Case Studies Luxury Ecommerce Retailer Improves Promotional Offers and Increases Customer Loyalty with Advanced Analytics

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	Luxury Ecommerce Retailer Improves Promotional Offers and Increases Customer Loyalty with Advanced Analytics

Luxury Ecommerce Retailer Improves Promotional Offers and Increases Customer Loyalty with Advanced Analytics

Technology Category	Analytics & Modeling - Data Mining Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	E-Commerce Retail
Applicable Functions	Business Operation Sales & Marketing
Services	Data Science Services System Integration Training
Challenge	A luxury e-commerce retailer based in Singapore was facing challenges in garnering repeat business and inspiring customer loyalty. Despite having a successful business operation across 8 neighboring countries, the company struggled to earn repeat business from customers, which is a common issue in the luxury retail sector where purchases are often discretionary and infrequent. The company had a wealth of customer data available through account creation and Facebook login, but this data was not being effectively utilized. They needed an analytics program to leverage this data for personalized customer engagement, a recommendation engine, and tailored offers to boost customer loyalty and optimize revenue. Read More
About Customer	The customer is a Singapore-based e-commerce luxury retailer specializing in high-end designer brands. The company has grown its business operations across 8 neighboring countries and enjoys success in the region. However, like many luxury retailers, they face challenges in earning repeat business from customers due to the discretionary nature of luxury purchases. The company collects extensive buying and activity data from customers who create free accounts or log in using Facebook credentials. Despite having this data, it was not being effectively utilized to engage customers and drive repeat business. The company sought to implement an advanced analytics program to address this issue and improve customer loyalty. Read More
Solution	Antuit was engaged to design and deploy a marketing analytics framework and predictive model to improve customer engagement and loyalty. They began by segmenting the retailer’s customers using Recency-Frequency-Monetary (RFM) scoring, which ranks customers based on the time spent on the site, frequency of visits, and money spent. From these RFM models, Antuit identified four distinct customer clusters and created Purchase Propensity models to understand the purchasing behavior of each segment. They also set up a Customer Migration Matrix to pinpoint customers worth retaining. Antuit then implemented a test and control framework to monitor the effectiveness of the analytics solution. Once the segmentation and profiling were complete, Antuit collaborated with the client to create new marketing campaigns with tailored offers and promotions for the targeted segments. They advised the company on the types of promotions to engage their most active customers, including exclusive previews of select items for the most valuable customers. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Data Mining

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

E-Commerce

Retail

Applicable Functions

Business Operation

Sales & Marketing

Services

Data Science Services

System Integration

Training

Challenge

A luxury e-commerce retailer based in Singapore was facing challenges in garnering repeat business and inspiring customer loyalty. Despite having a successful business operation across 8 neighboring countries, the company struggled to earn repeat business from customers, which is a common issue in the luxury retail sector where purchases are often discretionary and infrequent. The company had a wealth of customer data available through account creation and Facebook login, but this data was not being effectively utilized. They needed an analytics program to leverage this data for personalized customer engagement, a recommendation engine, and tailored offers to boost customer loyalty and optimize revenue.

About Customer

The customer is a Singapore-based e-commerce luxury retailer specializing in high-end designer brands. The company has grown its business operations across 8 neighboring countries and enjoys success in the region. However, like many luxury retailers, they face challenges in earning repeat business from customers due to the discretionary nature of luxury purchases. The company collects extensive buying and activity data from customers who create free accounts or log in using Facebook credentials. Despite having this data, it was not being effectively utilized to engage customers and drive repeat business. The company sought to implement an advanced analytics program to address this issue and improve customer loyalty.

Solution

Antuit was engaged to design and deploy a marketing analytics framework and predictive model to improve customer engagement and loyalty. They began by segmenting the retailer’s customers using Recency-Frequency-Monetary (RFM) scoring, which ranks customers based on the time spent on the site, frequency of visits, and money spent. From these RFM models, Antuit identified four distinct customer clusters and created Purchase Propensity models to understand the purchasing behavior of each segment. They also set up a Customer Migration Matrix to pinpoint customers worth retaining. Antuit then implemented a test and control framework to monitor the effectiveness of the analytics solution. Once the segmentation and profiling were complete, Antuit collaborated with the client to create new marketing campaigns with tailored offers and promotions for the targeted segments. They advised the company on the types of promotions to engage their most active customers, including exclusive previews of select items for the most valuable customers.

Impact #1	The implementation of the Antuit solution led to an improvement in marketing ROI in the range of 5-20% across the company's portfolio in the first market that went live in Singapore.
Impact #2	The newly designed, analytics-backed campaigns helped improve customer stickiness and engagement.
Impact #3	The solution enabled the company to measure the true lift of its promotional campaigns, providing valuable insights for future marketing strategies.

Impact #1

The implementation of the Antuit solution led to an improvement in marketing ROI in the range of 5-20% across the company's portfolio in the first market that went live in Singapore.

Impact #2

The newly designed, analytics-backed campaigns helped improve customer stickiness and engagement.

Impact #3

The solution enabled the company to measure the true lift of its promotional campaigns, providing valuable insights for future marketing strategies.

Benefit #1	Marketing ROI improved by 5-20% in the first market that went live in Singapore.

Benefit #1

Marketing ROI improved by 5-20% in the first market that went live in Singapore.

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Overview

Luxury Ecommerce Retailer Improves Promotional Offers and Increases Customer Loyalty with Advanced Analytics

Operational Impact

Quantitative Benefit