Online consumer behavior is rapidly changing in this world of technological advancement. The efficiency and convenience of the World Wide Web is a big contributing factor in how the consumers can alter their purchasing patterns and how easy it is to get access to a vast library of products available not only in their locale but also globally. According to the following research article, online consumers have certain behavioral characteristics that distinguish them. It indicates how consumers surf the web for information and how they compare it. These findings according to him are to help in implementation of strategies and technological innovations to enhance the on line shopping experience.
Introduction
Petrovic introduces his research report by stating the research area or question as characteristics of the online consumer and how they find, compare and evaluate product information. The question or hypothesis is how this is related to online purchase of mobile phones or related products: How do consumers find, compare and evaluate information? What are their behavioral characteristics? The core issues or research variables are the relation of Shun & Yunjie (2006) which show that there are product types such as software, books, electronics and music that are better suited to online purchasing and selling. They can be sold without the customer needing to personally inspect the product, since the details can be outlined in the product description and images. Pertinent literature in relation to the topic is shown with the review of research studies conducted recently (Cotte, Chowdhury, Ratneshwar & Ricci, 2006) that describes the distinct consumer groups in accordance with their motivations and intentions for looking for information online:
- Exploration
- Entertainment
- Shopping
- Information (Petrovic notes that in his research the target group relevant is usually teenagers who are more focused on accessing information.)
- Music, videos and lyrics
The objectives outlined are to provide recommendations that will effect change in online web sites that sell products resulting in better conversion of web page visitors into regular clients and encourage customer loyalty and referrals. The purpose is practical in that it seeks to provide e-commerce sites like e-bay with practical ways of building their consumer base. This section proves that the research is worthwhile in that it not only seeks to enhance the consumer experience in surfing for information, it also provides the online sites with key insight into the mind set of the consumer and how they can enhance and build their clientele.*
Methodology
The methodology used is the use of both qualitative and quantitative data in form of practical tests, survey statistics and one-on-one interviews done through verbal conversations, with the respondents being a group of volunteers. The evident biases in the study is that it ignores populations of above 35 years although as later discovered in the study the respondent were also not so knowledgeable as erroneously assumed. The methods for measuring results included analysis of search results on common search engines such as Google. They are pertinent in that they seek to find the common ways of finding information and give a reference of the ways they make comparisons through “extensive problem- solving behavior” (Andreasen, 1997). The implied limitations included potential for diverted attention and irritability when interrupted to give the researcher a response such that the respondents were not fully engaged in the task.
Findings
The author presents the results clearly with back up information in form of graphs and tables. They address the relevant objectives of representing the findings into pop up ads; web lay out, attractiveness of the website among other things in determining the frequency of on line visits or purchases. The author shows the behavioral patterns in form of a pie chart of the degree of patience in waiting for responses and uploading of information. The paper gives fresh insight into the necessity of high internet speeds and brevity in registration for on line purchase seeing as they are usually time conscious (Petrovic, n.d.).
Discussion / recommendations
The results support the recommendations of enhancing search engine features and optimizing on them through the graphical representation of importance of searches to finding information on products and their contribution to saving time by providing relevant information in the form of the matching indexes. Directions for further research, the alternative conclusions are not given although discussions on the related research is given I the form of a pie chart representation of Amazon.com’s price hikes and the outrage that sparked in response to it. He distinguishes how this could be another characteristic of online consumer behavior that demands consistency and fairness in prices.
Summary
The overall quality is wanting. In some areas like the introduction, research questions are not clearly defined and it is left to the reader to make inferences. The conclusion and recommendations are however very helpful for on line websites that sell products especially when the findings are assessed.
In my opinion, the research will go along way in enhancing the online buying experience. The results are important in the same respect.
The research has certain strengths: It gives an abundant amount of information through quantitative data and it clearly gives useful recommendations. On the other hand it is lacking in a distinct hypothesis that does not have to be inferred. It also lacks clearly defined research questions.
Reference
Andreasen, A. (1997). Prescriptions for Theory-Driven Social Marketing Research: A Response to Goldberg’s Alarms. Journal of Consumer Psychology, 6(2), 189-196.
Cotte, J., Chowdhury, T. G., Ratneshwar, S. & Ricci, M. L. (2006). Pleasure or Utility? Journal of Interactive Marketing, 20 (1), 45-57.
Petrovic, D. (n.d.). Analysis of Consumer Behavior Online. Analogik. 2010. Web.
Shun, C., Yunjie, X. (2006). Effects of outcome, process and shopping enjoyment on online consumer behavior. Electronic Commerce Research and Applications 5(4), 272–281