Data Analysis in Product Development

We already know that this is the digital age and decision made based on data. Data is called crude oil or gold for any organization. Yes, you heard it right.

I am sure, you have heard a term called Data Decision Management. It means data brings the value and after analyzing the data, draw some conclusion.

This conclusion brings the predominant decision management for our Products.

Let's understand through one story.

We have known the Coca-cola brand which provides carbonated drinks. Coca Cola is operational in almost all 195+ countries.

Each country has its own food culture and geographical requirement. The same taste could be welcomed in all countries. Let's talk about India only, different states of India has also different food cultures. Each is unique and different.

Coca Cola starts collecting data by analyzing their food ingredients and pattern and then they have made some certain tastes brand for individual states/provinces and it was accepted in that are Indian people likes lime/lemon drinks. Coca-cola brings the carbonated drink which has a similar taste as lime/lemon drinks as Limca and Nimbu Fresh.

For each country, Coca-Cola analyzed using available data and made drinks that are similar to their tastes. These products are super-duper hit and widely accepted.

So, Data Analysis is playing a very important role in Product Development. There are two types of Data.

1. Quantitative data

2. Qualitative data

Quantitative data:

This is also called as Numerical data. It consists of numbers. Using the numbers you can find the hidden pattern and predict for the future. Let's check this sales example.

Year Sales

2015 - 50 Lakh INR

2016 - 60 Lakh INR

2017 - 70 Lakh INR

2018 - 80 Lakh INR

2019 - 90 Lakh INR

2020 - ?

After analyzing the above historical data you can find the pattern. Each year sales increased by 10 Lakh INR so in 2020 it would also increase by 10 Lakh INR and it brings total of 100 Lakh INR.

This is one aspect of analyzing the data. While analyzing data it would consider multiple channels and factors and then validated results would be considered.

Qualitative data:

This is also called as categorical data. If you have used any product and company requested you for the feedback and you gave feedback as "Nice", "Good", "Awesome". It means it brings a positive value.

If you have given feedback as "Bad","Defected","Disgraceful". It means it brings negative feedback values.

Both kinds of data(Quality and Quantity) data are analyzed for understanding the best product-values. Using, these data, improvements are also made to make the wide acceptable product.

Claps for you.

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