With new tools being launched every day, the data industry has become a flourishing, profitable, and promising industry. To work in such a rapidly transforming field, one must be up to date with the latest technology, and hands on hands with the tools required to work. With no further delay, let’s jump to learn… Continue reading Tools required for an efficient data stack
Author: Ranjan Kashyap
I am an Analytics Engineer and CRO expert with a strong background in Data Science & Analytics and Marketing Measurement. I specialize in turning complex datasets into actionable insights, helping businesses enhance efficiency and achieve scalable growth through data-driven strategies.
What is mobile attribution and why it is important?
On a daily basis, an internet user comes across various ads run by various brands before making any purchase. Keeping a track of all these ads is important to know which of them are doing the best so that we can allocate more resources to the relevant ads and generate a bigger customer base.… Continue reading What is mobile attribution and why it is important?
How RFM analysis helps in customer segmentation?
If you think from a customer’s perspective then buying is not an easy process. One undergoes a series of long decisions taken by billions of neuron cells present in the brain and nervous system just to decide whether or not the product is worth the money to be spent. It’s strenuous to even… Continue reading How RFM analysis helps in customer segmentation?
How to track traffic sources in Mixpanel as Google analytics does?
Google analytics has it’s unique way to track traffic sources and attribute your user data to them. Here you can see what I am talking about: Mixpanel by default can only track utm parameters as they have mentioned in their documentation here – https://help.mixpanel.com/hc/en-us/articles/115004561786-Track-UTM-Tags This means that with utm tracking you can track your Google… Continue reading How to track traffic sources in Mixpanel as Google analytics does?
Steps involved in Mixpanel Tracking
Mixpanel implementation includes 4 states: Metrics Discovery (1 to 2 weeks) Technical Tracking Plan (1 to 2 weeks) Implement and QA Data (2-3 weeks) Training or Education (1 to 2 weeks) What is Metric Discovery? Goal: What questions you want to answer from your data. We do this by creating a simple measurement plan… Continue reading Steps involved in Mixpanel Tracking
Facebook Power 5 Strategy: Re imagining Advertising
Facebook, as we all know, is a global platform that can help businesses in brand building. The reach of Facebook is multi-continental and the audience varies in ages, interests, regions, customs, etc. What does this mean? This means that no matter what your business is, it’s a high probability that not only you will find… Continue reading Facebook Power 5 Strategy: Re imagining Advertising
Time Series Forecasting and Prediction
Forecasting and prediction, both are based on probabilities of an event occurring. Although the terms might seem similar, there are some differences between prediction and forecasting. Let’s first understand Prediction. What is a prediction? Prediction is an absolute outcome that we give after understanding the data. For example, a set of 10 people are… Continue reading Time Series Forecasting and Prediction
Multivariate Analysis: Visualizing Dimensions
In the real world, we face many problems where several factors affect a certain outcome. Something as simple as a school result depends upon different subjects (including physical activity) that serve as variables/ factors altogether in deciding the result. A change in any of the subject marks directly affects the result of the student. Multivariate… Continue reading Multivariate Analysis: Visualizing Dimensions
5 Major Statistics Topics Required For Data Science
Data Science is an emerging field that does not belong to a particular subject or study. Instead, data science requires knowledge of different fields of science and research like mathematics, statistics, programming, etc. Statistics play an essential role in data science as most of the analysis in data science is done with statistical abilities. In… Continue reading 5 Major Statistics Topics Required For Data Science
NumPy & Pandas: The most important Data Science Libraries in Python
Python is gaining huge success in the field of data science as a phenomenal tool that can write tough logics in simple codes and get us all the computations in fractions of seconds with its inbuilt features. It can be argued that it is making programmers lazy or helping to grow them by handling little… Continue reading NumPy & Pandas: The most important Data Science Libraries in Python
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