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In the face of stiff competition, a leading global hotel chain looked to identify new opportunities to generate additional revenue from its existing loyalty program members
WNS developed an analytical solution that mined demographic and transactional data from multiple data sources, identified variables impacting ‘share of wallet’ and applied regression techniques to accurately map the variables to the ‘size of wallet’
The client, a leading global hotel chain with a multitude of hotels operating under separate brands, was running a profitable loyalty program. In the face of stiff competition, the hotel chain aimed to identify new opportunities that could generate additional revenue from its existing loyalty program members.
The WNS Solution
Traditionally, hotel chains emphasize estimating the 'share of wallet' in monetary terms. Share of wallet is a percentage of the total number of nights that loyalty members spend in the client's hotels compared to those of competitors. It helps identify loyalty program members who are highly responsive to promotional offers.
In contrast to this approach, WNS recommended estimating the 'size of wallet' in monetary terms. Size of wallet is the total number of nights that loyalty members would willingly avail of in any hotel chain. This would help identify additional revenue opportunities from existing loyalty program members.
WNS then implemented the following steps:
Mined demographic and transactional data from multiple data sources such as the client, its competitors and WNS' proprietary resources
Identified variables impacting the size of wallet, both positively and negatively
Applied linear regression techniques to accurately determine the relationship between variables impacting the size of wallet
These steps enabled WNS to identify the client's loyalty program member categories with a large size of wallet.
Through the analysis, WNS accurately predicted loyalty member categories that could be targeted for generating additional revenue.