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«Use of Web Analytics and DataMining in Websites to Improve Navigation Process and Marketing Plan. Autoria: Andre Luiz Zambalde, Alexander Kippes, ...»

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Use of Web Analytics and DataMining in Websites to Improve Navigation Process and

Marketing Plan.

Autoria: Andre Luiz Zambalde, Alexander Kippes, Ahmed Ali Abdalla Esmin, Eder Bruno Fonseca

The knowledge of consumer habits can help companies explore user needs, how they use

products and how they react to marketing campaigns. Marketing experts mostly choose the

maximum of available channels in order to generate the most revenue. Choosing every

available channel often has the negative effect of companies loosing the real target group for their products. Sending messages only over the mass media is not the best solution for a marketing campaign in every case. The goal must be to identify the relevant focus groups and to send them individually targeted messages. To reach this goal companies should use Data Mining Tools that use Mining Techniques in order to help discover hidden consumer information. Data Mining consists of statistical techniques that help to find hidden information in huge amount of data related to user and customer experiences. Data Mining is used to find common user behavior patterns and the extracted information can improve the process of strategic business and marketing decision making. This paper describes the use of web analytics and data mining to improve web site navigation process for marketing purpose with real case study. The research was conducted between july/2009 and october/2009. The unit of analysis was the web site of distance-learning post-graduate course in Software Engineering, offered by Federal University of Lavras. Data were collected considering techniques of knowledge discovery in databases and web usage mining. The described results provides some valuable information on how to improve the marketing strategy for the website. A small minority of visitors used search engines to find the website and a big majority of users left the website after the first click. The website should firstly be optimzed for search engines and an AdWord marketing campaign could be initiated to generate more visitors from search engines. Furthermore, an e-Mail marketing campaign could increase the direct hits of the intended doorway page. An e-Mail campaign could be sent out to former students of the University or other universities. To estimate the success, different landing pages could be used in the e-Mail and AdWord campaigns. When a redesign including search engine optimization should be initiated, the website has to examined with Data Mining Context algorithm. The goal would be to find out the keyword density and the search ranking of the page. The ranking is a product of the link strengths that are connected to the page.

Considering the high number of visitors that left quickly, it could be recommended that the back links of the page are controlled to find out which back links work to improve the performance.

1 INTRODUCTION

1.1.Contextualization and motivation The Internet drastically changed the world in which we live in. The Internet connects millions of people and brings companies closer to their customers. With the Internet a massive amount of information is interconnected and data is available for everyone and everywhere. In the so called information age the amount of data for users and businesses is enormous and it needs to be selected to obtain new and relevant information. In business, knowledge, especially knowledge about the consumer behavior, is necessary to survive in today's highly competitive markets. Often consumers act differently than companies expect. It is necessary to find out more about the consumer needs and expectations. The Internet provides new opportunities to obtain the necessary data to discover the consumer knowledge in real time. Modern computer systems can help companies in finding relevant information that can be the foundation of innovation processes. Consumers talk freely on the Internet and exchange messages in many different ways.

Data Mining can also be used in marketing strategies and in selling products online. The size of the company is not important, start-ups as well as established companies can profit from Data Mining technologies. Data Mining can be used to identify special user groups and to create individual targeted marketing campaigns which deliver information to these groups.

The usability of a website can be improved by examining what the main navigation paths are and why the user might choose different navigation paths that were not expected.

1.2 Objectives and structure of the work The University Federal of Lavras MG-Brazil offers distance learning courses. On different websites they present courses and their objectives to potential learners. This research will examine the commercial website of a distance learning course in software engineering. The goal is to find out how the user enters, navigates and leaves the website. Also it is examined which technologies the visitor uses in order to create specific target groups and to help to test updates. The overall goal is to propose marketing strategies that can improve the performance of the website in the future.

This case study is divided into four parts. In the first part the theoretical background for the research is explained. It deals with customer behavior and online marketing explaining how the consumer behavior changed over the past decades, how the Internet invoked recent changes, and how companies create marketing strategies. Furthermore, the concept of Knowledge Discovery in Databases and the techniques and forms of Data Mining are explained. The second part describes the methodology that is used to collect and evaluate the data. Here it is explained how the research is conducted, how the website is observed and how relevant information is extracted. The overall concept of Knowledge Discovery in Database processes is explained in which data is collected until the results will reveal useful and relevant new information. The last two sections – the research, the discussion and the conclusion – present the results of the research including which technologies the investigated visitors used and how they navigated through the website. Opportunities for new marketing concepts and strategies are presented that can help to improve the performance of the website.





2 THEORETICAL REFERENCE

2.1 Consumer behavior 2.1.1 Today’s consumer Markets consist of consumers and companies, with new competing companies constantly entering the market and trying to sell their products. According to Vieira (2002) the customer relationship became more to a center of strategic thinking. In instable markets it is necessary to investigate consumer behavior in order to satisfy expectations and needs – this is considered the most important factor for surviving in a hyper competition (CARLOS;

VARGAS, 2008).

Consumer behavior is considered as what a consumer feels, thinks, and does during the process of making a purchase decision. When the consumer makes a decision he is influenced by his cultural background, his knowledge and the friends in his environment. Social and cultural environments of a customer change (VIERA, 2002) – therefore, winning a customer is only the first step in creating a lasting relationship and satisfying the customer in a long term. A customer model must be simple but it has to be checked for appropriateness every time it is used.

2.1.2 What is consumer satisfaction?

According to Lira and Marchetti (1999), there are five steps in a consumer’s purchase decision (Figure 1). In the first step the consumer compares an ideal form derived from knowledge and values with the real situation. Then the consumer searches for more information to make a decision. After the search the consumer makes an evaluation of the relevant information and from different perspectives. Based on the results the consumer buys a product and in the post buy decision phase the real satisfaction evolves.

–  –  –

The satisfaction and with it the human behavior is of high importance for companies.

According to Chauvel (1999), the maximization of the customer’s satisfaction is the most important instrument to a company’s successes. Thereby, the different ways of usage of a product have to be considered in marketing decisions. Some models are criticized because they see the usage only from the perspective of the manufacturer and not from the customer’s side. The consumer is not only one stereotype person. There are several types of consumers with different minds, ideas of use and rationalities (CHAUVEL, 1999). The rationalities of different persons range widely and with it what is considered to be rational. When a customer acquires a product, the usage can be quite different to what the constructor intended and the customer’s behavior might be considered irrational. The observed irrationality in consumer behavior was the reason why companies started to examine the consumers’ minds and to interpret cognitive processes (CHAUVEL, 1999).

2.1.3 Online consumer behavior Today many technical innovations like the Internet inform consumers quickly about new products and even offer the opportunity to create own retail outpost (GABRIEL, 2008). The online consumer spends a lot more time browsing for products and information than he would in real stores. In physical stores a seller can quickly find out if a product is a success but he cannot see quickly when it is a flop. In the online marketplace this changes and sellers can see very quickly when a product flops because a lot of customers are influencing the purchasing process of others by telling their opinions online or leaving hidden messages in comments, blogs or guestbooks. (BURBY; ATCHISON, 2007, CAMPELL; 2005).

The consumer is the most important force in markets. Without a consumer there is no market.

Companies should have a special interest in the reactions of a customer. Every reaction of the customer must lead to reaction of the company with the goal to provide better services or products (BURBY; ATCHISON, 2007). Therefore, companies have to measure and collect data of the customer’s behavior. In the data collection the companies save page visits and navigation routes. This kind of data may describes the cognitive processes of the customer and can be used to learn about customers and the success of business decisions. This is not only a momentary situation – the history of a customer’s behavior can help to learn from the past and improve future marketing and business decisions. To reach these goals the website has to be optimized in a customer driven process (BURBY; ATCHISON, 2007).

In order to understand the online customers the company needs knowledge about the online customer behavior (SONG; ZAHEDI, 2005). According to Song and Zahedi (2005) a genetic model of online customer behavior leading to a purchase decision.

2.2 Today’s Marketing Today the Internet is not only a platform to sell products but also a platform that provides companies with the opportunities to collect data about customers and to evaluate the performance of a website or campaign very quickly. Automatic performance tests and evaluation of customer behavior can support marketing and business decisions (BURBY;

ATCHISON, 2007).

Consumer often use search engines and keywords to find products online. For marketing strategists keyword marketing has become a main strategy and businesses often spent their marketing budgets for getting as many potential customers to their websites as possible.

However, not every visitor will make a purchase decision and the keyword is only a doorway that is not always matching the visitor’s wishes and needs. Data Mining can help to select the visitors in groups of interst (BURBY; ATCHISON, 2007).

To get a better overview over the website the content and hyperlinks have to be grouped.

According to Huang (2007), there are four basic steps in an online shopping process: product information site, click forward links, basket link, and the purchase. The model can be modified for individual needs since not all shopping processes need all these steps.

2.3 Knowledge Discovery with Web Mining 2.3.1 Data Mining and knowledge discovery With the enormous amount of collected data the necessity for processes that deliver useful information for supporting decision making arises (ZAIANE, 1999). The amount of data alone does not create more information or knowledge by itself. It is necessary to find techniques that help to produce useful information from the collected data (OBERLE, 2000).



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