Location-Based Offer Engine for Mobile Banking Engagement
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Solution Overview
Problem
Current mobile banking applications experience inconsistent usage and offer presentation, failing to effectively drive business back to banking entities, resulting in customer disengagement and missed sales opportunities for merchants.
Innovation Solution
A system that generates and presents location-based and time-sensitive electronic offers to customers through a mobile device, utilizing a recommendation engine to identify relevant merchants and offers based on customer characteristics, with a time expiration to encourage immediate action, thereby enhancing customer engagement and loyalty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional mobile banking applications present offers to customers, then offers are transmitted to customers, but customer engagement is low and offers do not effectively drive business back to banking entities
Solution Approach 1:
The system transitions from generic offers to location-specific and transaction-specific offers. By determining the customer's current location and analyzing recent transaction data, the system presents offers tailored to the customer's immediate context, making the offers more relevant and increasing engagement likelihood.
Solution Approach 2:
The system performs preliminary analysis of customer transaction history and current location before presenting offers. This pre-processing of customer data enables the system to anticipate customer needs and present pre-selected relevant offers, improving both engagement and business drive effectiveness.
2Loss of time
If mobile banking applications send offers to customers, then offers are delivered, but offers lack time sensitivity and customers do not act on them
Solution Approach 1:
The system implements time-sensitive offers with expiration deadlines. Offers are presented with specific time windows for redemption, creating a sense of urgency that motivates customers to act immediately rather than delaying response, thereby capturing sales opportunities that would otherwise be lost.
Solution Approach 2:
The offer system transitions from static, long-term offers to dynamic, time-limited offers. The expiration timestamps and urgent messaging create a dynamic environment where offers have evolving value over time, encouraging immediate customer action and improving sales capture.
3Device complexity
If generic offers are presented to all customers, then offer distribution is simple, but offers do not complement or effectively drive business back to particular banking entities
Solution Approach 1:
The system analyzes customer-specific transaction data and location information to present offers tailored to each customer's recent activities and current context. This customization ensures offers are relevant to the customer's needs and effectively drive business back to participating merchants, transforming generic distribution into targeted presentation.
Solution Approach 2:
The system uses feedback from customer transaction history and behavior patterns to refine offer selection. By continuously learning from customer responses and transaction data, the system improves offer relevance over time, enhancing business drive effectiveness without proportionally increasing system complexity.
4Adaptability or versatility
If location-based offers are implemented, then offer relevance to customer context improves, but system complexity increases due to location tracking and merchant identification
Solution Approach 1:
The system introduces a recommendation engine as an intermediary component that handles the complex tasks of location analysis, merchant identification, and offer selection. This modular approach encapsulates the complexity in a dedicated subsystem, making the overall system more manageable while delivering highly relevant location-based offers.
Solution Approach 2:
The offer system is segmented into distinct functional modules: location determination, transaction analysis, merchant identification, and offer presentation. This segmentation isolates complexity into manageable components, allowing each module to be optimized independently while maintaining overall system adaptability and offer relevance.
Data Source
AI summary
The invention relates to electronic offers in a mobile banking application. An embodiment of the present invention is directed to a system that provides relevant offers for customized deals to a customer responsive to a current customer transaction, current location and/or other profile information. The relevant offer may be available for a limited time. The customer's response (e.g., save, redeem, skip, ignore, etc.) may then be used for more relevant offers in the future.