he global online business environment, in recent years, is seen commercially. The development along with the emergence of online stores has made it possible to turn users into consumers. Social media creates a platform for the consumers and marketers to make communication. (Hennig-Thurau et al., 2004). (Kozinets, 1999) said that social media creates a new podium to collect product information by peer communication. Consumers can motivate other buyers by reviewing of products and services they use. There are several factors on which consumers can be influenced to buy the products and services such as income, brand's value, purchase motivation (on social networks), age, sex (Demographic), payment method, stores type (online or physical).Companies are trying to use modern marketing tools and techniques to get the competitive advantage. Modern users use Google to find the list of suggestions for their desired goods and services. They compare the goods and services among multiple sellers, shoppers. Those companies are listed top in the search results and have positive viewers' feedback sustain in the market.

People purchase consistently with their requirements both from online and in their physical presence. They consider several issues while making their purchase decision especially in case of online shop. (Mersey et. al. 2010) mentioned that due to the development along with quick growth of social networks, customers do several activities including blogging, chatting, and entertainment and messaging. (Ross et al. 2009) found that Facebook has been recognized as the top most popular as well as widely used social media networks. Social relationship, dealings with people have a great impact on consumers' buying decisions.

Internet has created a platform on which organizations of all sizes and categories can compete. Businesses using modern marketing techniques such as Internet marketing, Facebook marketing, viral marketing, search engine marketing, and e-mail marketing has become more successful in meeting the competition (Dwyer, Schurr & Oh, 2015). Flint and Woodruff (2015) reviewed the advantages related to new technology, such as shortening the product life cycle and altering standards. Social network has given scope to the marketers for product customization and targeting customers in a better way (Crosby & Johnson, 2015).

Initially starting out as a means for people to stay connected worldwide, social networking has now grown into a crucial business tool for both social as well as commercial needs. Social media provides an opportunity for businesses to involve and interact with potential consumers, inspire an increased sense of intimacy with consumers, and make all important relationships with potential consumers. (Mersey, et al., 2010). With the increasing impact of social networking on daily lives, its impact spans beyond global boundaries, transcending even social and cultural limitations (Dwyer, Schurr & Oh, 2015). Many researchers thinks that social media plays the role of a special touch point for today's consumer decision process, from the stage of consideration to the stage of post purchase. Similarly, companies are also T Keywords: social networks, google, consumer, buying behavior, dhaka city, bangladesh.

endeavoring to boost customer engagement, create brand awareness, drive traffic for marketing properties, and also raise the number of communication channels (Zarrella & Zarrella, 2010). Many companies today have pages on social networks to reveal the information about products. By using social media, consumers have the power to influence other buyers through reviews of products or services used (Kozinets, 2014).

Consumers are using several online formats to communicate to share ideas about a given product, service, or brand and contact other consumers, who are seen as more objective information sources (Kozinets, 2014). The distinctive features of social media along with its popularity have given revolutionized platform for marketing practices like advertising, promotion (Hanna, Rohn and Crittenden, 2011). (Mangold and Faulds, 2009) mentioned that social media has also effect on consumer behavior (information acquisition to postpurchase behavior) such as dissatisfaction statements or behaviors about a product or a company. The advanced level of efficiency of social media comparing to other traditional channels has impelled industry leaders to participate in Facebook, and others sorts of social media in order to be successful in online environments (Kaplan and Haenlein, 2010). A study done by Deloitte Touche´ in USA found that 62% of US consumers read consumer generated online reviews where 98% of them found these reviews trustworthy; 80% of these consumers said that reading reviews has influenced them to buy products and services. (Pookulangaran, et al., 2011). Prior research has shown that negative information from a few posts can have significant effects on consumer attitudes (Schlosser, 2005).

Researchers from social psychology have identified the sheer presence of observers who have the power to change behaviors. At the same time, in online social media there are options for subscribing contents permitted by sites and user subscriptions allow some content generators to keep record their audience size which indicate levels of trust for the content developers who allow them to push in an easier manner when it comes to their followers' pages or walls. The presence or absence of a captive audience can influence behavior (Trusov et al., 2009). Hoand Wu (1999) stated that consumers are much more likely to post reviews when they are highly content with the offerings of the product. However, in earlier times, consumers of a product tended to be more enthusiastic about it, and thus with the span of time average ratings tend to be decreased in the end. Along with all this it has seen that the uniqueness of consumers may be effective their decision of providing important reviews or their feedback about products or services. Social relations and dealings with individuals play a great role in changing people's mind sets regarding their purchasing decisions. Merseyet al. (2010) noted that the development and quick growth of online social networks enables customers to do several kinds of activities that include blogging, chatting and interaction, gaming and entertainment, as well as messaging.

This is a descriptive research where both quantitative and qualitative data have been used. Quantitative data was used as primary source and for this reason a survey with structured questionnaire, containing the 5-points Likert Scale statements, has been conducted and qualitative data was collected through secondary sources like journals, periodicals, articles, books etc. 160 respondents who are experienced with online buying and search their products to find the desired online business or ecommerce sites on using goggle and social networks. Out of 160 respondents, 30% was male and 70% was female. The average age of the sample was 25. 66% of respondents had undergraduate or graduate level of education. We have conducted Exploratory Factor Analysis (EFA) to decide if multiple variables comprise single dimension. And to do the analysis, we used Statistical package SPSS 20.0.

For this study, we have identified10 variables which are consequent of reviewing the literature review. These variables are included: V1 Product customization, V2 Interaction with customers, V3 Intimacy with customer V4 Brand awareness, V5 Update content, V6 Effective SEO, V7 Positive word of mouth V8 Key word search, V9 Type of Search engine, V10 Trust

We have used Bartlett's sphericity test to assess the null hypotheses which states that the population correlation matrix is an identity matrix where all diagonal terms are 1 and all off-diagonal terms are 0. Test statistic with large value will favor the null hypotheses rejection. The factors' appropriateness will be questioned if this hypothesis is not rejected. On the other hand, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy is termed to be useful to compare the magnitudes of the observed correlation coefficients with the magnitudes of the partial correlation coefficients. Small values (below 0.5) of the KMO statistic, in case of larger number of factors, indicate that the correlations between pairs of variables cannot be explained by other sort of variables thus factor analysis may not be appropriate. .000

Consequently, from the above table, it is apparent that factor analysis is appropriate. Here, the KMO value is .634, which is between 0.5 and 1.0, and the approximate chi-square statistic is 198.776 with 45 degrees of freedom, which is significant at the 0.05 levels. Therefore, the null hypotheses can be rejected and the alternative hypotheses that all variables are correlated to each other can be accepted. To analyze the variables ranging from V1 to V10, factor analysis has been used for data reduction. This analysis divulges the most important factors that have influence on customer loyalty From the above table, only 4 factors have been extracted, as cumulative percentage is greater than 63% at the very next cell and Eigen value is greater than 1.0 (it is recommended that factors with eigenvalues greater than 1.0 should be retained) that indicates the adequacy of the analysis using derived factors. From the above table, only 4 factors have been extracted, as cumulative percentage is greater than 61.53% at the very next cell and Eigen value is greater than 1.0 (it is recommended that factors with eigenvalues greater than 1.0 should be retained) that indicates the adequacy of the analysis using derived factors. The extracted 4 factors can be interpreted on the basis of variables that load high coefficients. From the rotated component matrix table, factor 1 includes high coefficients for Effective SEO (.732), Key Word Search (.517), and Type of Search Engine (.434). Thus, factor 1 can be named as "Searching Attributes". Factor "Customer Behavior Attribute". We termed factor 4 as Customer Relationship Attributes which generate high coefficients for Trust (.567) and Intimacy with Customer (.455).

This study tried to identify the effect of Social Networks and Google on consumers' buying behavior by investigating various related attributes and factors originated from both literature review and feedback of the questionnaire. According to the analysis of the data generated by SPSS 20, four components together explain 61.53% of the variety. But this explanation is not enough rather there are different components also and further research can be possible to find out the other factors. Moreover, city or country-wise research can also be done based on this topic.