How should businesses analyze data to get useful conclusions?

actionable insight

How should businesses analyze data to get useful conclusions?

Businesses are using data these days to a large extent. But it is also important that apart from data collection, businesses focus on analyzing that data also. Companies are getting more data than the previous periods, thanks to the developments in IT. But the businesses don’t know how to use that data. For this, a business needs to develop an actionable insight. But what is it?

Actionable insights are processes that are developed after data analysis. So, actionable insights are insights on which action can be taken. The purpose of data analysis is to derive some conclusion or actionable insight based on which a business can take a strategic decision. For example, what are the actionable insights behind observing the behaviour of customers? It’s because the data collected can be used to improve sales. It’s because when customers report that they don’t like a product feature anymore and need a new feature in it, that data forces a business to make product changes. Social media also allows businesses to get some useful data from which actionable insights can be derived.

Actionable insights are no longer a freedom of choice for a business. Such conclusions are necessary for becoming more competitive in the market.

Getting actionable insights from data has become even easier with the advent of analytics platforms. These platforms use machine learning to analyse data.

The jobs of humans in this case is only to act on the actionable insight.

Whether they abide by it or deny it, it is upto them.

Problems with analyzing data

Analytics must be able to use both structured and unstructured data to deliver results.

Analyzing structured data can be however pretty useful. This data has been produced by human beings through calls and entered into data entry forms embedded in computer software. So, this data is entered into a database with fields and can be easily analyzed by a machine learning algorithm.

Using unstructured data is quite a challenge. It’s because this data can consist of calls, social media comments. So, this data first need to be converted into structured data and stored in a database. This is a huge problem because a majority of the data is in this format. A business intelligence platform can be used to create actionable insights from this data. Such a platform must be used which can collect data from different sources.

How to get actionable insight from the data?

Before you decide to derive actionable insight, it’s important to formulate certain questions to which you need answers. Also, deriving a conclusion from a dataset might not be right if that was not its scope.

Data collection methods have problems. For example, there can be log files indicating that customers spent the most time on a feature in a website. But this might be not due to the popularity of the feature but its inability to be used.

Once you have understood the scope of the data, the next part is to prepare a hypothesis and test it through the data. This is where the questions business has constructed before analyzing data can come to use. If any of the hypothesis tests true, then that can be actionable insight derived through the data.

 

Follow us:
EMAIL
ALSO READ:  How to get a client for an elearning course?

Write a Comment

× How can we help you? Available on SundayMondayTuesdayWednesdayThursdayFridaySaturday

DSLR stands for Digital single-lens reflex camera. It has a digital imaging sensor. In this kind of camera, the captured image can be viewed in the viewfinder when the shutter button is pressed. Its shown through the main lens rather than through a secondary lens, so the user knows what has been captured. 

He was a German psychologist who is known for discovering the forgetting curve. According to this curve, the biggest decline in memory happens within 20 minutes, and then 1 hour.