Data Analysis

Create analyses by using various data collected from different data sources.

Data Analysis

The concept of data analysis covers all the analyses that are carried out to decide on the next action by means of using data from different data sources. For instance, data analysis is used to decide whether to increase the digital marketing budget for the next year by considering the amount of money a bank has used for its digital marketing activities in the previous year and the money it has earned in the same period.

How to do Data Analyses?

In the process of data analysis, the question of “why we do it” is as variable as the question of “how we could do it”. In addition, the size of all the data that are supposed to be analyzed in this process of data analysis is also of great importance. For example, if you are supposed to analyze the data consisting of more than 1 million rows, then a table-based analysis tool like Excel would be insufficient. For these purposes, some statistic-based programming languages (Python, R, etc.) could be a better choice.

In respect of some certain data analyses, the criterion for which we want to identify the value is already apparent. For example, when calculating the profitability ratio of an e-commerce company in the previous year, the total profit amount is calculated by means of multiplying each of all the products sold with the profitability rate in the respective month. However, sometimes, the value that we are supposed to identify is not apparent. For example, using the question of “what is the product that is sold the most?”, there may be some different methods to be used for the data analysis such as sorting by the sales figures.

What is Forecasting Model?

A forecasting model is a mathematical model that is used to forecast the next data in the upcoming process considering the course of a criterion through data analysis. For example, with the help of the forecasting models, one could identify the sales figures if the budget is to be doubled considering the clicks that have been achieved and the orders that gave been placed in the previous period. Assume that rain is expected for the next Saturday according to the weather forecast. And we have a marketing budget that is about 2 times that we had in the previous year. Accordingly, considering the pizza sales figures and weather condition details in the previous years on a table, we could forecast the number of pizza sales for a Saturday on which it will be raining. And making use of using this forecast, the marketing team could take actions to increase or reduce the budget.

What is Data Cleaning?

The process of data cleaning covers the stages of the data preparation before the data analysis and, the finalization of the data that are to be analyzed accordingly.

For example, the ball-point pens for which a purchase order is placed with an e-commerce company for 95 pieces may not be considered in an analysis to find the best-selling product of the previous year.

Data Analysis Tools

Data analysis is carried out under the three main steps and, a different program is used for each step;

1- Data Collection: If your company has the data and keeps them out of the SQL databases, then the data are collected through an API. Although different programs may be used for this purpose considering the size and requirements of the company, the SQL databases such as MySQL, MSSQL, Access, Oracle, and PostgreSQL, the NoSQL databases such as Cassandra and MangoDB or the applications such as Google AdWords, Google Analytics and Facebook Ads API could be made use of.

2- Data Analysis: There are different data analysis tools to be used depending on the data size, the analysis type and, the nature of the intended output. The most common tools used in the sector are Excel, R, Python, SAS, and SPSS.

3- Data Visualization and Reporting: Human brain is better at perceiving the data visually than numerically. Inherently, the data are to be visualized so that we could understand and transfer them in a better manner. The main data visualization and reporting tools are as follows: Excel, Tableau, QlikView, D3.JS, and R.

As Boosmart Digital Marketing Agency, we serve the brands in the field of data analysis about which we are experts. In addition, this skill significantly increases our optimization ability in the field of digital marketing.

If you think that you need a great and comprehensive Data Analysis service please don’t hesitate to contact us and let’s decide together what we can do for you.