Targeted Consumer Offers for Inventory Turnover
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Solution Overview
Problem
Existing marketing strategies for industries with fixed capacity and uneven demand patterns, such as restaurants and hotels, often result in excess inventory during low-demand periods, which are not effectively utilized due to broad-based discount approaches with low success rates.
Innovation Solution
A system that utilizes extensive data mining of consumer and merchant data to predict demand patterns and offer customized discounts to cardholders based on their preferences, demographics, and shopping habits, shifting demand from peak to non-peak periods and locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If broad-based discounts are offered to spur demand during low-demand periods, then demand may increase, but the success rate is low and excess inventory is not effectively utilized
Solution Approach 1:
The patent segments the customer base into distinct groups based on their purchasing behavior, preferences, and responsiveness to promotions. By analyzing historical data and customer profiles, the system identifies specific segments most likely to respond to discounts during low-demand periods, rather than offering broad-based discounts to everyone. This segmentation increases the success rate by targeting only those customers who are most likely to convert the offer into actual purchases.
Solution Approach 2:
The patent applies local quality by customizing discount offers to match the specific preferences, needs, and purchasing patterns of individual customer segments or local markets. Instead of a uniform discount strategy, the system tailors promotional parameters (discount magnitude, timing, product selection) to the local characteristics and customer profiles of specific geographic areas or customer groups, thereby improving the effectiveness of inventory clearance efforts.
2Adaptability or versatility
If broad-based discounts are offered to existing customers or individuals geographically located near the merchant, then notification is limited, but the ratio of offers to acceptances remains high
Solution Approach 1:
The system segments the potential customer base into highly targeted groups based on multiple criteria including purchasing history, preferences, demographics, and geographic location. This segmentation allows the merchant to send a smaller number of highly targeted offers to the most promising customers rather than sending broad-based discounts to everyone, improving the offer-to-acceptance ratio while maintaining precision in targeting.
Solution Approach 2:
The patent changes the parameters of customer targeting by moving from broad-based criteria (geographic location only, or all existing customers) to multi-dimensional criteria that include purchasing behavior patterns, product preferences, temporal patterns, and demographic characteristics. This parameter transformation enables precise identification of the optimal customer subset for each promotional campaign, reducing the total number of offers needed while increasing acceptance rates.
Data Source
AI summary
Consumer, merchant, and transactional data from a closed loop network and external sources may be leveraged to increase demand of a merchant's inventory during normally low-demand periods. Extensive data mining is used to determine the excess merchant inventory and demand patterns at different times and different locations for merchants and groups of merchants. Similar data mining is used to analyze cardmember demand patterns to identify the cardmember preferences regarding when and where they which to purchase goods and/or services. Cardmembers may also be grouped based on their demand patterns. Using pricing as a lever, cardholders with specific preferences are targeted to shift the demand from peak periods and locations to non-peak periods and locations, and to increase the non-peak demand by location as well as time period. Higher precision may be obtained using product level transaction data from point-of-sale terminals used by merchants wherever applicable.