In-Store Ad Customization via BLE Beacons
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Solution Overview
Problem
Traditional in-store advertisements are static and lack specificity, failing to effectively capture the attention of all customers, as they often include general content that does not cater to individual preferences or demographics.
Innovation Solution
A system that detects and checks-in users within a merchant's store, retrieves their preferences, and customizes advertisements based on transaction history, location, and movement, using Bluetooth Low Energy (BLE) beacons to deliver personalized promotions and offers in real-time, considering user importance and context such as age restrictions and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static advertisements with general content are displayed in-store, then the advertisement coverage is broad and can be seen by all customers, but the advertisement effectiveness is low because it lacks specificity and cannot capture the attention of all types of customers
Solution Approach 1:
The patent transforms static advertisements into dynamic, real-time personalized advertisements. The system continuously updates advertisement content based on real-time customer data including location, movement speed, and historical behavior patterns, allowing the advertisement to adapt its content and delivery timing dynamically rather than remaining fixed
Solution Approach 2:
The patent applies local quality by customizing advertisement content specifically for each customer based on their individual characteristics and real-time state. Instead of using uniform general content for all customers, the system creates personalized advertisement variants tailored to each customer's preferences, location within the store, and behavioral patterns
2Productivity
If personalized advertisements are implemented using real-time data detection, then the advertisement effectiveness is improved by capturing customer attention, but the device complexity increases due to multiple sensors and data processing requirements
Solution Approach 1:
The patent applies universality by designing a multi-functional integrated system where a single device or platform performs multiple functions: detecting customer location, measuring movement speed, retrieving historical data, analyzing behavior patterns, and delivering personalized advertisements. This consolidates what would otherwise require multiple separate systems into one unified solution
Solution Approach 2:
The system implements self-service by automatically performing data collection, analysis, and advertisement delivery without requiring manual intervention. The system autonomously retrieves customer data from historical records, analyzes behavior patterns, determines optimal advertisement content, and delivers it in real-time based on detected customer state
3Adaptability or versatility
If real-time data collection and analysis is performed for each customer, then the advertisement customization is improved, but the loss of time increases due to data processing delays
Solution Approach 1:
The patent applies preliminary action by pre-processing and storing customer data in historical records before actual advertisement delivery is needed. Customer information including preferences, purchase history, and behavior patterns are collected and analyzed in advance, creating ready-to-use data structures that can be quickly retrieved and applied when a customer enters the store, eliminating the need for real-time analysis from scratch
Data Source
AI summary
A system or method is provided to detect and check-in a user at a merchant's store. The system may retrieve the user's preferences and may customize advertisements and/or promotions based on the user's preferences. The customized advertisements may then be presented or displayed to the user as the user browses or shops in the merchant's store. In particular, the customized advertisements may be selected or generated based on the user's transaction history, browsing history, purchase history, pre-defined preferences, and the like. In an embodiment, the system may detect and check-in multiple users at a merchant's location. The system may select or generate advertisements based on multiple users who are visiting the merchant.