Customer Analytics/ Business Analytics Study Roadmap

Tool Part (Only for Mac user)

  • Anaconda — Jupyter Notebook (for Python)
  • Google Colab (for Python and Deep Learning)
  • Quiver (Best Snippet and notebook for code)
  • Data Graph (Paid Software)
  • Sublime Text (Best Code Editor)
  • Rstudio
  • MySQL Workbench
  • Jupyter Notebook Viewer
  • Kite(Help you deal with parameters when coding)
  • Sawtooth Questionnaire and Conjoint Analysis
  • Digital Marketing Toolbox please view my LinkedIn post here.

Tech Part & Theory Part

Python & Data Science

  • List,Dictionary & Tuple
  • File IO
  • List Comprehension
  • Pandas Data Wrangling
  • NumPy manipulation(For Data Science purposes)
  • Data Visualization
  • (Path: Matplotlib -> Seaborn ->ggplot/pyplot)

SQL and Database

  • ER diagram
  • Select From Where
  • Logical, Sorting, Removing
  • Aggregation
  • Null Values
  • JOIN(Cartesian, Inner, Natural, Self, Outer)
  • Subquery
  • Operators(Set, All&Any, Exist, Case-When, Ceiling)
  • Create New Database(Create, Update)

Data Structures and Algorithms

Big Data & Cloud Computing

  • Linux Basics (Bash Coding, HDFS)
  • Hadoop Tools(Hive, Impala, Pig)
  • MapReduce
  • PySpark(Most popular for job hunting purpose as I see)
  • Cloud Computing Tools [AWS and GCP(Google Cloud Platform)]

Prescriptive Analytics

  1. Min Cost/Max Profit
  2. Route Choosing
  3. Shipping Choosing
  4. Cash Flow
  5. Sensitivity Analysis
  1. Python Optimization With Pulp (For Linear)
  2. Mixed Integer Optimization with SciPy (For Nonlinear)

Predictive Analytics

  1. Resampling
  2. Bootstrap & Resampling
  3. Regularization
  1. Linear Regression (LASSO & RIDGE)
  2. Logistic Regression
  3. LDA&QDA
  • Decision Trees, Bagging & RandomForest & Boosted Trees
  • Support Vector Machine
  • Neural Network
  • Hierarchical Clustering
  • K-Means Clustering

Deep Learning

  • RNN/CNN building and hyperparameter tuning.
  • Keras transfer learning
  • NLP(Natural Language Processing) with Keras.
  • Time Series analysis.

Text Mining

  • Text Preprocessing
  • Feature Engineering(Bag of Words, TF-IDF, Ngrams, Word2Vec)
  • Text Classification
  • Topic Modeling
  • Sentiment Analysis

A/B Testing

  • Prediction v.s. Causation
  • Obstacles to Causality(for example, sample bias)
  • Potential Outcome(ATE-Average Treating Effect)
  • Quantifying Uncertainty(Variance, Confidence Interval)
  • Blocking & Clustering
  • Regression Analysis
  • Heterogeneous Treatment Effect(HTE)
  • Noncompliance
  • Regression Discontinuity Design
  • Difference in Difference (DiD)— Reflection on Measuring Impact

Business Part

Marketing Research

  • Backward Marketing Research
  • Types of Researches
  • Measuring Preferences
  • Segmentation
  • Market Simulation
  • Conjoint Design

Customer Analytics

  • Basic Analytics
  • Prospecting and Targeting the Right Customer with ML models
  1. Logit
  2. Decision Tree & Random Forest
  3. Neural Network
  • Developing Customers
  1. Recommendation System(from reviews, ratings, etc)
  • Retain Customers
  1. Predicting Attrition

Brand Management

  • Industry Level Primary Demand Assessment (BASS Model & GBM)
  • Brand Level Competition and Market Structure (Factor Analysis & Perceptual Map)
  • Brand Level Demand Models(Scan Pro Model & Advertising Response Model)
  • Brand Level Diffusion (Logit Model)

Digital Marketing

  • Personas & Digital Profiles
  • Paid Search Advertising
  • Paid Media Integration
  • Content Marketing
  • Social Media Marketing
  • Marketing Automation (Email & Social Media)
  • Channel Integration(Manager Level)

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Sean Zhang

Sean Zhang

Data Science | Machine Learning| Data Engineer