		I Believe That Influencer Recommendations Assist Me in Making Purchasing Decisions
Most Extreme Differences	Absolute	0.036
	Positive	0.036
	Negative	−0.031
Kolmogorov–Smirnov Z		0.354
Asymp. Sig. (2-tailed)		1.000

^a Grouping variable: Place of origin. Source: Created by authors based on the SPSS output.

).

According to Table 5, Dcalc = 0.036 = 3.6%. The same value is obtained by applying the formula Dcalc = max k|F1(k) − F2(k)| (

Table 6. Calculation of differences between cumulative relative frequencies.

	Relative Frequencies		Cumulative Relative Frequencies		Difference
	Rural	Urban	Rural	Urban	F1–F2
Complete disagreement	6.2%	4.1%	6.20%	4.10%	2.10%
Disagreement	9.2%	9.2%	15.40%	13.30%	2.10%
Neither agreement nor disagreement	33.8%	32.8%	49.20%	46.10%	3.10%
Agreement	33.8%	40.5%	83.00%	86.60%	−3.60%
Complete agreement	16.9%	13.3%	100%	100%	0.00%
Total	100%	100%	-	-	-

Source: Created by authors based on the SPSS output.

).

$$\mathrm{D}\mathsf{\alpha } =136\times \sqrt{{\displaystyle \frac{\left({\mathrm{n}}_1+{\mathrm{n}}_2\right)}{\left({\mathrm{n}}_1\times {\mathrm{n}}_2\right)}}}$$

$$\mathrm{D}\mathsf{\alpha } =136\times \sqrt{{\displaystyle \frac{\left(130+390\right)}{\left(130\times 390\right)}}}=13.77\%$$

Considering that Dcalc < Dα (3.6% < 13.77%), Hypothesis H3 is accepted. Therefore, we cannot assert with 95% probability that there is a correlation between the agreement level with the statement “I believe that influencer recommendations assist me in making purchasing decisions” and the respondents’ place of origin. The same conclusion is drawn based on the significance level value (Table 5), Asymp. Sig. (2-tailed) = 1, which is greater than the considered theoretical significance level (0.05).

5. Discussion

The results of this study bring an addition to this field, more precisely to studies in the scientific literature. For a better understanding of the overall image of the study performed, the authors illustrated Figure 11.

The conducted marketing research aimed to identify the opinions, attitudes, and behaviors of consumers in Romania regarding influencer marketing campaigns encountered in the digital services market in Romania, as well as the opinions of Romanians regarding various elements of influencer marketing campaigns. Additionally, this study sought to determine the level of familiarity with specific terms in influencer marketing. The questionnaire was drafted and administered using Google Forms, resulting in a sample of 618 adult respondents from Romania, although the sampling method employed was non-random.

The analysis of the quantitative research results has provided valuable information that can be integrated into the development of digital marketing strategies. Firstly, understanding the social media platforms on which adult Romanian users have accounts is essential. Based on the analysis of the primary data, it is observed that Instagram is the most utilized platform (82.80%), holding the top position in user preferences (75.48%). Even though Facebook is the second most used social media platform (71.50%), it ranks fourth in the respondents’ preferences (5.77%), with TikTok (10%) and YouTube (7.31%) occupying the second and third positions, respectively.

The researchers aimed to identify the level of impact of online promotional activities carried out by content creators. Therefore, a question was posed regarding the purchases made based on influencer recommendations. Ninety-two percent of respondents acknowledged having made at least one purchase based on the recommendation of a content creator, a result similar to those obtained by other studies (Sarwar-A Alam et al. 2019; Suprapto et al. 2020; Dabbous and Barakat 2020; Saydan and Dülek 2019).

An important aspect emerging from the analysis of primary data is related to the types of campaigns that instill greater trust in the subjects. The top three types of campaigns that inspire confidence in the subjects are social media campaigns where the influencer integrates the promoted product into their daily activities (68.8%), campaigns conducted by influencers they follow on social media platforms (54.60%), and those that indicate the existence of a paid partnership (31.20%). The credibility of marketing campaigns can also be influenced by other factors; for example, the number of followers an influencer has impacts the credibility of promotional activities according to 38.10% of respondents. The remaining 61.90% do not consider this aspect as crucial.

On the other hand, there are also negative effects of influencer marketing campaigns; in some cases, these can even lead to a decrease in the influencer’s community. Sixty-six percent of respondents have stopped following a particular content creator online due to the campaigns they conducted. The most frequently cited reasons include the following: the campaign was too aggressive (44.8%), the promoted product did not align with the influencer’s activities (44.8%), dissatisfaction with the promoted product (38.4%), or issues with the collaborating brand (23.30%).

6. Conclusions

In conclusion, regarding the level of trust that subjects place in recommendations from content creators on social media, the response option ‘Neither distrust nor trust’ was the most frequently selected by members of the sample. Among the most cited factors influencing the credibility and authenticity of influencer marketing campaigns are the following: social media campaigns where the influencer seamlessly integrates the promoted product into their daily activities (68.8%), social media campaigns featuring influencers that participants follow (54.6%), and the disclosure of paid partnerships in social media campaigns (31.2%).

Ninety-two percent of participants from the sample have purchased at least one product recommended by a content creator.

With respect to Objective 4, “Identifying the social media platform where influencer marketing campaigns have the greatest impact on users”, an analysis of the obtained results indicates that the top three social media platforms where influencer marketing campaigns exert the most significant impact on users are Instagram, TikTok, and Facebook. Conversely, the social media platform where the impact of these types of campaigns is least pronounced is Snapchat.

The final aspect proposed for analysis pertains to elements within influencer marketing campaigns that may lead Romanians to stop following an online content creator. Based on the analysis of the results, it can be stated that among these elements are aggressive campaigns and a lack of alignment between the promoted product and the influencer’s activities, the brand with which the content creator collaborated for the marketing campaign, sponsored campaigns as another reason, as well as factors such as the following: the influencer’s insincerity, running multiple campaigns with brands in the same sphere, promoting very different products, and focusing more on promotions than on the influencer’s personal life.

7. Limitations and Future Implications

The obtained results are highly valuable for laying the groundwork for future re-search in this field. The academic environment stands to benefit from these advantages as they can lead to the identification of new research opportunities concerning influencer marketing actions. Simultaneously, the data resulting from this research can be valuable in the economic sphere. Marketing agencies, industry specialists, or companies operating in any market, regardless of their field of activity, can formulate highly effective marketing strategies in the digital environment.

The information obtained from the conducted research is valuable for companies; however, they must extract the most suitable aspects for their specific business needs. Marketing strategies developed in collaboration with influencers will vary based on several factors, including the products marketed or services offered, the target audience characteristics (such as age, gender, and income), and the available budget. Based on these details, a partnership should be established with a content creator recognized as an expert in the relevant field, ensuring that the target audience for the promoted product aligns with the influencer’s community. Furthermore, a company’s budget may influence the type of content created, the frequency of posts by the content creator, and the duration of the campaign.

Thus, an influencer marketing strategy consists of several steps: studying the influencer market, selecting a content creator who aligns with the product to be promoted, choosing the platform where the company’s target audience is active, and determining the type of content to be created (such as video, images, or text), as well as establishing contractual terms.

Considering the information obtained from the quantitative research, the economic environment may place greater emphasis on the frequency of promotional posts and the manner in which influencers present the promoted product in their posts (the most effective approach being the seamless integration of the product into the influencer’s daily activities), which enhances followers’ trust in the influencer’s recommendations. According to the results, Instagram emerges as the most suitable platform for creating a credible influencer marketing campaign; however, the characteristics of the targeted audience also hold significant importance. Companies should request influencers to provide information about the demographics of their followers to ensure alignment with the target audience’s characteristics.

To optimize influencer marketing strategies, brands should focus on collaborating with micro-influencers, who often have higher engagement rates and resonate more deeply with niche audiences, providing a cost-effective way to target specific demographics. It is crucial to provide content to the unique behaviors of users on each platform, such as prioritizing short, creative videos on TikTok for Gen Z while using longer, high-quality content on Instagram and YouTube for millennials. Additionally, the data-driven personalization of messaging and offers, based on audience demographics, can significantly boost engagement and conversion. Authentic storytelling, rather than overt promotion, builds stronger audience relationships, especially among younger demographics that value transparency. Incorporating social proof through user-generated content and reviews can increase credibility and influence purchasing decisions. Interactive campaigns like giveaways or social media challenges, combined with real-time engagement tools like Instagram Live, further enhance brand visibility and connection with audiences. Finally, tracking and optimizing influencer campaigns with real-time analytics ensures continuous improvement and a maximized return on investment by identifying what works best for specific demographic groups.

Given the sample obtained in this research, for the development of an effective influencer marketing strategy, a content creator active on Instagram, whose niche aligns with the promoted product, should be selected. Additionally, it is important that the targeted audience falls within the age range of 18–29 years or even 18–39 years. The frequency of promotional posts should be moderate to avoid an aggressive strategy.

The present research has encountered a series of limitations throughout its course. The primary constraint arises from the non-random sampling method we employed, thereby rendering the results non-extrapolatable to the broader population under investigation. The research results may be influenced by the snowball sampling method, as it tends to create a homogenous sample whose members share similar characteristics. Consequently, the obtained information might not accurately reflect the entire consumer population of Romania. Therefore, this method limits the generalizability of the conclusions drawn. Another aspect to consider is that by distributing the questionnaire through existing social networks, diverse perspectives and experiences may be overlooked. As a result, valuable insights from various demographic groups or consumer segments that are not well represented in the initial sample could be lost.

The snowball method was also employed by distributing the questionnaire online through influencers, which may have an impact on the recorded responses. Content creators often have specific follower demographics, resulting in a sample skewed towards certain age groups, interests, or socio-economic statuses. This could affect the understanding of how different consumer segments respond to influencer marketing strategies.

Nevertheless, the outcomes derived from the analysis of collected data remain relevant to the chosen topic, as the sample size is suitable for formulating specific digital marketing strategies.

A second limitation was determined by the prevalence of closed-ended questions within the questionnaire, which may restrict the expression of respondents, thereby potentially affecting the accuracy of the research. This limitation may lead to a reduction in the variety of perspectives that subjects have regarding the concepts addressed, as they will be unable to express their opinions if these do not fit within the response options predetermined by the researcher. Closed-ended questions have the disadvantage of being unable to identify the reasons behind respondents’ opinions; consequently, important contextual information may be lost, and the depth of consumer motivations cannot be determined.

From another perspective, closed-ended questions may be interpreted differently by members of the sample, depending on each individual’s personal experiences.

Simultaneously, the theme of influencer marketing is highly topical in Romania, generating a multitude of aspects to be studied. However, the questionnaire does not permit the exploration of all aspects, making it practically impossible to cover all aspects in this study.

Considering this limitation, the diversity of responses is negatively impacted in several perspectives. Firstly, by imposing predefined response options, the predefined response options become uniform, thereby reducing variability and diversity. As a result, the findings may be less representative of the studied population, as some respondents may not fully relate to the available options. Additionally, the order in which the response options are presented can influence choices.

Moreover, closed-ended questions fail to capture the complexity of respondents’ opinions, leading to conclusions that may be inaccurate or reflect the subjects’ views with limited accuracy. The diversity of information collected through a questionnaire with closed-ended questions is also affected, as respondents with differing opinions or unique experiences may be excluded, due to their lower frequency and the potential oversight by the researcher regarding these variants.

Respondents’ motivation to reflect on their answers may decrease due to limited response options, which in turn reduces the depth and quality of the information collected. Therefore, it can be argued that closed-ended questions reduce complex phenomena to binary or simplistic choices, often leaving the respondent’s genuine and nuanced opinion unknown.

Given the identified drawbacks of closed-ended questions, future research will aim to formulate clearer and more detailed questions, offer an “Other” option for all such questions to allow respondents to express themselves freely if they do not resonate with the predefined options, and reduce the number of closed-ended questions where the research topic permits.

Another limitation may arise from respondents themselves, specifically certain terms that might be incorrectly interpreted or misunderstood by subjects. Completing the questionnaire without the support of an operator amplifies the difficulties that may arise during its completion.

Conducting the research on the Google Forms platform could represent a fourth limitation, as potential study participants are required to have internet access and a smartphone or a laptop/computer. Additionally, Google Forms may potentially mislead individuals, especially due to filter-type questions that can redirect subjects, among other factors.

A future direction involves continuing the study to ensure representativity at the level of the population under investigation. Additionally, considerations are being made to introduce new questions that better capture consumer behaviors toward influencer marketing campaigns. Furthermore, a new quantitative research study involving marketing agency managers is being contemplated to identify their opinions and attitudes regarding promotion strategies involving collaborations with content creators.

Another future perspective is represented by non-parametric tests such as the Wilcoxon signed-rank test, which might be applied. This method does not rely on the assumption of normality and could serve as a robust alternative to the t-test, particularly given the nature of our data. Secondly, running a Bayesian analysis could provide a more nuanced understanding of the probability distribution of our results, particularly in light of the benchmark used. Therefore, to complement the t-test, effect size metrics could be reported by using Cohen’s d, which can offer additional insights into the practical significance of the observed results.