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What is Analytics data?

Data Analytics is business intelligence, which is the science of using various data from different sources to analyze together. To improve a business or marketing, Data Analytics is a way to use information technology to analyze data of assist in business is divided into 3 types.

1. Descriptive Analytics is the most basic form of data usage. The emphasis is on explaining what is happening, or maybe something happens. Can explain why there are different reasons why Descriptive Analytics sample is a business report. Report on the Campaign or advertising or report the past performance. This is the basic information that shows us how to do things.
2. Predictive Analytics is a sophisticated data model that will “predict” what’s going on. Use historical data. Predictive Analytics also allows us to analyze the opportunities and risks that will occur in the future and like to know the market trend, Sales Forecasting or Campaigning. How many people are there or how much ROI?
3. Prescriptive Analytics is a form of data analysis. The most of complicated and difficult. Do not just predict or predict what will happen. The Prescriptive Analytics model will be able to adjust more and more data, and Prescriptive Analytics will also use a lot of data. The best and related to Big Data is a lot.

How important is Analytics data?

Data Analytics is very important in the digital age because online activities are increasing every year. It can analyze the relationship of the data. We can gain advantage and improve the marketing process or the experience of people buying it better. Deciding and executing marketing through the information will help to do the business better. Instinct

We can see from the international flow that many organizations have a culture called Data Driven or use the numbers and data that drive the organization or marketing strategy. Understanding the data and counting information from different media will increase the marketing and understanding of consumers. It also allows consumers to experience better by refining the marketing process and advertising to suit consumers. The key is to be able to predict the demand. Or create future market opportunities through the use of these data.

Analysis of the available data on web page information, advertising information, and social listening tools or marketing tools to try to link these data. You will see that this information will make. We know where consumers are and how they are in the online world. And where are we going to insert in the Journey to the consumer to us. How do we optimize our advertising efforts?

Data Analytics Process

Marketers are interested in reporting. I do not care what the source of the numbers affect the market and the measurement is correct? In this age has many statistics. Measurement settings are important. Which measure will be effective and important for data analysis?

Data Analytics needs to start thinking about how to measure what it will measure. And what units should be kept. Then select the required data and eliminate unnecessary or unnecessary information. And make reports.

Data Analytics Process

Many overseas companies have used Data Analytics for a long time, such as President Obama used Data Analytics in 2012 to analyze his own voice and the interaction of the bases with election activities. Obama’s can campaign and real-time campaign strategy, and the creation of various campaigns that fit the sound base.

Or Domino Pizza itself that sells pizza through the online world. Domino Pizza has implemented a Data Analytics system to analyze individual Domino Pizza business data and find out the relationships of each data set. Make sales and marketing teams aware of interesting sales information. And predict what products will sell next. And the answer is whether branches that are selling well or are likely to make a profit.

Examples of using Data Analytics

Marketers are interested in reporting. I do not care what the source of the numbers affect the market and the measurement is correct? In this age has many statistics. Measurement settings are important. Which measure will be effective and important for data analysis?

Data Analytics needs to start thinking about how to measure what it will measure. And what units should be kept. Then select the required data and eliminate unnecessary or unnecessary information. And make reports.

Where are we now?

Many businesses now do not think their data is worth it. And still look at the report after the end of the marketing campaign. Or look at just one set of data. Not interested in finding the relationship of information together to improve their business or marketing plans. It may be that most businesses in Thailand are still in the process of just Descriptive Analytics, if all the data is done and use Data Analytics seriously, it will help the business is ahead of the course.

How to begin?

Now, Data Analytics is a very important part of the future because data is an important asset. First start are try to analyze and find the link. Do not just look at it but the summary report. I need to see other raw data to make sure that any important information is missing, any important link or something related?

The information is a very serious war in the future. There are many companies that do data analysis and get the important information to keep.

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