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Lead Qualification: Readiness, Willingness, and Ability
Lead qualification is a systematic process of evaluating potential clients based on Readiness, willingness❓, and Ability (RWA).
Theoretical Framework:
- Transtheoretical Model (TTM): individuals❓ move through stages when adopting new behaviors. Stages include Precontemplation, Contemplation, Preparation, action❓❓, and Maintenance.
- Economic Utility Theory: Individuals make rational decisions to maximize their utility, where U = f(x1, x2, …, xn).
Readiness:
- Readiness Index (RI): RI = (t_horizon - t_current) / t_horizon, where t_horizon is the time horizon for purchase and t_current is the current time.
- Readiness Threshold (R_th): A predefined value indicating when a lead is ‘Ready’. If RI <= R_th, classify as ‘Ready’.
- Experiment: Group leads into cohorts based on RI and apply different follow-up frequencies. Measure conversion rates to identify the optimal frequency for each RI range.
Willingness:
- Likert Scale: A psychometric scale used in surveys.
- Net Promoter Score (NPS): Measures customer loyalty. Promoters (9-10), Passives (7-8), Detractors (0-6).
- Experiment: A/B test different value propositions to different groups of leads and measure click-through rates, engagement metrics, and conversion rates.
Ability:
- Debt-to-Income Ratio (DTI): DTI = (Total Monthly Debt Payments / Gross Monthly Income) * 100.
- Loan-to-Value Ratio (LTV): LTV = (Loan Amount / Appraised Property Value) * 100.
- Credit Score: Evaluates credit worthiness.
- Experiment: Train a machine learning model (e.g., logistic regression) to predict loan approval outcomes using DTI, LTV, credit score, and other relevant variables.
Integrating RWA:
- Lead Scoring Algorithm: Score = w1 * Readiness + w2 * Willingness + w3 * Ability, where w1, w2, and w3 are weights summing to 1.
- Example Weights: w1 (Readiness) = 0.3, w2 (Willingness) = 0.4, w3 (Ability) = 0.3
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Decision Matrix:
Score Range Lead Classification Action 0.8 - 1.0 High Priority Immediate personalized follow-up 0.5 - 0.8 Medium Priority Targeted content and engagement 0.0 - 0.5 Low Priority Nurturing and educational content
Chapter Summary
Lead classification prioritizes potential clients based on their probability of conversion, assessing Readiness, willingness❓, and Ability (RWA).
Readiness refers to the lead’s temporal proximity to a transaction, inversely proportional to the time❓ remaining before engaging in a real estate transaction. It involves identifying and evaluating barriers.
Willingness reflects the lead’s psychological inclination and motivation towards engaging in a transaction and working with an agent. Resistance to agent involvement indicates lower willingness.
Ability signifies the lead’s financial qualification, including creditworthiness, access to capital, and affordability.
The classification process uses structured questioning to gather RWA data. Responses are analyzed to categorize leads based on their combined RWA profile.
High-RWA leads warrant immediate and intensive engagement. Lower-RWA leads are placed into nurturing pipelines to improve their scores. The framework supports efficient resource allocation by identifying unsuitable potential customers.
