Keywords

Digital advertising, Social media marketing, Web-ads, Factor analysis.

Introduction

Social Media Marketing (SMM) stands out as a highly potent tool for businesses, regardless of their scale, to broaden their audience, attract new clientele, and enhance revenue streams. It represents a swiftly evolving force in today's marketing arena, positioning itself as the inevitable future of promotional strategies, potentially supplanting conventional marketing mediums entirely. Leveraging the internet, businesses can now promote their ventures even with minimal financial resources, thanks to an array of innovative and cost-effective online advertising methods, offering greater flexibility compared to traditional print or broadcast media. Moreover, the internet facilitates round-the-clock interaction and business transactions between buyers and sellers, fundamentally altering the dynamics of commerce Alijani et al. (2010).

The facts are that digital methods of communication and marketing are faster, more versatile, practical and streamlined. According to Ittisa Team survey 2016, 50% of the world’s population will be connected to the internet by the end of 2016, with 15% internet penetration in India, and with an average user spending around 4 hours and 25 minutes a day online.

In India, the number of internet user is over 300 million and growing exponentially. Unlike traditional marketing, Digital making can attract the mass at a lower investment. With the change in trend and the amount of time people are spending on internet, it is very likely that the marketers can catch their attention in person, unlike offline marketing where they are mainly public display.

Rationale of the Study

The Internet Advertising Revenue Report (2016), conducted by PriceWaterhouseCoopers (PWC) US, unveiled a notable uptick in U.S. internet ad revenues during the first quarter of 2016, reaching a new high of $15.9 billion, surpassing the previous year's Q1 record of $13.2 billion. These findings underscore the growing importance of the internet as a key marketing channel, reflecting consumers' increasing reliance on digital platforms.

A retail survey conducted by PWC (2016) on 25000 shoppers in 25 countries, concluded that 54% of shoppers buy products online weekly or monthly, 34% agreed that mobile phone became their main purchasing tool and 67% said that either reading or writing social media reviews and comments influences their online shopping behavior.

According to a report by the India Brand Equity Foundation (IBEF) in 2016, India's advertising industry is poised to become the second-fastest-growing market in Asia, trailing only China. Projections indicate that by 2018, advertising expenditure in India's Gross Domestic Product (GDP) will comprise approximately 0.45 percent. Notably, the digital advertising sector in India has experienced rapid growth, with a yearly expansion rate of 33% between 2010 and 2015. The share of internet advertising within the overall advertising revenue is expected to double, rising from 8% in 2013 to 16% by 2018.

The surveys and reports revealed the importance of growing internet and digital penetration in India in generating leads and increasing sales. In this context, the present study is an attempt to explore the consumers’ attitudinal factors that makes web-ads more effective in order to attract the attention of target customers.

Review of Literature

In their 2003 study, Peter and Mullarkey delved into the factors influencing web advertising recall and recognition. Their investigation encompassed variables like viewing mode, duration of page viewing, and web page context, including text complexity and background, as well as banner advertisement style. Their findings suggested that individuals exposed to banner ads for longer periods were more likely to recall them. In a separate study by Kendall Goodrich in 2011, the relationship between online advertising effects and demographic factors such as age, gender, and time of day was explored. This research concluded that a significant correlation exists between online advertising attention and age.

Weintraub(2012) concluded in his research that clean images with bold colors and fonts make the ad more interesting. Abdul Azeem & Zia ul Haq (2012) studied the perception of customers with reference with three demographic groups and analyzed that five factors entertainment, information credibility, economy and value are significant predictors of attitude towards internet advertising Chaubey et al. (2015).

Vida David (2012) identified the features that make online advertising effective are: top page location, animation and frequency (6-7 exposures) of banner, audio/video streaming contents of rich media, SEO results location within the first page of results list, top location, content related sponsorships, useful content, compelling titles and frequency of 1-2 times per month of email newsletters, compelling and useful content with no requirement to pass-along the message of viral marketing and public relation activities with video, audio, picture and photo containing communication, involvement stimulation and company generated daily posts Danaher & Mullarkey, (2003); Davidaviciene, (2012).

Michael Cornwell (2015), in his article entitled “The role of the internet in marketing and advertising” concluded that 2.8 billion people are connected to the internet as of 2014, increasing from 35 million 20 years ago. Farhan & Yousaf (2016); Falebita et al. (2020); Sebastian, (2015); Sharma (2015); Vejju (2018); Wang & Sun (2010) conducted a study to explore the factors which make web advertising effective and the results revealed that to get consumers attention it is necessary to create an attractive format with colour that could highlight the advertisement and make it easy to read examined the relationship between belief factors or advertising values are predictor of attitude towards internet advertising. From their study, it was found that belief factors are better predictor of attitude toward internet advertising then behavioral variables such as internet usage and demographic variables.

Objectives of the Study

1. To explore the consumers’ attitudinal factors that makes web-ads effective.

2. To examine the influence level of consumers’ attitudinal factors on effectiveness of web-ads.

Hypothesis of the Study

H0: There is no significant relationship between consumers’ attitudinal factors and effectiveness of web-ads.

H1: There is a significant relationship between consumers’ attitudinal factors and effectiveness of web-ads.

Research Methodology

Research Design

The study is exploratory and descriptive in nature as it is mainly aimed at exploring the consumers’ attitudinal factors that are considered very important for effective web-ads placed on various social networking sites and to what extent these factors have a significant influence on effectiveness of web-ads.

Population of the Study

The present study mainly aims at identifying the influential factors on effectiveness of digital advertising, so the target population of the study included the respondents, having internet /GPRS connection and are exposed to web-ads on various social media sites.

Sampling Design and Sample Size

Purposive sampling technique was used to collect the data from 200 respondents who are residing twin cities of Hyderabad and Secunderabad and who use social media sites.

Survey Instrument

The research employed a structured questionnaire divided into two parts. The first section aimed to gather demographic data from the sample respondents, while the second part focused on exploring consumers' attitudes deemed essential for effective web advertisements across diverse social media platforms. Utilizing a five-point Likert scale was deemed appropriate for the survey instrument. Respondents were presented with attitudinal-based questions related to web advertisements and asked to indicate their agreement level on a scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Questionnaire has been distributed to 200 sample respondents, out of which 10% of the respondents are not exposed to web-ads and also 25 responses have incomplete information. These questionnaires are removed from the study and after cleaning, 155 responses are found to be in order. Hence, the present analysis has been carried out on the basis of 155 respondents.

Procedure

To meet the objectives, hypothesis was tested using various statistical tools. Data collected had been first coded and then using SPSS20 software, an Exploratory Factor Analysis and descriptive statistics has been applied to decide whether to accept or reject the hypothesis.

Data Analysis and Results

Demographic Analysis

Out of the 155 sample respondents, the majority of the respondents are females. It was found that majority of the respondents are in the age group of 18-25 years. With regard to education qualification, majority of the respondents are graduates and with regards to income majority of the respondents are in the income group between two lakhs to five lakhs. It was also observed that majority of the respondents (92%) had awareness about web-ads and only 8% of the respondents are not aware of web-ads and majority of the respondents’ opinion that YouTube consists of more ads and they preferred web-adds related to consumables.

Factor Analysis

Before conducting the factor analysis, to check the reliability of the items included in the questionnaire, Cronbach alpha test was applied. It was found that Cronbach alpha is 0.698, indicates that the items in the Likert five point scale of the questionnaire were highly reliable and can be used further in the study. After checking the reliability and consistency of the items, an exploratory factor analysis has been conducted using SPSS 20 software to group the variables/items in to a broad dimensions that makes web-ads effective. An inter-correlation matrix was first calculated to explore the possibility of applying factor analysis. Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and Barlett’s test of sphericity were used for this purpose. From the results, it was found that KMO value is 0.687, suggest that factor analysis is appropriate for the data and the significance value of Bartlett’s Test is 0.000, this leads to rejection of the idea that the correlation matrix is identity matrix Table 1.

Table 1 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.687
Bartlett's Test of Sphericity	Approx. Chi-Square	304.230
	Df	91
	Sig.	.000

Factor analysis of the responses by Principal component method and Varimax rotation with criterion of Eigen value more than 1.00 produced 4 internally consistent and meaningfully interpretable factors that explained 61.668% of total variance. Table 2 shows that the factors extracted out of 10variables under study are four in number at the Eigen value= 1.157and together contribute 61.668% of total variance. This is a fair percentage of variance to be explained and assumes the appropriateness of the factor analysis.

Table 2 Total Variance Explained
Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Variance	cumulative %	Total	% of Variance	cumulative %	Total	% of Variance	Cumulative %
1	3.029	21.636	21.636	3.029	21.636	21.636	2.000	14.287	14.287
2	1.515	20.818	42.454	1.515	10.818	32.454	1.919	13.706	27.993
3	1.290	11.214	53.668	1.290	9.214	41.668	1.682	12.015	40.008
4	1.157	8.268	61.668	1.157	8.268	49.936	1.390	9.928	49.936
5	.991	7.078	67.014
6	.964	6.888	73.902
7	.839	5.992	79.893
8	.788	5.631	81.525
9	.726	5.186	83.711
10	.683	4.880	85.591
11	.648	4.625	90.217
12	.521	3.722	93.938
13	.470	3.361	97.299
14	.378	2.701	100.000
Source: Principal component analysis

In the present study, all the 10 variables have factor loading more than 0.50, so all the 10 variables are considered for loading on extracted factors. Thus the present study extracted four factors using 10 variables named as: Web-ad presentation, Web-ad placement, Web-ad content, Celebrity in web-ads.

The table displays the outcomes of a principal component analysis (PCA), a statistical technique used to simplify and understand complex datasets by identifying underlying patterns and reducing dimensionality. Each row corresponds to a component generated by the analysis, with associated metrics revealing its explanatory power. The "Initial Eigenvalues" indicate the amount of variance explained by each component, with higher values suggesting a greater ability to capture variability in the data. The "Extraction Sums of Squared Loadings" and "Rotation Sums of Squared Loadings" show the cumulative squared correlations between original variables and the components, after extraction and rotation respectively, offering insights into how well each component represents the original dataset. The "Total % of Variance" highlights the percentage of total variance explained by each component, while the "Cumulative %" indicates the cumulative proportion of variance explained as additional components are considered. This information aids in identifying the most influential components for further analysis or interpretation, guiding researchers in understanding the underlying structure of the data Table 3.

Table 3 Factor Loadings, Eigen Value and % of Variance of Factors and their Variable
Item no	Components	Factor loadings	Eigen value	% of variance
Factor -1  web -Ad presentation
	Web – ads with bold & big letters are interesting	.610	3.029	21.636
	Web – ads with interesting colours are interesting	.559
Factor-2 Web-ads placement
	Web-ads placed in the right positions are interesting	.788	1.515	20.818
	Web-ads that are timely updated on related websites are interesting	.652
Factor- 3 Wed -ad content
	Web – ads with info that interests the consumers are interesting	.631	1.290	11.214
	Web – ads that are real & not statistical projections are interesting	.688
	Web – ads with a good sense of humour are interesting	.549
	Web – ads which provide detailed information about products are interesting	.625
Factor- 4 Celebrity in wed-ad
	Web – ads endorsed by a celebrity are interesting	.784	1.157	8.268
	Web – ads with good looking models are interesting	.674

Mean Score Analysis

To examine the influence level of consumers’ attitudinal factors on effectiveness of digital ads, Descriptive statistics such as mean score values of each factor and its concerned variables are taken into consideration. The influence level given by the respondents to the variables are ranging from level 1 (least influence) to level 5 (Most significant influence).

The table presents the findings of a factor analysis aimed at understanding the underlying dimensions of web advertising. Four distinct factors emerge, each capturing different aspects of ad effectiveness. Factor 1, termed "Web Ad Presentation," emphasizes visual appeal, encompassing characteristics like bold text and vibrant colors. Factor 2, labeled "Web Ad Placement," focuses on strategic placement and timely updates on relevant websites. Factor 3, denoted "Web Ad Content," reflects the importance of engaging content, including factors such as information relevance, humor, authenticity, and detail. Factor 4, identified as "Celebrity in Web Ad," highlights the influence of celebrity endorsements and the presence of attractive models in ads. Eigenvalues indicate the amount of variance explained by each factor, with higher values suggesting greater significance. Factor loadings reveal the strength and direction of the relationship between variables and factors. This analysis provides valuable insights for advertisers, guiding decisions on ad design, placement, and content strategy to enhance effectiveness in the competitive landscape of web advertising. Understanding these underlying dimensions can inform targeted and impactful advertising campaigns tailored to consumer preferences and behavior in the digital realm.

From the table 4 it was found that all four consumers’ attitudinal factors have significant influence on effectiveness of web ads. Among four factors, web-ad content has most significant influence on effectiveness of digital advertising.

Table 4 Mean Score of Extracted Factors Influencing Effectiveness of Digital ADS
Item no	Components	Mean	Factor mean
Factor -1  web -Ad presentation			3.52
	Web – ads with bold & big letters are interesting	3.43
	Web – ads with interesting colours are interesting	3.65
Factor-2 Web-ads placement			3.78
	Web-ads placed in the right positions are interesting	3.89
	Web-ads that are timely updated on related websites are interesting	3.65
Factor- 3 Wed -ad content			4.12
	Web – ads with info that interests the consumers are interesting	4.21
	Web – ads that are real and not statistical projections are interesting	3.72
	Web – ads with a good sense of humour are interesting	3.85
	Web – ads which provide detailed information about products are interesting	3.98
Factor- 4 Celebrity in wed-ad			3.26
	Web – ads endorsed by a celebrity are interesting	3.35
	Web – ads with good looking models are interesting	3.12

The table presents the mean scores of extracted factors influencing the effectiveness of digital ads, along with the factor mean for each component. Factor 1, "Web Ad Presentation," has a mean score of 3.52, indicating that, on average, respondents find ads with bold and big letters moderately interesting (mean = 3.43) and ads with interesting colors slightly more interesting (mean = 3.65). Factor 2, "Web Ads Placement," has a mean score of 3.78, suggesting that ads placed in the right positions are generally more interesting (mean = 3.89), while timely updates on related websites contribute to their interest (mean = 3.65). Factor 3, "Web Ad Content," has the highest mean score of 4.12, indicating that ads featuring consumer-interesting information (mean = 4.21), real content (mean = 3.72), humor (mean = 3.85), and detailed product information (mean = 3.98) are perceived as highly interesting. Factor 4, "Celebrity in Web Ad," has a mean score of 3.26, implying moderate interest in ads endorsed by celebrities (mean = 3.35) and those featuring good-looking models (mean = 3.12). These mean scores provide insights into the relative importance and appeal of different factors in driving the effectiveness of digital ads.

Discussions and Conclusions

The present paper makes an attempt to explore the consumers’ attitudinal factors that make web-ads more effective. To achieve this objective, a structured questionnaire was distributed to the target respondents who have internet connection and exposed to web-ads and who residing in twin cities of Hyderabad and Secunderabad. Out of 200 questionnaires sent, 155 responses are found to be in order and the present analysis done on the basis of 155 respondents. With regards to sample respondents’ demographic profile, majority of the respondents are female, young and educated and 92% of the respondents are aware about the web-ads. To identify the factors that make web-ads effective from consumers’ view-point, an exploratory factor analysis has been conducted using SPSS 20 software. Before conducting the factor analysis, to check the reliability of the items included in the questionnaire, Cronbach alpha test was conducted and it was found that Cronbach alpha for all 14 variables are 0.698, indicated that all items in the scale are reliable and can be used for further study. An exploratory factor analysis has been conducted to explore the consumers’ attitudinal factors that make web-ads effective. The results of the study found that 10 variables are grouped into four factors at an eigen value of 1.157 with a total variance of 61.688% and the factor loadings of all 10 variables are more than 0.5. The results of the study found that four factors named as: Web-ad presentation, Web-ad placement, Web-ad content, Celebrity in web-ads are the influential factors on effectiveness of web-advertising and among all the four factors, web-ad content was the most significant influencing factor on effectiveness of web ads.

From the results, it can be concluded that web-ad content is the most important factor where the content is showed to the target customers with full information and it should trigger an immediate response from customers’ end. Web-ad placement is the next important factor and the marketers need to put their web-ads in related search engines and ad should be easily visible to grab the attention of the customers. Web-ad presentation is the next important factor that has the potential to attract the customers by displaying the ad with different font sizes and use of colours. Celebrity in web-ads is also an important factor as the ads are endorsed by good looking celebrities who made ads more effective. The results of the study can help the marketers in leveraging the benefits by attracting the attention of target customers.

Limitations and Scope for Future Research

The present study is confined to limited geographic region of Hyderabad and Secunderabad cities only. Future studies can be extended to wider geographical regions for more generalized results. The present study laid main emphasis on web-ads placed on social networking sites. But the future studies can be elongated to different platforms where the marketer can place their ads to attract the attention of target customers.

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Received: 06-May-2024, Manuscript No. AMSJ-24-14791; Editor assigned: 07-May-2024, PreQC No. AMSJ-24-14791(PQ); Reviewed: 29-May-2024, QC No. AMSJ-24-14791; Revised: 26-Jun-2024, Manuscript No. AMSJ-24-14791(R); Published: 20-Aug-2024