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Through Recency-Frequency-Monetary model and Managerial Segmentation machine learning model with Python

To be a successful marketing professional nowadays, marketing analytics is a must-have technique. Therefore, the marketing experts with the economic and statistical background are generally regarded as a definite advantage over the others. But regardless of your backgrounds, there is still one easy analysis technique that you can make use of — the RFM (Recency-Frequency-Monetary) model.

RFM analysis is a marketing analysis tool used to determine which of your customers are the best ones. The RFM model is based on 3 quantitative factors: First it is Recency (R), which shows how recent a customer has purchased; then Frequency (F), which…


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To excel data analysis/data science/machine learning in Python, Pandas is a library you need to master. Here is a cheat sheet of some of the most used syntax that you probably don’t want to miss.

The Pandas package is the most imperative tool in Data Science and Analysis working in Python nowadays. The powerful machine learning and glamorous visualization tools may have drawn your attention, however, you won’t go anywhere far if you don’t have good skills in Pandas.

So today I gathered some of the most used Pandas basic functions for your reference. …


Basic data visualization and prediction with the saved model and pipeline in the end

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Churn is an important topic and sales and marketing. It is particularly important for company providing subscription services, like Apple Music, or Amazon Prime, and long-term services like the saving account or investment service of the banks.

However, what is Churn Analysis? And why is it so important? And how do we do it with Python and big data?

Customer Churn Analysis

The purpose of customer churn analysis is to understand the underlying reasons of the quitting customers more in order to reduce the churn and improve the sales. Through the analysis, generally, we will find out what causes the leaving of the…


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According to techrepubic.com, the top 3 most talked skills in job postings for data science position are:

  1. Python (72%)
  2. 2. R (64%)
  3. 3. SQL (51%)

Python is for sure indispensable, while SQL skill comes the 3rd. As a data analyst, I can’t imagine any day we live without python and SQL.

Therefore, it never hurt to practice SQL, and to master it; and in fact, you need it in almost all data analyst job interviews. (Therefore, our exercises are not just ordinary SQL questions, they are SQL interview questions from the real world I gathered online. So that you don’t…


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According to techrepubic.com, the top 3 most talked skills in job postings for data science position are:

  1. Python (72%)
  2. 2. R (64%)
  3. 3. SQL (51%)

Python is for sure indispensable, while SQL skill comes the 3rd. As a data analyst, I can’t imagine any day we live without python and SQL.

Therefore, it never hurt to practice SQL, and to master it; and in fact, you need it in almost all data analyst job interviews. (Therefore, our exercises are not just ordinary SQL questions, they are SQL interview questions from the real world I gathered online. So that you don’t…


Free SQL Exercise (Real Interview Questions) with Data Set and Answer — Salesforce (Easy) Part 2 Photo by XPS on Unsplash

In case you missed Part 1: Free SQL Exercise (Real Interview Questions) with Data Set and Answer — Salesforce (Easy) Part 1.

According to techrepubic.com, the top 3 most talked skills in job postings for data science position are:

  1. Python (72%)
  2. 2. R (64%)
  3. 3. SQL (51%)

Python is for sure indispensable, while SQL skill comes the 3rd. As a data analyst, I can’t imagine any day we live without python and SQL.

Therefore, it never hurt to practice SQL, and to master it; and in fact, you need it in almost all data analyst job interviews. (Therefore, our exercises…


Photo by Austin Distel on Unsplash

According to techrepubic.com, the top 3 most talked skills in job postings for data science position are:

1. Python (72%)

2. R (64%)

3. SQL (51%)

Python is for sure indispensable, while SQL skill comes the 3rd. As a data analyst, I can’t imagine any day we live without python and SQL.

On any ordinary day, a data analyst or market analyst might use SQL queries to pull data from his company database, or then use Python skills to analyze the retrieved data, and at last will report the interesting stories found to the decision makers or stakeholders.

It’s a…


關鍵績效指標(英語:Key Performance Indicators,即KPI,是指衡量一個管理工作成效最重要的指標,是一項數據化管理的工具)會告訴您您的業務是否步入成功之路,或者偏離路線並需要糾正。
關鍵績效指標(英語:Key Performance Indicators,即KPI,是指衡量一個管理工作成效最重要的指標,是一項數據化管理的工具)會告訴您您的業務是否步入成功之路,或者偏離路線並需要糾正。
這4個財務KPI,每個公司的管理人都應該要知導 Image source:Carlos Muza on Unsplash

這4個財務KPI,每個公司的管理人都應該要知導 Image source:Carlos Muza on Unsplash

關鍵績效指標(英語:Key Performance Indicators,即KPI,是指衡量一個管理工作成效最重要的指標,是一項數據化管理的工具)會告訴您您的業務是否步入成功之路,或者偏離路線並需要糾正。雖然我本人覺得不應該盡信KPI,但是也不能沒有,所以,如果你是公司管理人,又或是想投資這公司,這四個 financial 上的 KPI 指標你一定要知道。

1.收入/銷售額(Revenue/Sales)

就是您一單賺幾多錢,使用此KPI時,我建議你都要睇每月銷售額(sales) ,及check下您的收入增長率(revenue growth rates)。 按產品或地區劃分總體收入是很有用的(例子: 右下角的visualiz …

Lorentz Yeung

Founder of El Arte Design and Marketing, Certified Digital Marketer, MSc in Digital Marketing (University College of Dublin)

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