Personalized Promotional Offers via Marker Interaction
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Solution Overview
Problem
Online marketplaces face challenges in delivering promotional offers to users with minimal user input requirements, as existing methods often require sign-ups or personal information, and demographic targeting can be ineffective, leading to reduced campaign effectiveness and user engagement.
Innovation Solution
Implementing a system that dynamically determines personalized promotional offers using markers, where user interactions with markers on websites or physical objects trigger personalized offers based on user history, minimizing input requirements and enhancing user experience by associating offers directly with user accounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If promotional offers are provided based on general user demographics, then campaign coverage is improved, but effectiveness with users who do not fit the targeted demographic profile deteriorates
Solution Approach 1:
The system transitions from uniform demographic targeting to personalized offer delivery by analyzing individual user histories and behaviors. Each user receives promotional offers tailored to their specific interests and past interactions, rather than applying a single demographic-based approach to all users. This localizes the marketing quality to match individual user characteristics.
Solution Approach 2:
The system performs preliminary analysis of user histories, browsing patterns, and past interactions before delivering promotional offers. By pre-processing user data and identifying relevant patterns in advance, the system can immediately present personalized offers when users interact with markers, eliminating the need for users to fit predetermined demographic profiles.
2Reliability
If users are required to sign up for a service or provide personal information to receive promotional offers, then user account association is improved, but user input requirements and friction increase
Solution Approach 1:
The system enables users to receive and redeem promotional offers through marker interactions without requiring traditional sign-up processes. Users simply interact with markers (e.g., scanning QR codes, clicking digital markers) to receive offers that are automatically associated with their user accounts through their device or browser identity, eliminating the need for manual information provision.
Solution Approach 2:
The system uses device identifiers, browser cookies, or temporary session tokens as intermediaries to associate promotional offers with user accounts without requiring users to directly provide personal information. This intermediary mechanism bridges the gap between anonymous marker interaction and personalized offer delivery while maintaining account association.
3Reliability
If promotional offers are delivered through traditional methods requiring user sign-ups, then user account creation is improved, but user engagement and campaign effectiveness deteriorate
Solution Approach 1:
The system inverts the traditional marketing funnel by delivering promotional offers first through marker interactions, then associating them with user accounts in the background. Instead of requiring users to create accounts before receiving offers, the system provides offers immediately and handles account association subsequently, reversing the conventional sequence to prioritize user engagement.
Solution Approach 2:
The system replaces the mechanical process of manual sign-up and account creation with automated digital identification methods. Users are identified through device fingerprints, browser characteristics, or temporary tokens generated during marker interaction, substituting the traditional account creation mechanism with a seamless automated recognition system that maintains reliability without increasing friction.
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for dynamically determining personalized promotional offers using markers. In one embodiment, an example method may include determining a first user history associated with a first user account and a second user history associated with a second user account, the first user history and the second user history being indicative of respective interactions by a first user and a second user with a marketplace, receiving an indication of interaction by the first user with a marker associated with a promotional offer campaign, determining, using the first user history, a first promotional offer for the first user, associating the first promotional offer with the first user account, receiving an indication of interaction by the second user with the marker, determining, using the second user history, a second promotional offer for the second user, and associating the second promotional offer with the second user account.