Imagine how an organization can gain competitive advantage and add value to customers if they are able to predict what customers want, have a clear insight on how they act and react, and how they behave on different platforms and devices.
Behavioural Analytics provide businesses with the ability to predict someone’s personality and behavioural traits. This provides opportunities for organisations to target their advertising and enable businesses / organisations to segment customers according to their personality type. Recent studies found that personalization has allowed businesses to achieve higher conversion average and stronger lead acceptance rate. By leveraging on extensive data collected at every stage of the consumer journey, Businesses can even find out what really drives consumers into making a purchase.
Leading Multinational Companies like Amazon, Apple Google are utilizing Behavioural Analytics to tailor their brand strategies, marketing campaigns, and customer services to meet the expectation of consumers, and optimize customer experience. In fact, it has been reported that close to 35% of Amazon’s revenue are generated by their recommendation engine. Such strategic use and implementation of insights to map products and services has also been a key driver behind the successes of Facebook, Uber, Grab to name a few, in terms of revenue and customer satisfaction.
- Duration: 1 Day / 8 Hours
- Who Should Attend: Business Development Professionals, Customer Service Professionals, Sales and Marketing Professionals, Executives, Business Owners and Anyone who are interested in Behavioural Analytics, and how to implement HR Analytics in their organization.
Behavioural Analytics Essentials (BeAE) is designed for participants interested in acquiring fundamental and essential knowledge on how to leverage on Behavioural Analytics to uncover insights based on consumer behaviour.
Participants will receive a Certificate of Completion upon successfully completing the course
Module 1 Introduction to Analytics
- Types of Analytics
- Behavioural Economics
- Psychology vs Analytics
- Segmentation techniques
- Predictive models
Module 2 Data Exploration
- Population vs. Sample
- Types of Data Variables
- Summarizing data
- Describe measure of central tendency/measure of location of data set
- Describe spread/variability of data set
- Symmetry and Skewness for the distribution of a data set
- Data Collection
- Outlier Treatment
Module 3 Analyzing Customers’ Behaviour
- Customer Analytics
- Introduction to Tools and Software commonly used in Analytics
- Logistic Regression
- Decision Trees
- K-means Clustering
- Association Rules
- Market Basket Analysis in Retail Industry
- Affinity Rule