ALM Media, LLC
British Gas
Mosaic Insurance
Oxford Nanopore Technologies
WS Audiology (WSA)
Kiwi.com
Flight Centre
Healius Pathology
Varo Bank
Yorkshire Building Society Group (YBS)
Sharang Patil, Director of Group Finance Excellence
United Airlines
GFG Alliance
Energy Australia
Delaware North
Moneycorp
Prodigy Finance
M&T Bank
Minerals Technologies Inc. (MTI)
Church's Chicken
Oct 16, 2017
AUTHOR(s)
A WNS Perspective
A global retail chain was looking to strategically target previous buyers of a seasonal product to drive sales volumes
WNS used propensity modeling to accurately divide the company’s entire loyalty member base into granular segments
The retail chain rolled out hyper-personalized offers to these segments resulting in a 200 percent increase in sales
The right insights enable companies to understand customer behavior, communicate more effectively and increase loyalty. Analytics can help companies glean such insights to develop the right cross-selling and upselling campaigns.
To drive the sales volumes of a seasonal product and enhance its visibility among loyal customers. Prior attempts to target previous buyers of the product with simple promotional campaigns had failed to deliver the desired results. The company leveraged WNS’ analytics expertise to build an effective solution.
WNS developed a sophisticated customer segmentation framework to enable the client to launch hyper-personalized campaigns for the product. Robust statistical tools were deployed to glean qualitative insights.
Through Exploratory Data Analysis on the previous year’s transactions related to the product, WNS identified characteristics that differentiated the typical buyers from non-buyers. An analytical model was deployed across the retailer’s entire loyalty base to predict purchase behaviors for the larger population.
The retail chain’s entire loyalty base was divided into 17 granular segments. Targeted promotional offers, based on the revenue objectives, were identified for each segment. Keeping in mind the client’s need to minimize the number of promotional e-mails, similar segments were clubbed and tailored offers were launched for each group.
Post the campaign rollout, parameters, including response rate, incremental revenue generated and the number of buyers, were measured using control and test groups.
That propensity modeling can achieve accurate customer segmentation, which can be effectively used to boost loyalty and sales.
The WNS approach enabled the retail chain to:
Better target prospective buyers of the product
Get stellar response to the personalized promotional offers
Achieve a 200 percent increase in the loyalty purchase of the product compared to the previous year
WNS’ proprietary model continues to be used to launch promotional offers for the product as well as another popular seasonal item. WNS also continues to support the retail chain in its marketing efforts.
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