Campaign Management for a Leading Membership Based Retailer
Overview
Customer retention has become the crux of revenue growth today. Personalization is the most effective contributor to customer retention. Personalized marketing makes the customers feel that their preferences are valued. It is also convenient for customers to shop from recommended products rather than hunting for them.
A leading membership-based retail leader partnered with Mu Sigma to improve their customer retention rate. Mu Sigma developed a comprehensive campaign management tool driven by data and insights.
The Problem
The membership-based retail chain was running standard campaigns for all their customers.These campaigns were inefficient and failed to sustain membership renewal rates. Mu Sigma collaborated with the retail chain to diversify its campaigns according to customer needs as retaining existing customers was more economical than acquiring new ones.
To facilitate this, we needed to:
• Understand customer behavior
• Roll out campaigns with customized messaging
• Measure campaign effectiveness to correct course
The goals were to:
• Improve customer retention
• Increase purchase frequency
Decoding the dynamics of personalization is the driving force behind creating a capable marketing engine. We imagined a seamless interplay between fast data retrieval, Machine Learning algorithms, a CRM interface, and external APIs for a holistic solution.
The Mu Sigma Approach
A data science perspective of looking at this problem would yield customer segments, product recommendations, and their operationalization into existing data systems. We approached this from a decision science lens, where we combined math and technology (Data Science) along with business decisions (CRM manager experience, campaign measurement capabilities) to deliver an end-to-end business application ready to facilitate data-driven decision-making. We imbibed design thinking to create a good user experience for CRM managers. Behavioral science was used to understand the end customers’ psyche to co-define the personalization levels along with our client.
Using these, the Mu Sigma team proposed a holistic campaign management app to help the retailer drive and test the personalized marketing initiative. The aim was straightforward: the team would use the Targeted Campaign Management tool to send customized messages, rewards, offers, and recommendations through the member’s preferred mode of interaction.
We focused on building three capabilities:
• Customer segmentation – Sort and target customers for each campaign through a clustering algorithm running every quarter
• Product recommendations – Recommend products that will increase the purchase range of regular and need-based customers
• Automated lifecycle management – Automate outreach with the right messages based on their lifecycle stage
We arrived at a tool design which comprised of:
• A CRM web app – Hub to launch and manage campaigns
• A dashboard – Track and report campaign metrics
• An Integrated data layer – Improve data retrieval for quick responses to changing customer preferences
Together, they added speed and value along the entire chain of data from their legacy database to insight consumption at Marketing Team’s end.
The Solution
The team started by extracting a data warehouse from the larger database to serve the Targeted Campaign Management tool exclusively.
The CRM app communicates directly with this warehouse through a daily refresh to process consumer preferences quickly.
Besides grouping members with similar behavior, the tool uses supervised machine learning algorithms to identify product categories that can be recommended to each member group. As the single source of truth for campaign managers, this tool enables them to synthesize learnings from successful campaigns and use that to roll out other campaigns in a short period.
End-consumers employed the following features of the tool to streamline personalized marketing.
The solution helped end customers to:
• Select custom segments to design personalized campaigns in real-time
• Design targeted personalized campaigns at customer segment level to increase purchase frequency
• Assess the performance of campaigns and compare metrics for effectiveness
• Get customized product recommendations based on customer segments
• Pick personalized communication channels to reach out to customers
• Trigger SMS, MMS, and texts on the region’s preferred messaging platform through integration with external APIs
Unlike most CRM apps, this tool has extensive impact measurement features, including comparisons of campaign effectiveness across multiple channels such as online and brick & mortar.
The tool was also tailored extensively to the retailer’s business requirements, down to the clustering algorithm, which segmented customers into as many segments as they intended.
The Impact
The Targeted Campaign Management tool helped the client:
• Improve customer renewal rate by 2%
• Realize a potential incremental annual revenue of $10M+
• Launch 500 campaigns, +1M members impacted, +80M messages sent/year
Download the case study to know more.