Data Analysis

Data analysis, is all of the analyzes which were made about what the next action should be by using all collected data. For example, the decision of a bank to increase its digital marketing budget for the next year with data analysis help by taking into account the money that a bank spent on digital marketing activities in the previous year and the money it earned

How is Data Analysis done?

How data analysis is done varies greatly according to the question of why the data analysis was done. The size of the data is also important here. For example, if you will examine a data line higher than 1 million lines, table-based analysis tools such as Excel may be insufficient. Statistical based programming languages may be required.

In some data analysis the metric which its value is tried to be found, is already clear. For example, while the profitability rate of an e-commerce company was calculated for the previous year,  all of the products sold are multiplied by the profitability ratio over the respective acquisitions in the respective months, and the total profit amount is found. Sometimes, however, the value to be found is not certain. For example, for the question ”what is the best-selling product?” by using functions such as sorting in data analysis, methods are used like sort by sales figures.

What are Forecasting Models?

Forecasting models are mathematical models that predict what the next data will be based on the progression of a metric through data analysis. For example, according to past clicks figures and actual order information, it can be determined how a sales figure will be obtained if the budget is increased to 2 times.

As an example, let’s say the weather for the next Saturday looks rainy. We have about 2 times higher marketing budget than the previous year. In this case, by reviewing pizza sales figures and weather information in a table, we can foresee how we can expect to sell a pizza on a rainy Saturday. At this point, the marketing team will be able to take action to increase the budget for this date.

What is Data Cleaning?

Data cleansing involves the preparation of the data and the preparation of the data to be analyzed before starting the data analysis.

For example, 95 pcs ballpoint pens ordered from an e-commerce company, may not want to be considered in an analysis to find the best-selling product of the previous year. Such outlier data should be cleaned prior to data analysis.

Data Analysis Tools

Data Analysis is done in three basic steps and different programs are used at each step:

1- Reaching the Data

If your company has a database, it is usually retrieved from SQL databases, and if the data is kept out, it is retrieved via the API. The programs used here vary according to the size and needs of the company but tools can be used such as SQL databases such as MySQL, MSSQL, Access, Oracle, PostgreSQL, Cassandra, MangoDB, NoSQL databases or Google AdWords, Google Analytics, Facebook Ads API.

2- Data Analysis

Different data analysis tools can be used depending on the size of the data, the nature of the analysis and the nature of the desired output. The most commonly used tools in the industry are Excel, R, Python, SAS, SPSS.

3- Data Visualization and Reporting

The human brain is more successful in perceiving the data visually than numerically. In accordance with our nature, data visualization is performed to better understand and transfer the data. The main data visualization and reporting tools are Excel, Tableau, QlikView, D3.JS and R.

As Boosmart Digital Marketing Agency, we serve brands in data analysis which is our expertise. In addition, our ability about this, increasing our ability to optimize in digital marketing

If you think that data analysis service is appropriate to your needs, contact us. Let’s decide together what we can do for you.