Call Tracking System with Automated Spam Filtering
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Solution Overview
Problem
Existing call tracking systems face challenges in accurately attributing phone calls to advertisements due to the need for multiple phone numbers, which increases costs and the likelihood of spam calls or misdials, leading to distorted data and reduced accuracy.
Innovation Solution
Implementing an automated filtering function, such as CAPTCHA, blacklist, or IVR, to block unwanted calls, and using a pooling algorithm to manage a pool of phone numbers for optimal accuracy and cost, along with sampling algorithms to estimate call distribution across publication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a separate phone number is designated for each advertiser and source, then call tracking accuracy is improved, but system cost and operational complexity increase
Solution Approach 1:
The patent applies universality by enabling a single phone number to serve multiple advertisers and sources through time-based allocation. The system dynamically assigns the same phone number to different advertising campaigns at different times, allowing one number to perform multiple tracking functions rather than requiring dedicated numbers for each campaign.
Solution Approach 2:
The patent implements dynamics through time-based phone number allocation, where the system dynamically assigns and reassigns phone numbers to different advertisers and sources based on temporal patterns. This dynamic allocation allows the system to adapt to varying advertising needs without requiring static dedicated numbers for each campaign.
2Device complexity
If phone numbers are recycled to reduce costs, then system cost decreases, but the likelihood of spam calls and misdials increases
Solution Approach 1:
The patent applies preliminary action by implementing a challenge-response test before allowing calls to be completed. This preliminary verification step checks whether the caller is a legitimate user before the call reaches the advertiser, preventing spam calls and misdials from affecting the system while still allowing phone number recycling.
3Measurement precision
If more phone numbers are used to track multiple advertisers and sources, then call attribution accuracy is improved, but data distortion from spam calls increases
Solution Approach 1:
The challenge-response test serves as a preliminary filter that verifies caller legitimacy before calls are processed. This preliminary action prevents spam calls from entering the tracking system, thereby eliminating data distortion from unwanted calls while maintaining accurate attribution data from legitimate users.
Solution Approach 2:
The challenge-response test acts as an intermediary between the phone number and the advertiser. It mediates the call flow by verifying caller identity before allowing the call to reach its destination, thus protecting the tracking system from data distortion while maintaining accurate measurement capabilities.
Data Source
AI summary
A call tracking system and method that uses an automated filtering function to increase accuracy of call tracking. In some embodiments, the system utilizes a spam blocking module, such as a challenge-response test (e.g., a CAPTCHA), a blacklist for callers sharing certain criteria indicative of robo-dialed or spam calls, or other similar spam filter to block unwanted calls from being routed to an advertiser. By using a spam blocking module, the amount of noise in the call tracking system can be reduced and the attribution of calls correspondingly more accurate. In some embodiments, an interactive voice response (IVR) module is utilized to reduce the noise in the system by filtering or blocking unwanted calls. By utilizing an automated filtering function, the disclosed system improves the accuracy of call tracking and allows advertisers to better track the performance of advertising campaigns that they undertake.