S-MALL Overview

Turning Concrete Malls into Smart Malls (S-MALL):
A web-based analytics application for visualizing and mapping in-mall customer journeys and shopping behaviours

Team S-MALL: Chen Yun-Chen | Chiam Zhan Peng | Zheng Bijun

Overview

Proposal

Application

Poster

Reports

ABSTRACT

With growing popularity of e-commerce and online shopping, traditional brick & mortar retail malls are facing stiff challenge and need to reinvent itself and compete with these new “online” channels. As part of the Smart-Nation drive and transformation, retail malls can leverage on this digital transformation journey to find its own unique value preposition with its physical and “offline” presence. With new technologies and connected era like IoT, shoppers are leaving their digital footprints and trackable just like on-line customers.

Retail malls have data such as presence and movement via Wi-Fi access point with customers’ mobile devices, traditional transaction data gathered from daily operations and customers profile data obtained from loyalty programs. The opportunity is to discover patterns and relationship within the data and offer deeper insights, formulate marketing strategies for retail stores and better experience for their customers. This project aims to design and develop a web-based application that provides such analytical visualization. It is developed using open-source R Shiny framework and several R packages such as ggplot2, chorddiag, hexbin, sunburstR, highcharter, arules, visNetwork.

The motivation and objectives will be discussed followed by detailed discussion of the principles, approach and data visualization techniques that are used. Using actual data from a well-known shopping mall, we will demonstrate the functionality of the application in visualizing and discovering the patterns such as peak hour, busy area, movement and customers behavior associated with their profile and transactions. Finally, we will conclude by providing some insights and potential recommendations for their mall operations and strategy.

MOTIVATION

In view of the competitions from online e-commerce channels, there are stronger interests and motivation for key stakeholders in the physical retail malls space to better understand their operations and business so to provide better value and experience for their customers. We will analyze from a Who, What, Why, How approach to better understand in details and frame the objectives of this project.

DATA DESCRIPTION

Expected Outcome

Data Integration: Combine the three dataset to derive patterns, associations and actionable insights

Interactive Visualization:

1. Overview of customers movements patterns by weeks, days, hours
2. Inter-floor movement
3. Customers' profile and transactions integration

Use Cases: Zone Traffic Statistics, Zone Traffic Flow, Staff Planning, Marketing/Event Campaign

Visualization Tool & Packages

R: Hexagonal binning using ggplot2 and Kernel Decimal Estimate using stat_Density2d

R: Chord diagram using chorddiag

R: Shinyapp, shinydashboard, flexdashboard