Database Sampling for Marketing Recipient Count Analysis
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Solution Overview
Problem
Marketers face significant challenges in efficiently querying large databases to determine the number of potential recipients for targeted marketing promotions due to the prohibitive costs, time, and computing resources required, especially when dealing with vast amounts of recipient and transaction data.
Innovation Solution
A method and system that utilize database sampling and probability to analyze records by querying a recipient database and a sampling transaction database, intersecting results, and extrapolating an approximate count based on the total number of records, reducing the data analyzed and operations needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate queries are executed against recipient database and transaction database to determine potential recipient count, then accurate count is obtained, but cost, time and computing resources become prohibitive
Solution Approach 1:
The patent applies partial action by executing queries against a sampled subset of the transaction database rather than the complete database. A sampling ratio is applied to select a representative portion of transactions, which when intersected with recipient data and extrapolated, provides an approximate count that is sufficiently accurate for marketing decisions while dramatically reducing query execution time and computational resource consumption.
2Manufacturing precision
If complete database queries are executed to fine tune marketing communications, then precise targeting is achieved, but the number of queries that can be effectively executed is significantly reduced
Solution Approach 1:
The system enables marketers to execute multiple iterative queries with different targeting criteria by sampling only the necessary portion of transaction data for each query. This partial action approach allows for fine-tuning of marketing communications through multiple exploratory queries, each operating on a manageable sample size rather than the complete database, thereby increasing the volume of queries that can be effectively executed.
Solution Approach 2:
The patent implements preliminary action by pre-computing and maintaining sampled subsets of transaction data that can be quickly queried. This preliminary preparation of sampled data structures enables rapid iterative querying for marketing optimization without repeatedly processing the entire transaction database, thus supporting higher query volumes for fine-tuning campaigns.
3Loss of information
If transaction data is continuously accumulated over time, then valuable purchasing habit information is obtained, but the size of transaction data grows quickly requiring more resources
Solution Approach 1:
The patent applies the extraction principle by separating a representative sample of transaction data from the complete transaction database. Instead of processing or storing all transaction data for analysis purposes, the system extracts a sampled subset that contains sufficient information to derive meaningful insights about purchasing habits while requiring significantly less storage space and computational resources for querying and analysis.
Data Source
AI summary
A method for analyzing database records using sampling includes querying a recipient database for recipients with attributes that match one or more specified recipient attributes, querying a sampling database for transactions with attributes that match one or more specified transaction attributes, where the sampling database stores a subset of transactions that are also stored in a transaction database, intersecting the recipients resulting from the querying of the recipient database and the transactions resulting from the querying of the sampling database based on attributes thereof to create a set of joined sample results, and determining an approximate full count value by extrapolating a count value associated with the set of joined sample results based on both a total number of recipients in the recipient database and a total number of transactions in the transaction database.