Database-Driven Contact Ratios for Goal Attainment

Database-Driven Contact Ratios for Goal Attainment

A. Introduction:

Real estate lead generation and conversion utilize database management and contact ratios to optimize lead conversion for goal achievement, based on behavioral economics, marketing science, and statistics.

B. Database Segmentation and the Pareto Principle:

  1. Database Segmentation: Categorizing contacts based on demographics, source, engagement level, and “Met” vs. “Haven’t Met” status is crucial for tailored communication strategies.

  2. Pareto Principle (80/20 Rule): Approximately 80% of results come from 20% of the effort. A significant portion of closed deals will likely originate from a smaller, more engaged segment of the database.

    • Application: Prioritize nurturing the “Met” database.

    • Mathematical Representation: Effort_Critical * Output_Critical = k where Effort_Critical = 0.2, Output_Critical = 0.8 and k is a constant.

C. Contact Ratios: Quantifying Lead Conversion:

  1. Contact Ratio Definition: The contact ratio represents the number of contacts required in a database to generate a specific number of closed sales over a defined period.

  2. Factors Influencing Contact Ratios:

    • Database Quality
    • Communication Frequency and Quality
    • Market Conditions
    • Agent Skill and Expertise
    • Lead Source
    • “Met” vs. “Haven’t Met” Distinction
  3. The “12:2” and “50:1” Ratios:

    • Ratios of “12:2” for “Met” database and “50:1” for “Haven’t Met” database.
    • Statistical Interpretation: Consider sample size, confidence intervals, and statistical significance.
  4. Calculating Required Database Size:

    • Formula (Met Database): Contacts_Met = Closed_Sales_Goal * (12/2) = Closed_Sales_Goal * 6
    • Formula (Haven’t Met Database): Contacts_Haven't_Met = Closed_Sales_Goal * (50/1) = Closed_Sales_Goal * 50
    • Combined Approach:

      1. Sales_Met = Closed_Sales_Goal * Percentage_Met
      2. Sales_Haven't_Met = Closed_Sales_Goal - Sales_Met
      3. Contacts_Met = Sales_Met * 6
      4. Contacts_Haven't_Met = Sales_Haven't_Met * 50
    • Example: To achieve a closed sales goal of 40 sales, targeting 60% from the “Met” database:

      1. Sales_Met = 40 * 0.6 = 24
      2. Sales_Haven't_Met = 40 - 24 = 16
      3. Contacts_Met = 24 * 6 = 144
      4. Contacts_Haven't_Met = 16 * 50 = 800

D. The “8x8” and “33 Touch” Programs:

  1. Concept: Structured contact sequences designed to build relationships.

  2. “8x8” Program: Eight contacts over eight weeks.

  3. “33 Touch” Program: 33 interactions per year.

E. Statistical Considerations and Experimentation:

  1. A/B Testing: Compare different contact strategies.

  2. Cohort Analysis: Track the performance of different cohorts of leads.

  3. regression analysis: Use regression analysis to identify the factors that most strongly predict lead conversion.

    • Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε
  4. Accurate tracking of all lead generation activities and conversion metrics is essential.

F. Addressing Data Decay and Database Hygiene:

  1. Data Decay: contact information becomes outdated over time.

  2. Database Hygiene: Regularly cleaning and updating the database.

    • Verification
    • Suppression
    • Segmentation
      G. References
  • Farris, P. W., Bendle, N. T., Reibstein, D. J., & Pfeifer, P. E. (2010). Marketing Metrics: The Definitive Guide to Measuring Marketing Performance. Pearson Education.
  • Berger, J. (2013). Contagious: Why Things Catch On. Simon & Schuster.
  • Ariely, D. (2008). Predictably Irrational: The Hidden Forces That Shape Our Decisions. Harper Perennial.

H. Conclusion:

Database management and contact ratios are strategic tools.

Chapter Summary

Database management for real estate lead generation uses probabilistic models linking contact frequency and database size to sales. Contact ratios are 12:2 for “Met” contacts and 50:1 for “Haven’t Met” contacts, representing conversion probabilities. Increasing database size linearly increases expected closed sales, assuming consistent contact strategies (“33 Touch,” “12 Direct”). The 12:2 ratio indicates a higher conversion probability for “Met” contacts due to pre-existing relationships. Strategic allocation of effort between “Met” and “Haven’t Met” databases optimizes lead generation based on agent resources and network strength. Deficiencies in current contacts compared to target contacts indicate the minimum leads needed to meet sales goals, assuming steady contact and lead generation. Conversion probabilities depend on consistent contact over time, decreasing near year-end due to a lack of consistency.

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