In choosing your outsourcing partner, it is always important to determine whether their working environment fits your business culture.
Businesses from across industries can benefit from the use of data analytics. Part of the many benefits of its use is helping companies improve their customer service performance, optimise their marketing strategies, and boost their efficiency.
Data analytics have different processes and techniques to help firms come up with valuable insights. These insights will help business leaders to make informed decisions for the growth and success of their organization.
The travel and tourism industry is just one of the business sectors that have recognized and continuously use data analytics to figure out solutions to their customer issues. Digital marketing companies also make use of data analytics to keep their target audience clicking and watching more of their online content.
How data analytics works
Data analytics generally undergoes a step by step process:
- It starts by identifying what your data requirements are and how you are going to collect and group your data.
- The next step is the data collection.
- Third step is organizing and cleaning out all data collected. This includes fixing errors, removing duplicates, and filling out incomplete data.
- Last step is the data analysis itself.
Overall, the data analytics process and techniques will depend on the type of data to be collected, how it will be collected, and the goals for the process itself.
List of data analytics techniques
How data analysis is performed depends on the type of data acquired. Before knowing the techniques it is necessary to have a clear understanding about quantitative and qualitative data.
Quantitative data refers to anything that can be measured, this refers to numbers and specific quantities. Quantitative analysis techniques are often used for statistical analysis to explain a certain phenomena or to make predictions. Some of the quantitative analysis technique include:
Monte carlo method
In this method, you will be given different possible outcomes and how likely will each outcome be known. This method is usually used for risk reductions as it helps businesses determine what might happen and decide accordingly.
Regression analysis
The aim of this method is to determine how one dependent variable is affected by several variables. This type of analysis technique is usually used to identify and predict trends and patterns in the market industry.
Time series analysis
In this method, data is in the form of a sequence of data points that are measured in different time intervals like weekly and monthly total sales. This technique helps businesses determine cycles and trends over a period of time.
Qualitative data examples are comments, reviews, social media posts, interviews. Qualitative analysis techniques are more subjective and are often used to understand and interpret unstructured data. One example for which is sentiment analysis.
Sentiment analysis
The goal in this technique is to analyze and categorize the customers emotions within a textual data. This helps you understand what your customers’ sentiments regarding your products and services.
