a. Data collection
Data collection is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes.
There are many different methods to collect data. One can be divided into two types: the desk method and the field method.
• The desk data collection method is the method of collecting data available inside and outside the company, ie secondary data. However, by means of modern telecommunications such as web, e-mail, telephone, networked camera,… the researcher can have indirect access to the object to be studied to collect data. Therefore, data collectors can sit in the office to search secondary and primary data. In the Internet age, this method is easy to implement. However, at present, there are many limitations in secondary data sources in Vietnam.
• Field methods include many different forms of primary data collection.
Those are the methods:
1) Methods of observation
Observation method is a method of collecting primary data about customers, competitors by using people or machines to record the phenomena, behaviors of customers and employees of the company. of the competitors. The purpose of the observation is to record the behavior, words of employees, of customers when they are at places dealing with customers. After observing a certain behavior of a customer, we can interview them for more information about that behavior. It is possible to make observations by eye, by recorder, video...The observation method gives us objective results. However, the difficulty with this method is not to see the connection between the phenomenon and its nature. In order to do so one must conduct observations many times to find the rule. When observing, keep it secret to ensure objectivity. If customers know we observe, they will not behave objectively.
2) Method of interview
Interview Method is a method of collecting primary data by interviewing selected subjects. This is the only way to know customers' opinions and intentions. However, the interview method also has certain disadvantages. It is high cost, time-consuming and sometimes the interviewees do not answer or answer dishonestly (especially for Asians). Interviews can be conducted by personal face-to-face interviews, public interviews, focus group interviews, telephone interviews and mail interviews. Each of these methods has its advantages and disadvantages.
3) Experimental method
Experimental Method to create artificial conditions to determine the result when one variable is changed while the other remains the same The empirical method is appropriate for the type of cause and effect study, that is, the study of the effect of one variable on another, such as changes in price, or changes in packaging. Come to the purchasing power of customers. Some goals of empirical methods are:
• Explore the causal relationship between two quantities
• Verify a hypothesis
• Testing new products
• Test new marketing strategies (new packaging, new prices, new advertising ..).
Experimental results are observed, or participants are interviewed so that researchers know their reactions, and the data are carefully documented for analysis.
The disadvantage of the experimental method is that it is high cost, and it is difficult to control the influence of foreign factors.
b. Data analysis
Data analysis is the process of discovering, interpreting and communicating meaningful models in data. Especially valuable in areas where there is a lot of recorded information, analysis based on the simultaneous application of statistics, computer programming and operational research to quantify performance.
Application of Data Analysis - Optimize marketing
Marketing has evolved from an innovative process to a process that is highly dependent on data. Marketing organizations use data analysis to determine the results of campaigns and marketing efforts and guide investment decisions and target customers. Demographic research, customer segmentation, combination analysis and other techniques allow marketers to use large amounts of data on consumer purchases, surveys and groups to understand and communicate marketing strategy. Common analytical techniques used in marketing include mixed marketing, pricing and discount analysis, sales force optimization and customer analysis.
- Analyzing human data
This application of data analysis assists management companies in terms of personnel, with the goal of selecting which employees to hire, reward or promote, what assignments and HR other issues. Human resources analysis is becoming increasingly important to understanding which profiles with which type of behavior will succeed or fail. While human analysis is applied to employees in an organization, customer segmentation techniques are used to research customer profiles and uncover the most potential customers of the market.
- Analyzing catalog data
A common application of business data analysis is portfolio analysis. In particular, a bank or lender has a collection of customer accounts with many variables of value and risk. These customers may vary in social status, geographic location and other factors. The lender must balance the profit earned on the loan with the risk of default on each loan. Data analysis solutions can
combine time series analysis with many other issues to make decisions about when to lend to each group of customer segments, or decide on the interest rate for each in the portfolio segment to compensate for losses from the entire object in that category.
- Analyzing risk data
Predictive models in the banking industry are developed to provide certainty for the risk index of each individual customer. Credit indexes are designed to predict individuals' legal violations and are widely used to assess the creditworthiness of borrowers. Besides, risk analysis is done in science and the insurance field. It is also widely used in financial institutions to analyze whether a transaction is real or fraudulent using the client's transaction history. This application is more widely used in credit card purchases to minimize losses in the above cases.
- Analyzing digital data
Digital data analysis is a group of business and technical activities aimed at identifying, initiating, collecting, verifying or converting digital data into reporting, research, analysis and proposals…, optimize, forecast or automate. The app also includes SEO (Search Engine Optimization) in which keyword searches are tracked and become data used for marketing purposes.
- Analyzing security data
Analyzing security data related to information technology, to collect and analyze security events to find out which factors bring the greatest risks. Products in this area include information security management - events and user behavior data analysis.
- Software data analysis
Software data analysis is the process of collecting and analyzing information about how a software is manufactured and used.