Exploration Geochemistry: Indicator and Background Elements

Mets (Established Contacts) are individuals within an existing network, characterized by pre-existing contact information in a CRM or comparable system. They are individuals with whom a prior interaction has occurred.

Haven’t Mets (Unestablished Contacts) are the segment of the population outside of the established network, potential leads not yet directly contacted or integrated into a contact management system.

Mere-Exposure Effect: Repeated exposure to a stimulus increases liking for that stimulus. Affinity = k * ExposureFrequency, where k is a proportionality constant.

Social Exchange Theory: Social behavior is the result of an exchange process to maximize benefits and minimize costs. Perceived Relationship value❓ = Perceived Benefits - Perceived Costs.

Diffusion of Innovation Theory: Explains how an idea or product spreads through a population. Adopter categories: Innovators, Early Adopters, Early Majority, Late Majority, Laggards.

Cognitive dissonance❓ Theory: Humans strive for internal consistency; inconsistency (dissonance) causes discomfort. Dissonance = |Attitude – Behavior|.

Statistical Segmentation: Utilizing data to segment Mets and Haven’t Mets into homogenous groups using techniques like cluster analysis (k-means, hierarchical clustering), factor analysis, discriminant analysis. Minimize J = Σ Σ ||xᵢ - cⱼ||², where xᵢ is a data point, cⱼ is the centroid of cluster j.

Propensity Modeling: Developing statistical models to predict the likelihood of a contact converting, using techniques like logistic regression, decision trees, SVMs. P(Y=1) = 1 / (1 + e^(-(β₀ + β₁X₁ + β₂X₂ + … + βₙXₙ))), where P(Y=1) is the probability of conversion, β are the coefficients, and X are the predictor variables.

CRM Analytics: Leveraging CRM data to identify patterns that correlate with successful conversions. Metrics: customer lifetime value❓❓ (CLTV), Conversion Rate, Engagement Score. CLTV = (Average Transaction Value * Number of Transactions) * Retention Period.

A/B Testing Methodology: Randomly assigning Mets or Haven’t Mets to treatment groups and measuring the impact on an outcome variable.

Statistical Significance Testing: Determining whether the difference between treatment groups is statistically significant using T-tests, Chi-square tests, ANOVA. t = (X̄₁ - X̄₂) / √(s₁²/n₁ + s₂²/n₂), where X̄ is the sample mean, s is the standard deviation, and n is the sample size.

Communication Accommodation Theory (CAT): Individuals modify communication style❓ to converge or diverge.

Elaboration Likelihood Model (ELM): Two routes to persuasion: central (logical) and peripheral (emotional).

Transparency and Informed Consent: Disclose data collection purpose and obtain consent when required.

Data Security and Privacy: Implement security measures to protect personal information.