Automated Lead Scoring Rule Refinement via Historical Conversion Data

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing lead scoring methods are subjective, burdensome, and static, relying on marketers' gut feelings without empirical data, leading to inefficient generation of qualified leads and potential loss of time and money.

Innovation Solution

Automated lead scoring systems that use machine learning algorithms to determine and refine scoring rules based on actual conversion and rejection data from prior leads, adjusting scores dynamically over time to reflect changing activity significance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If marketers manually create lead scoring rules by assigning scores to activities based on experience and gut feelings, then the process is simple to implement, but it is extremely burdensome and time-consuming when there are hundreds or thousands of activities

Engineering Contradiction:

Improveease of creating lead scoring rulesVSAvoidtime spent on manual scoring rule creation

Core Design Contradiction:

Ease of manufactureVSLoss of time

Solution Approach 1:

The system automatically creates and refines lead scoring rules by analyzing historical conversion and rejection data, allowing the system to self-adjust scores without continuous manual intervention. The automated lead scoring system processes activity data and dynamically updates scoring rules based on observed patterns in lead behavior and outcomes.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of score assignment with an automated computational system that uses machine learning algorithms to analyze data and determine optimal scores, substituting human judgment with data-driven automated decision-making.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Ease of manufacture

If marketers manually assign scores to activities based on experience, then the process is straightforward, but the scores are static and fail to account for changes in activity significance over time

Engineering Contradiction:

Improvesimplicity of score assignmentVSAvoidadaptability of scoring rules to changing conditions

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The lead scoring rules are made dynamic through continuous monitoring and adjustment based on incoming conversion and rejection data. The system automatically updates scores as new patterns emerge, allowing the scoring model to adapt to changing lead behaviors and market conditions without manual reconfiguration.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements feedback loops where conversion and rejection outcomes are continuously fed back into the scoring model. This feedback mechanism allows the system to learn from actual results and automatically refine scoring rules, ensuring that scores remain relevant and accurate over time.

Inventive Principle:

Principle #23Feedback

3Productivity

If marketers use gut feeling to assign scores without empirical data, then the process is quick and simple, but the scores have little or no relationship to actual conversion and rejection rates

Engineering Contradiction:

Improvespeed of scoring rule creationVSAvoidaccuracy of lead quality assessment

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs preliminary analysis of historical conversion and rejection data to establish accurate scoring rules before they are applied to new leads. By pre-processing and learning from historical patterns, the system ensures that scoring rules are data-driven and accurately reflect the relationship between activities and conversion outcomes.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces subjective human judgment with objective data-driven algorithms that automatically determine scores based on empirical evidence from historical performance data, eliminating the disconnect between assigned scores and actual conversion potential.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10430807B2Automatic creation and refining of lead scoring rules

Publication Date: 2019.10.01 ADOBE INC

AI summary

Systems and methods disclosed herein score leads by determining and applying a scoring rule based on lead participation in an activity. This involves a processor of a computing device receiving information on participation in the activity by prior leads that resulted in conversions or rejections. A scoring rule is determined for the activity by assigning a score to the activity based on the information on participation in the activity by the prior leads that resulted in the conversions or the rejections. A new lead is scored using the scoring rule by assigning the new lead the score based on participation by the new lead in the activity. The scoring of the new lead can be used in various ways. In one example, the score of the new lead is used to determine to send a communication to the new lead.