Business Studies Journal (Print ISSN: 1944-656X; Online ISSN: 1944-6578)

Research Article: 2021 Vol: 13 Issue: 6

Impact of Digital Marketing on Customer Experience: A Case Study In Iran

Mansoureh Zare, Islamic Azad University,

Roya Mahmoudi, Islamic Azad University

Ali Reza Honarvar, Islamic Azad University

Sahar Abdipoor, Barkhat University Ahvaz

Citation: Zare, M., Mahmoudi, M., Honarvar, A.R., & Abdipoor, S. (2021). Impact of digital marketing on customer  experience: a case study in Iran. Business Studies Journal, 13(5), 1-19.


People increasingly use online environments to make purchases regarding the widespread digital environment and Internet applications. Online businesses, as a major part of people's daily lives, are strongly competing in this market. Nowadays, marketing in the digital space and creating a positive customer experience are regarded as one of the most effective strategies for business growth and a necessity for all organizations, respectively. So far, companies have been able to apply digital technologies to improve customer experience; however, scientific resources are still limited for studying the digital marketing impact on customer experience. This research aims to develop a scientific knowledge-based conceptual model, and its influential findings allow managers to develop their new strategies for providing a better customer experience. Accordingly, a sample of 385 Snapp customers in Iran participated in SEM through Smart PLS to investigate the proposed model. The results demonstrate that the considered dimensions of digital marketing (Social media, Search Engine Optimization, Two-sided market, Contextual interaction`, Consumer behavior) influence the customer experience.


Digital Marketing, Social media, Search Engine Optimization, Two-sided market, Contextual interaction`, Consumer behavior, Customer experience.


The corporates approach has shifted toward digitization and affected marketing regarding information technology (IT) advancement and increased the internet and internet tools usage; the corporates approach has shifted toward digitization and affected marketing. Digital marketing is a collection of tools and activities, which are used for marketing in digital media (Internet, mobile, or other digital media). The continuous advances in technology have resulted in the appearance of numerous new methods of electronic communication, such as social networking websites, emails, voicemails, and video conferences. This is beneficial not only to business but also to education. For instance, the current rate of internet use among American adults is about 87% and is closer to 100% for demographic groups such as college-educated and higher-income adults (American Adults, 2015, Stephen, 2016); there is no doubt that over the years technology has been responsible for creating useful resources which put all the information we need at our fingertips. The development of technology has led to so many mind-blowing discoveries that have dramatically changed our daily lives. (Stephen, 2016).

Most consumers have different contact points with companies in multiple decision-making phases (before, during, and after consumption), and these physical, affective, behavioral, and intellectual sub-experiences shape the fundamental consumer shopping experience (Brakus, & Schmitt, & Zarantonello, 2009, Flavián, C., Ibáñez-Sánchez, & Orús, 2018).

Customers now have the opportunity to experience the companies delivering productive services. This trend has led customers to expect targeted, more sensitive, and equally effective retail and other business services. (Foroudi, et al. 2018). Given that, business perspective has shifted towards digitization, and the competition between the businesses is very intense; thus, it is important for companies to evaluate changes made through digital marketing to customer experience. So far, a large number of empirical studies have been conducted on the value of customer experience due to the digital marketing dimensions (Social media, SEO, Two-sided markets, Conceptual interaction, Consumer behavior…), which are addressed in this research. Considering the development of information technology in recent years and the increase of the average online time of users, as well as the widespread use of mobile and internet devices in the world, the present study aims to determine the role and importance of digital marketing components on the customer experience and to rank them from the perspective of customer experience. This research examines digital marketing by considering the dimensions that may improve customer experience in a startup. Understanding the importance of customer experience for the success and durability of a startup is the main purpose of this research to increase the information of corporate executives for developing their digital marketing strategies.

This article aims to answer the question of whether digital marketing has an impact on improving customer experience.

There are many factors that enhance the experience of the customer regarding digital marketing, but which stands out?

Paper's Section 2, which is referred to as the conceptual background, discusses the literature and definitions of electronic marketing and dimensions related to customer experience in the digital environment to explain the questions and objectives of the research. Section 3 presents the research model, along with the proposed hypotheses. Sections 4 and 5 represent the research method and the analysis of data and findings, respectively. Finally, the discussion and conclusion, as well as the limitations of this research and suggestions for future research, are presented in Sections 6 and 7, respectively. This study is of great importance for startups and companies in order to realize customer experience through digital marketing.


The overall goal is to measure the digital aspects of marketing on customer experience in the online world. The main concepts are discussed below.

Digital Marketing

One of the things that can help companies compete in the online market and lead them to progress is the use of various integrated techniques in this field, one of the ways to gain it is to use the experiences of marketers. (Petit, O., Velasco, C., & Spence, C., 2019).

One of the consequences of adaptive processes resulting from digital technologies is the creation of added value to companies and institutions, which can be transferred from the institution to customers or vice versa (Kannan, P. K., 2017), which can lead to customer loyalty and business durability in competitive markets.

Social Media

Social media serves as a platform where buyers and sellers alike reside (Yadav, M. S., De Valck, K., Hennig-Thurau, T., Hoffman, D. L., & Spann, M. 2013., Bheekharry, N. D., & Singh, U. G., 2019). It should be noted that understanding the role of social media in the context of marketing is critical for both researchers and managers ( Fong, J., & Burton, S., 2008., Kumar, A., Bezawada, R., Rishika, R., Janakiraman, R., & Kannan, P. K., 2016., Schultz, D. E., & Peltier, J., 2013., Felix, R., Rauschnabel, P. A., & Hinsch, C., 2017).

Social media marketing gives businesses the ability to use social media to build relationships with clients, staff, communities, and other stakeholders (i.e., when they act as explorers) (Schultz, D. E., & Peltier, J., 2013., Felix, R., Rauschnabel, P. A., & Hinsch, C., 2017). Social media generally refers to online communication networks for social networking, photo and video sharing, blogging, etc., including blogs and web applications. ( Boyd, D. M., & Ellison, N. B., 2007., Teo, T. S., & Choo, W. Y., 2001., He, W., Tian, X., Chen, Y., & Chong, D., 2016).

More and more consumers are using social media sites to express their opinions, thoughts, and complaints about the services they have received and goods. Consumer interactions on social media sites will help us learn about their buying habits and shopping experiences and provide useful knowledge to help companies enhance their marketing and customer service (He, W., Tian, X., Chen, Y., & Chong, D., 2016).

The presence of businesses in social networks is accompanied by identifying their brand names and services to individuals and more communicating with the audience. Considering the presence of a large part of the community on social platforms, appropriate marketing in these networks allows to attract a large number of customers and create a competitive advantage by taking into account the role of the customer in the success of a business.

Search Engine Optimization (SEO)

The main purpose of using the internet by search engines and surfing the web by customers is to increase their information about a product or service provided by companies (Bheekharry, N. D., & Singh, U. G., 2019., Smith, A. N., Fischer, E., & Yongjian, C., 2012., Holliman, G., & Rowley, J., 2014 ). Therefore, Search Engine Optimization (SEO) is a method of increasing the prominence of a digital profile on relevant search engine results pages within a search engine. SEO plays a critical role in many companies ' digital marketing and communications campaigns globally (Iredale, S., & Heinze, A., 2016).

SEO is the combination of methods, approaches, and strategies for long-term optimization to help a web presence (i.e.blogs, social media, videos, and apps) gain consistent rankings in the search engine results pages for relevant search queries (Iredale, S., & Heinze, A., 2016).

The new technological advances coupled with the growth of contemporary search engines have influenced web content and brought significant changes (Safran, Nathan., 2013., Giomelakis, D., & Veglis, A., 2016).

There is no question that much Internet traffic depends to a large extent on the search engines (Kannan, P. K., 2017). As a result, optimizing search engines can play an important role in the success of digital marketing.

Consumer Behavior

The Internet has absolutely refurbished the way customers behave in many different marketing environments (Sharma, A., & Sheth, J. N., 2004., Lopez, A., & Castaño, R., 2019). Such technical and sociological innovations affect how marketing managers build and execute their strategies by presenting new challenges and opportunities, given the great impact such new digital environments have on the actions and engagement of consumers with products, and how marketers develop and implement their strategies to target their consumers (Lopez, A., & Castaño, R., 2019).

Exuberant Figure 1, website managers, and internet marketing researchers agree that there is an urgent need to establish a comprehensive understanding of consumer behavior in commercial online environments (Novak, T. P., Hoffman, D. L., & Yung, Y. F., 2000).

Figure 1 Path Coefficients, Factor Loadings of the Model

One of the disadvantages of traditional markets was that the customer spent a lot of time evaluating the product or service they needed, but in the digital environment, the customer can gather the required information and knowledge with a simple search on the Internet. This will lead to customer loyalty to the brand because it has made an informed choice based on knowledge and need. (Kannan, P. K., 2017., Edelman, D. C., & Singer, M., 2015).

In order to understand the effect of digital technologies, it is important to understand how customer procurement processes – pre-purchase, purchase consumption, and post-purchase phases–change as a result of new environments and devices ( Kannan, P. K., 2017).

For example, Xu et al. (2016) The effect of tablets on consumer behavior in digital environments were examined, with a focus on the role of decision-making aids in changing consumer behavior (Kannan, P. K., 2017., Xu, K., Chan, J., Ghose, A., & Han, S. P., 2016). Shi and Zhang (2014) It has been found that consumers change over time through distinct behavioral environments, and the evolution is due to their prior experience of use with different decision aids. (Kannan, P. K., 2017., Shi, S. W., & Zhang, J., 2014).

Two-sided Market

In two-sided markets, two (or more) parties communicate on a site, and different "indirect" network externalities impact the interaction. In fact, the price structure faced by both sides affects market share and overall demand volume (Roson, R., 2005).

A market is two-sided if platforms represent two groups of participants so that the involvement of at least one group increases the value of the other group participating (Roson, R., 2005., Rochet, J. C., & Tirole, J., 2004).

Though intermediaries have been operating in many marketplaces for centuries, Consumers have different approaches to certain goals in the digital environment. These goals may range from gaining information about the price of a particular product to searching for information about a product or visiting a chat room. Some may just want to have fun and have a good time. Consumers share their past experiences and knowledge when searching. Such as experiences visiting different sites or searching for specific brands that have been done in the past. The emotional state of the consumer is also important in the process of forming the consumer mental structure during the search." (Frieden, R., 2018).

There are many samples of a variety of channels in the digital marketplace which make the connection between two individuals, one final customer and main seller like e Bay. Or another kind of connection like Amazon, Alibaba, and so forth, which suggests many products and choices to the consumer to decide by comparing many aspects. Another kind of marketplace is a B-to-B platform to connect businesses to and firms with the crowd (crowdsourcing and innovation platforms like Kickstarter) ( Kannan, P. K., 2017 ).

Extended research on the online platform markets has empirically explored the nature of network effects, suggesting that more users/buyers would increase the number of two-sided marketplace advertisers/sellers (Kannan, P. K., 2017., Parker, G. G., & Van Alstyne, M. W., 2005).

Conceptual interaction

Regarding the undeniable role of interaction with the customer in achieving many of the business goals, this section aims to investigate the digital contextual interactions with the customer. Consequently, digital customer experience can be a combination of all digital interactions with the customer. The company should be able to establish communication and strengthen it every day to gain customer loyalty. For example, PK Kannan, Hongshuang, and "Alice" Li (2016) Presented an article entitled "Conceptual Interaction" and claimed that: What is studied in this section is the relationship between digital technologies and their impact on a company's atmosphere. Which can be examined in three different parts: (1) geography and location, (2) privacy and its rules, and (3) copying content and its rules ( Kannan, P. K., 2017., Kannan, P. K. Hongshuang 'Alice'Li., 2016 ).

Customer Experience In The Digital Environment

Intuition and previous research indicate that developing a convenient online environment for web users will have many beneficial implications for commercial providers; digital managers note that creating a compelling online experience for cyber clients is essential to building a competitive Internet advantage. Nonetheless, very little is known about the factors that make use of the Internet a compelling experience for its users and the main effects of this compelling experience in consumer behavior. (Novak, T. P., Hoffman, D. L., & Yung, Y. F., 2000).

Digital companies are making growing efforts to exploit useful individual information on the search habits of consumers, online reviews, social media interactions, and anything else that customers connect with the user. (Kannan, P. K., 2017).

Processes Enabled by Digital

Technologies generate value through new customer experiences and through customer interactions. A set of adaptive digital touchpoints encompassing marketing activities, entities, processes, and customers activate digital marketing itself. Significantly, the number of touchpoints rises by more than 20 percent annually as more offline customers turn to digital technologies and "younger, digitally focused consumers join buyers ' ranks (Kannan, P. K., 2017., Bughin, J.,2014).

Literature Review

This research not only addresses the dimensions of digital marketing (Social media, SEO, Two-sided markets, Conceptual interaction, Consumer behavior…) inspired by PK research (Hongshuang, 2016), under the name of Digital Marketing: A Framework, Study Program, and Research, which presented a framework for digital marketing research but also evaluated the impact of these dimensions on the customer experiences. The following section concerns several studies in the same field due to the lack of precise studies to examine the impact of these dimensions of digital marketing on customer experience.

Previous Research

Because customer value plays an important role in improving customer experience, Normada et al. presented an article entitled "Integrating Information and Marketing Technology for Better Customer Valuation" in which they discussed how developments in digital technology have helped to define, shape, and implement digital opportunities to improve the competitive advantage of organizations. Marketing's basic principles have been significantly influenced by the proliferation of information technology, where consumer engagement has been mushrooming across new digital channels, making the role of marketers inspiring. This is a systematic study based on the critical examination of applicable literature reviews and an overview of the American Advertising digital marketing topics. Breakouts in technology have given rise to various digital channels where organizations and consumers communicate, resulting in a massive data flow. Marketers find it challenging to define marketing's' who' and' what.' Different business analytics was developed and tested to better understand customer demand and deliver better customer values.

Advances in technology also brought new ways to collect and analyze data for strategic organizational development. Digital advertising and marketing are among the effective measures for businesses to be able to properly introduce their brand to customers and increase sales of their goods or services. The subject of digital advertising and marketing is so important and complex that it requires the guidance of digital advertising and marketing experts. (Bheekharry, N. D. & Singh, U. G., 2019).

Petit et al. (2019), in an article entitled ' Digital Sensor Marketing: Integrating New Technologies in Online Multimedia Experience, ' argues that: There have always been two perspectives on media culture. One is the view that challenges the effects of modern media on the agency of contemporary man and considers media culture as the result of large-scale planning and investment, and the other is the view that owes the cultural development of contemporary society to media technology. In the meantime, what is fixed and clear is the impact of these media on the life and culture of contemporary man. Contemporary man in his media life will find another identity that is most different from the previous one in the concept of relationship that the media defines for him, and this is the concept of interaction. This analysis is designed to help interested readers understand better what sensory marketing can deliver in a digital context, hoping to open the way for further research and development in the field (Petit, O., Velasco, C., & Spence, C., 2019).

In an article entitled "The Impact of Digital Technology and Increased Reality on Customer Experience," Flavian et al. (2018) emphasizes that the advent of Virtual-Reality, Increased-Reality, and Mixed Reality technology is forming a new environment in which physical and virtual objects are combined at different levels. The customer experience environment is transforming into new types of hybrid environments due to the creation of portable and embodied apps, together with highly interactive, physical-virtual interactions. Nevertheless, researchers and practitioners have not yet clearly established the boundaries between these new realities, technologies, and experiences. The aim of this paper is to provide a better understanding of these concepts and to combine technical (embodiment), psychological (presence), and behavioral (interactivity) perspectives to propose a new technology taxonomy, namely the "EPI Cube." The cube helps academics and managers to identify all technologies, current, and future, that could help or empower customer experiences, but can also produce new experiences along the customer journey. The paper concludes with theoretical and managerial implications, as well as a future research agenda (Flavián, C., Ibáñez-Sánchez, S., & Orús, C. 2018).

In the study entitled "The Role of Digital and Social Media Advertising in Consumer Behaviour," Stephen (2015) mentions: This article discusses recently published consumer research in digital and social media advertising settings. Five trends were identified: I modern consumer culture, (ii) digital advertising reactions, (iii) consumer behavior effects of virtual environments, (iv) mobile environments, and (v) mouth-of-mouth online (WOM). Such reports collectively shed light on how consumers perceive, affect, and are affected as part of their daily lives by the virtual worlds in which they are situated. Much needs to be learned, and current awareness tends to focus primarily on WOM, which is just part of the online consumer experience. To order to inspire researchers to investigate a wider range of phenomena, many paths for future research are being explored (Stephen, 2016).

In an article entitled "Investigating the Impact of Intelligent Technology in Consumer Dynamics and Customer Experience," Foroudi et al. (2018) notes that: increased use of smart technology by consumers contributes to appreciation by practitioners of their effect on consumer shopping experiences. Nevertheless, the academic literature does not consider the effect of the use of smart technology, combined with the customer's behavioral purpose, on the dynamics and customer experience. This work uses preliminary explanatory studies to examine this trend in a retail setting.

As a result of this study, there are many determinants that affect not only the dynamic of consumers but also the experience of costumers while they are involved with smart technologies (Foroudi, Gupta, Sivarajah, & Broderick, 2018).

Considering the definition of digital marketing dimensions for this research, the following hypotheses are proposed:

H1: Digital marketing has a significant effect on improving customer experience in the Snapp brand.

H2: Consumer behavior plays a significant role in improving customer experience in the Snapp brand.

H3: Search engine has a significant impact on improving customer experience in the Snapp brand.

H4: Social Media has a significant impact on improving customer experience in the Snapp brand.

H5: Two-sided markets have a significant effect on improving customer experience in the Snapp brand.

H6: Contextual interaction plays an influential role in improving customer experience in the Snapp brand.


Date Collection

In order to carry out this research and to investigate the dimensions of digital marketing, as well as its effect on customer experience, the topic cannot be well understood without referring to a particular company and examining the comments of their customers. Thus, by understanding the increasing number of startups in the digital world, the internet-based taxi startup (SNAPP) was selected for evaluation because of its activities in the digital environment, popularity, and high number of customers. In a survey, a questionnaire link was designed and sent to customers via social networks and emails, as well as in person.

Regarding the descriptive nature and the defined purpose, this research is a practical and a descriptive-survey one based on its methodology. The research method is a study of past research.

When it comes to the current study, Internet and Snapp users are considered as a statistical population. According to the research community in this research, the population of the study was unlimited. Therefore, the number of samples is obtained regarding the following equation.


The use of a questionnaire is useful for collecting accurate data and information, considering the descriptive-survey nature of the present research. Studying library information, reviewing available research samples, using journals and articles printed in journals, and studying Persian and English web sites were among other methods for collecting theoretical information in the study. Due to lack of a standard questionnaire measuring digital marketing with the desired dimensions, after studying the scientific texts and considering the experts' opinion, 32 items were considered for the variable of digital marketing with dimensions of customer behavior, search engines, social media, two-sided markets, and contextual interaction, in order to prepare the questionnaire. Regarding the questions related to the customer experience variable, according to the brand experience questionnaire (Zartanloo and Schmidt 2010), 12 items were designed with emotional, mental, and behavioral dimensions based on the Likert scale. After measuring the sample size and preparing the questionnaire, it was first designed on the Internet, and then, its link was sent to the users' email or to their account in Telegram or Instagram; some of the volunteers were received the printed version of the questionnaire.


In this study, two methods of "descriptive analysis" and "inferential analysis" were applied for data analysis. In the descriptive analysis method, we merely described the characteristics of the sample by setting tables and drawing Figure 2.

Figure 2 Bootstrap (t Values)

The accurate classification and analysis of the data and the proper use of statistical techniques, along with the use of appropriate research methods, will ultimately lead to the achievement of reliable results. After collecting, extracting, and organizing the data, the frequency distribution table and distribution ratios were prepared to begin a new phase of the research process, known as the data analysis. In the analysis stage, the important thing is that the researcher should analyze information and data with respect to the target, answer research questions, and evaluate the hypotheses Figure 3.

Figure 3 Path Coefficients, Model Factor Loadings for the Main Hypothesis

In order to analyze the data and respond to the research hypotheses, the inferential statistics, including structural equations, were used for determining the relationships between quantitative and qualitative characteristics and prioritizing the research criteria, using Statistical Package for the Social Sciences (SPSS) and SmartPLS software. In the present work, a structural model was fitted and used for SEM to confirm or disconfirm research hypotheses in Figure 4.

Figure 4 Bootstrap (t -Value) for the Main Hypothesis


Research Findings

Table 1 presents the statistical description in the considered sample.

Table 1 Statistical Descriptions
Gender Abundance Percent Have a private car Abundance Percent
Male 157 77/40 Yes 201 21/52
Female 228 23/59 No 184 79/47
Total 385 100      
Age     Education    
Less than 20 years old 31 05/8 Under the diploma 36 61/9
21- 35 years 276 68/71 Diploma 69 92/17
36- 50 years 67 4/17 Associate Degree 97 19/25
51- 65 years 9 33/2 Bachelor 113 35/29
66 years and older 2 52/0 Supplementary 69 92/17

Gender distribution

Based on the results, 157 (40.77%) people of the community were female, and 228 (59.23%) were male.

Age Distribution

Based on the results obtained in the sample, the age of the participants was as follows: 31 (8.5%) were under 20 years old, 276 (71.68%) from 21 to 35 years old, 67 (17.4%) from 36 to 50 years old, 9 (2.3%) were between 51 and 65, and 2 (0.5%) were 66 years old or older.

Education Distribution

According to the results, 36 (9.61) persons were under diploma, 69 (17.92%) had a diploma, 97 (25.19%) had an associate degree, 113 (29.55%) had a bachelor degree, and 69 (17.92%) had a master degree.

Personal Car Distribution

Based on the data gathered in the study, 201 people had a private car, while 184 people had no private car.

Table 2 reports the technical analysis of the research variables, mean, and standard deviation (SD) of the indicators. Accordingly, 385 correct answers to all survey questions were collected in this regard. The two-sided market had the highest mean among the digital marketing components, indicating the special attention of people to this component.

Table 2 Mean and Standard Deviation (SD) of the Indicators
Standard Deviation Avg Max Min  
4.54264 20.7506 29.00 4.00 consumer behavior
4.24740 24.2842 32.00 16.00 search engines
2.30580 14.4597 20.00 6.00 social media
6.90373 31.1766 45.00 21.00 two sided markets
4.03015 19.0519 25.00 12.00 contextual interaction
5.82194 35.7818 43.00 27.00 Costomer Experience

Inferential Analysis

Model fitting: After calculating factor loads, it was found that the factor loadings of items 1, 2, 12, 13, 17, and 18 were less than 0.6, and thus, they were removed from the model.

Figure 1 illustrates the factor loadings and model path coefficient after removing the above-mentioned items.

Before testing the assumptions of the research, it is necessary to fit the measurement model, structural model, and general model. Fitting the research measurement model is carried out based on the convergent validity (considering the factor loading and average variance extracted (AVE)), combined reliability, Cronbach's alpha, and divergent construct validity (diagnostic validity). As shown in Figure 1, the factor loading of all indicators/questions of the main research structures is significant at the confidence level of 95%, and there is no need to remove them. Tables 3,4,5 summarizes the fitting process of the measurement model. The values of Cronbach's alpha, combined reliability, and AVE are greater than 0.7, 0.6, and 0.5, respectively (Table 3). In addition, the amount of second power AVE of the research structures is more than the correlation power of that structure with other structures (Table 3), confirming the validity of the diagnostic validity for all structures of the model.

Table 3 Fitting Indicators of the Measurement Model
Indicators Cronbach's Alpha Composite Reliability AVE R2 Q2 GOF
Consumer behavior 0.794 0.857 0.548 0.904 0.587 0.728
Contextual interaction 0.869 0.905 0.768
Search engines 0.798 0.869 0.626
Social Media 0.949 0.958 0.743
Tow sided Market 0.834 0.889 0.640
customer experience 0.860 0.906 0.707
Table 4 Factor Loading of Each Item on Research Structure Variables
Structure Original Sample (O) Standard Deviation (STDEV) T Statistics (|O/STDEV|) P Values
AFFECTIVE <- customer experience 0.803 0.020 39.928 0.000
B11 <- Consumer behavior 0.646 0.042 15.453 0.000
B13 <- Consumer behavior 0.832 0.021 38.979 0.000
B7 <- Consumer behavior 0.737 0.019 39.818 0.000
B8 <- Consumer behavior 0.642 0.036 17.924 0.000
B9 <- Consumer behavior 0.821 0.019 44.083 0.000
BEHAVE <- customer experience 0.923 0.008 123.019 0.000
C14 <- Contextual interaction 0.983 0.007 138.124 0.000
C15 <- Contextual interaction 0.986 0.006 152.156 0.000
C16 <- Contextual interaction 0.604 0.063 9.604 0.000
D19 <- Social Media 0.910 0.008 114.536 0.000
D20 <- Social Media 0.956 0.005 196.692 0.000
D21 <- Social Media 0.763 0.024 31.773 0.000
D22 <- Social Media 0.792 0.013 59.169 0.000
D23 <- Social Media 0.927 0.006 164.944 0.000
D24 <- Social Media 0.862 0.009 99.186 0.000
D25 <- Social Media 0.893 0.015 57.989 0.000
D26 <- Social Media 0.768 0.023 32.887 0.000
E27 <- Tow sided Market 0.907 0.011 82.280 0.000
E28 <- Tow sided Market 0.828 0.031 26.563 0.000
E29 <- Tow sided Market 0.932 0.007 133.226 0.000
E30 <- Tow sided Market 0.255 0.060 4.252 0.000
E31 <- Tow sided Market 0.871 0.020 42.945 0.000
INTELECTUAL <- customer experience 0.765 0.017 43.810 0.000
SENSORY <- customer experience 0.864 0.016 54.516 0.000
a3 <- Search engines 0.746 0.032 23.500 0.000
a4 <- Search engines 0.655 0.037 17.832 0.000
a5 <- Search engines 0.884 0.009 95.602 0.000
a6 <- Search engines 0.859 0.012 73.835 0.000
Table 5 Estimated Path Coefficients
way (O) STDEV T Statistics P Values RESULT
Consumer behavior -> customer experience 0.535 0.026 20.587 0.000 Confirmed
Contextual interaction -> customer experience 0.279 0.035 8.006 0.000 Confirmed
Search engines -> customer experience 0.225 0.022 10.283 0.000 Confirmed
Social Media -> customer experience 0.233 0.060 3.894 0.000 Confirmed
Tow sided Market -> customer experience 0.204 0.048 4.205 0.000 Confirmed

Furthermore, the fitting of the structural model is carried out by using the adjusted R2Q2 and indicators. As presented in Table 3, all of the adjusted R2 values are significant. Chine (1998) introduced three values of 0.19, 0.33, and 0.67 as the benchmark for weak, moderate, and strong R2 values. Accordingly, the values R2 and adjusted R2 the model's dependent variables are at a relatively moderate level.

The index measures the predictive power of the model. The values of 0.02, 0.15, and 0.35 indicate the weak, moderate, and strong predictive power of the model for the endogenous structure, respectively. This value has been obtained less than 0.35 for dependent variables of research, indicating the relatively moderate predictability of the model and the relatively favorable structural model. In order to study the fitting process of the general model, which controls both sections of the measurement and structural model, the goodness-of-fit (GoF) criterion is used as follows:


Where Communalities is obtained from the average of the common values of the first-order hidden variables? The three values of 0.01, 0.25, and 0.36 are used as the benchmark value for weak, moderate, and strong GoF values. Therefore, achieving the value of 0.445 for GoF indicates a strong fit of the model. Hypotheses test.

Fitting Model for the Main Hypothesis

Tables 6,7,8 summarizes the fitting process of the measurement model. The values of Cronbach's alpha, combined reliability, and AVE are greater than 0.7, 0.6, and 0.5, respectively. In addition, the amount of second power AVE of the research structures is higher than the correlation power of that structure with other structures, which confirms the diagnostic validity for all structures of the model. According to the findings, digital marketing has a positive and significant impact on customer experience because the amount of path coefficient is equal to 918 and the significance level is 118.236, indicating the statistical significance of the coefficient.

Table 6 Fitting Indicators of the Measurement Model
Indicators Cronbach's Alpha Composite Reliability AVE R2 Q2 GOF
Digital Marketing 0.742 0.831 0.636 0.904 0.587 0.728
customer experience 0.860 0.906 0.707
Table 7 Factor Loading of Each Item on Research Variables
Structure Original Sample (O) Standard Deviation (STDEV) T Statistics (|O/STDEV|) P Values
AFFECTIVE <- customer experience 0.818 0.018 46.349 0.000
BEHAVE <- customer experience 0.918 0.008 119.963 0.000
Cansumer behavior <- Digital Marketing 0.891 0.007 134.056 0.000
Contextual Interaction <- Digital Marketing 0.444 0.057 7.728 0.000
INTELECTUAL <- customer experience 0.747 0.018 41.093 0.000
SENSORY <- customer experience 0.870 0.015 57.722 0.000
Search engines <- Digital Marketing 0.886 0.036 24.626 0.000
Social Media <- Digital Marketing 0.969 0.002 434.281 0.000
Tow Sided Markets <- Digital Marketing 0.683 0.020 33.759 0.000
Table  8 Estimated Path Coefficients
Way (O) STDEV T Statistics P Values RESULT
Digital Marketing -> customer experience 0.918 0.008 118.236 0.000 Confirmation

Consumer behavior has a significant impact on improving customer experience in Snapp brand. Based on the results, the path coefficient of the consumer behavior to the customer experience is equal to 0.535. The t-statistic value for this path is equal to 20.587, which represents the significance of the estimated coefficient given the larger value of this coefficient (1.96). As a result, the present hypothesis is confirmed. The results are represented in Table 9.

Table 9 Results from the Implementation of Sem (First Hypothesis)
Result t-statistic Coefficient Dependent variable Independent variable Hypothesis
Confirmed 587/20 535/0 Costomer Experience consumer behavior First

Search engines have a significant effect on improving customer experience in the Snapp brand. The results indicate that the path coefficient of the search engine to the customer experience is equal to 0.225, and the t-statistic value for this path is 10.283. This value is larger than the value of 1.96, which indicates the significance of the estimated coefficient. Thus, the hypothesis is confirmed, and the results are summarized in Table 10.

Table 10 Results from the Implementation of Sem (Second Hypothesis)
Result t-statistic Coefficient Dependent variable Independent variable Hypothesis
Confirmed 283/10 225/0 Costomer Experience search engines Second

Social media plays a significant role in improving customer experience in Snapp brand. Considering the findings of this research, the path coefficient of social media to the customer experience is 0.233, and the t-statistic value for this path is 3.894, which is larger than 1.96 that highlights the significance of the estimated coefficient. As a result, the hypothesis is confirmed. Table 11 reports the results for this hypothesis.

Table 11 Results from the Implementation of Sem (Third Hypothesis)
Result t-statistic Coefficient Dependent variable Independent variable Hypothesis
Confirmed 894/3 233/0 Costomer Experience social media Third

Two-sided markets have a significant impact on improving customer experience in Snapp brand. Based on the results, the path coefficient of the two-sided markets to the customer experience is 0.204. The t-statistic value for this path is 4.205, which is larger than the value of 1.96, indicating the significance of the estimated coefficient; thus, this result confirms the present hypothesis, and the results are summarized in Table 12.

Table 12 Results from the Implementation of Sem (Fourth Hypothesis)
Result t-statistic Coefficient Dependent variable Independent variable Hypothesis
Confirmed 205/4 204/0 Costomer Experience two sided markets Fourth

Contextual interaction has a considerable impact on improving customer experience in Snapp brand. Regarding the findings, the path coefficient of the contextual interaction to the customer experience is 0.279, and the t-statistic value for this path is 8.006. This value is larger than the value of 1.96, which indicates the significance of the estimated coefficient. Consequently, the present hypothesis is confirmed. Table 13 depicts the results related to this hypothesis.

Table 13 Results from the Implementation of Sem (Fifth Hypothesis)
Result t-statistic Coefficient Dependent variable Independent variable Hypothesis
Confirmed 8.006 0.279 Costomer Experience contextual interaction fifth

Given the findings, among the effective indicators on customer experience, the consumer behavior indicator has the highest path coefficient and, consequently, has the most impact on the customer experience. Table 14 reports the ranking of the indicators.

Table 14 Ranking Factors Affecting the Customer Experience
Row Index Coefficient rank
1 Cosumer behaviour 0.535 1
2 Contextual Interaction 0.279 2
3 Search engines 0.225 4
4 Social Media 0.233 3
5 Tow Sided Markets 0.204 5


The present study was conducted to determine the impact of digital marketing on customer experience using the SEM method. The results of a survey on 385 consumers in the Snapp startup in Iran show that digital marketing has a significant impact on improving the customer experience. New digital technologies are constantly emerging and can be used for applying personalization, presenting targeted advertising, acquiring greater productivity, achieving market share, and creating sustainable competitive advantage. Most people know how to use the digital environment, and therefore, digital marketing can be effective in improving customer experience by creating targeted strategies. On the other hand, digital marketing managers can predict the needs of their customers in the digital environment by specifying the target groups and training them.

The findings of the research also indicate that consumer behavior has a significant effect on improving customer experience. Shopping digitally is not based on the actual experience of buying goods but on appearances such as images, shapes, information, and advertising. Before buying, there is an important process of decision-making and persuasion that needs to be considered. Build the mind of the consumer to buy.

Changing consumer behavior is regarded as one of the main goals of marketing. In this way, consumer behavior in digital environments is effective in enhancing customer experience, which can be used to achieve digital marketing goals. Digital technologies affect consumer behavior, and therefore, consumer behavior is effective in improving customer experience. Further, the research achievements indicate that search engines have a significant effect on improving customer experience. Since search engines are used to solve any problem or satisfy any need in today's world, the correct collection of information on the website is possible, resulting in attracting more audiences through search engines. Given that many buyers check online the products and services before purchase decision-making and a high percentage of people, who use search engines, try to find their answers at the initial results, it is necessary that the site appears on top and first for the related phrase. For example, the correct selection of the title is of great importance, especially for the users to know whether the page is related to what they are searching for. Search engines can improve customer experience and value creation.

Chan, Wu, and Xie (2011) found that The physical, emotional, and mental activities that people perform when selecting, purchasing, using, and disposing of goods and services to satisfy their needs and wants are interpreted as consumer behavior.

There is little room for doubt that the role of social media in increasing the experiences of customers is highly significant and leads to transform the ratio of potential customers to buyers. Furthermore, while changing the ratio of current potential customers to buyers, social media encourage these buyers to approve and share the products by recording their positive or negative comments on a purchased product (Foroudi, P., Gupta, S., Sivarajah, U., & Broderick, A., 2018).

Therefore, despite the impact of social networks on improving customer experience, companies can use social networks to strengthen their relationships with their customers by formulating targeted strategies. Additionally, managing social media is necessary to ensure positive interaction with the customer.

As mentioned-above, two-sided markets have a significant impact on improving customer experience. The Internet has reduced geographic space constraints, and now, we witness the emergence of huge companies in the two-way markets in recent years, including Uber, Ali Baba, Amazon, eBay. The Internet also has the potential to expand the scale of two-sided markets, although the benefit of the seller is to provide a set of sellers and buyers on both sides and to benefit from their transactions. The expectations and desires of the two groups of market participants should be met to succeed in these markets. In other words, these markets have provided infrastructures that allow two different groups of customers to interact; that is, there are users on both sides of the business, and we can create value for them by creating a customer experience. It is worth noting that understanding the behavior, designing strategies, and formulating optimal regulations are among the most important steps in this regard.

When it comes to Amazon, many aspects could be considered, but the main role which stands out is creating an integrated relation between sellers and customers in a web-based platform in which high-demand products are being offered to in a game-setting, the firm strategies (Kannan, P. K., 2017., Jiang, B.J., Jerath, K, and Srinivasan, K., 2011).

Finally, the results highlight that contextual interaction has a significant impact on improving the customer experience. Effective communication with customers can increase the rate of sales and re-visit of the customers to the company. Providing a better experience to the customer throughout his shopping process engages potential customers and leads them to purchase. Optimizing the customer shopping experience increases the conversion rate at any moment from interaction with the customer, as the quality of customer experience is crucial for the success of the purchase process, as well as to be acquainted with their needs through interaction with customers. Ultimately, recognizing the audience is a necessity to improve the customer experience, should be emphasized for stability in the long-term relationships market, and updated contextual interactions with customers.


At the time of purchase, the customer is involved in various issues that logically or even emotionally affect the customer's choice; the interactions resulting from the relationship between seller and customer and product selection factors cause the customer to gain experience in the field of purchase. This experience can be due to the marketer's attitude and relationship with the customer that the more useful this interaction is, the better the marketer's career future will be. Customer experience can also play an important role in preparing a roadmap for brands in the face of various issues. This category is the main difference between brands. Lack of proper customer experience management solutions will affect all aspects of your business.

The present study might be able to provide companies with instructions to attract and retain more customers through a descriptive analysis by linking digital marketing and customer experience to startup strategies. By developing a conceptual model and validating its determinant factors, this paper aims not only to create new insights that play a critical role in the success of startup apps but also to develop strategies that enhance the customer experience. Thus, the findings provide advantages for the success of startups.

The current research was conducted on Snapp startup, and the results may be changed for other companies. Furthermore, the culture of using emerging startup applications in the country is very important; for example, the elderly people or those who do not know how to use smart technologies are known as the limitations of our research; therefore, it could be a topic of future research to be conducted.

It is recommended that future research consider how different startups should design a digital experience that leads to customer attraction and what new technologies should be used to create customer value and overcome the competitors. Finally, providing insights on how to create changes in startup marketing can be another topic for future research; we hope that this research greatly contributes to paving the way for further research and development in the area.


Funding (There is no Funding)

Conflicts of interest/Competing interests (There is no Conflicts of interest)

Availability of data and material (applicable)

Code availability (Not applicable)


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