Building Your Database: Contacts & Information

The Scientific Foundation of Contact Management

Building a robust database is not merely about collecting names and numbers; it’s a strategic process rooted in relationship management theories and data-driven insights. In real estate, your database is your business. This section explores the scientific principles underpinning effective contact management.

Relationship Marketing and the Power of Personalization

At its core, effective contact management leverages the principles of relationship marketing. This approach emphasizes building long-term, mutually beneficial relationships with customers.

• Key Principle: Shifting from transactional interactions to relational engagements.
• Scientific Basis: Social Exchange Theory posits that relationships are formed based on a cost-benefit analysis. By consistently providing value and personalized experiences, you increase the perceived benefits of engaging with you, fostering stronger relationships.

The Personalization Equation

Personalization effectiveness can be modeled as:

E = f(R, D, C)

Where:

• E = Effectiveness of personalization
• R = Relevance of information provided
• D = Depth of knowledge about the contact
• C = Consistency of communication

A high E value indicates a strong likelihood of conversion and repeat business.

Case Study: Zappos and Customer Delight

Zappos, the online shoe and clothing retailer, built its brand on exceptional customer service. They empower their employees to go above and beyond, creating personalized experiences that foster loyalty. This dedication to relationship building resulted in high customer retention rates and positive word-of-mouth referrals.

Data-Driven Decision Making

A powerful database allows for data-driven decision making, enabling you to target your marketing efforts and tailor your communications effectively.

• Key Principle: Using data analytics to identify patterns, predict behavior, and optimize strategies.
• Scientific Basis: Regression analysis can be used to predict the likelihood of a contact converting into a client based on various factors, such as demographics, property preferences, and engagement history.

Predictive Modeling in Real Estate

A simple linear regression model for predicting conversion probability:

P = β₀ + β₁X₁ + β₂X₂ + … + βₙXₙ

Where:

• P = Predicted conversion probability
• β₀ = Intercept (baseline probability)
• β₁, β₂, …, βₙ = Regression coefficients (weights) for each predictor variable
• X₁, X₂, …, Xₙ = Predictor variables (e.g., lead source, property interest, time since last contact)

Common Predictor Variables

• Lead Source (Online inquiry, referral, open house)
• Property Interest (Price range, location, desired features)
• Time Since Last Contact (Recency of engagement)
• Engagement Level (Website visits, email opens, appointment attendance)
• Demographics (Age, income, family status)

Example

If a contact attended an open house (X₁ = 1), is interested in properties between $500,000-$600,000 (X₂ = 1), and was last contacted one week ago (X₃ = 7), and the regression model is:

P = 0.1 + 0.2X₁ + 0.3X₂ - 0.01X₃*

Then:

P = 0.1 + 0.2(1) + 0.3(1) - 0.01(7)
P = 0.53

This means the predicted probability of this contact converting is 53%.

Case Study: Using Clustering to Identify Target Markets

A real estate agency analyzed their database using cluster analysis. They identified three distinct customer segments:

• First-Time Homebuyers: Young professionals seeking affordable properties in urban areas.
• Upsizing Families: Families with young children looking for larger homes in suburban neighborhoods with good schools.
• Retirees: Empty-nesters seeking smaller, low-maintenance homes in retirement communities.

Based on these findings, the agency tailored their marketing campaigns and property listings to resonate with each specific segment, resulting in higher conversion rates.

Building Your Database: Step-by-Step Methodology

Building a valuable database requires a systematic and consistent approach. Here’s a step-by-step guide:

Step 1: Defining Your Ideal Client Profile

Before you start collecting contacts, define your ideal client. This will help you focus your efforts and attract the right kind of leads.

1. Demographics: Age, income, occupation, family status, location.
2. Psychographics: Values, interests, lifestyle, attitudes.
3. Buying Behavior: Preferred communication channels, decision-making process, price sensitivity.

Step 2: Identifying Key Data Points

Determine what information is crucial for effectively communicating with and serving your clients. Consider the items in the provided reference material:

Must-Have Contact Information:

• Name
• Phone number
• Email address

Essential Information:

• Interest Rate
• Spouse’s date of birth
• Available equity or down payment
• Spouse’s start date of employment
• Description of property
• Anniversary date
• House style
• Children(s) names
• Number of bedrooms, sizes
• Children(s) date of birth
• Number of baths, sizes
• Recreation, hobbies, interests
• Features
• Desired move date
• Property square footage
• Date began house hunting
• Home’s square footage
• Owns or rents
• Age of home
• Desired property features
• Information on the neighborhood
• Desired property price range
• Working with another agent (Yes / No)
• Name of the agent they’re working with
• Name of the lender they’re working with
• Lender’s address, phone, fax, email
• Has met with lender (Yes / No)
• Plans to do a FSBO (Yes / No)
• Able to offer seller financing (Yes / No)
• Seen houses they like (Yes / No)
• Available down payment ($ / %)
• Maximum monthly payment
• Contact history (conversations, mailings)
• Classification for potential for referrals
• Database group

Step 3: Choosing a Contact Management System (CMS)

Select a CMS that aligns with your business needs and goals. There are numerous options available, each with its own strengths and weaknesses.

1. eEdge/KW Command: If affiliated with Keller Williams, leverage these platforms. They offer integrated features for contact management, marketing, and transaction management.
2. Third-Party CRMs: Options like Salesforce, HubSpot, and Follow Up Boss offer advanced features for managing customer relationships.

Step 4: Implementing Data Entry and Update Protocols

Establish clear protocols for entering and updating contact information.

1. Timeliness: Enter new contacts into your database as soon as possible, ideally within 24 hours.
2. Accuracy: Double-check all data for accuracy to avoid errors in communication and targeting.
3. Consistency: Use a standardized format for entering data to ensure consistency across your database.
4. Regular Updates: Promptly update your database anytime a contact’s information changes or you get additional information about a contact.

Step 5: Segmenting Your Database

Segment your database based on relevant criteria to target your marketing efforts effectively.

1. Demographic Segmentation: Age, income, location, family status.
2. Behavioral Segmentation: Past transactions, property interests, engagement level.
3. Source Segmentation: Lead source (e.g., online inquiry, referral, open house).
4. Classification Segmentation: Potential for referrals.
5. Database Group Segmentation: Mets, Haven’t Mets, Geographic/Niche.

Using RFM Analysis for Segmentation

RFM (Recency, Frequency, Monetary Value) analysis is a powerful technique for segmenting customers based on their purchasing behavior.

• Recency: How recently did the customer make a purchase or engage with your services?
• Frequency: How often does the customer make purchases or engage with your services?
• Monetary Value: How much money has the customer spent on your services?

Each customer is assigned a score for each RFM variable, and these scores are used to segment customers into different groups (e.g., high-value customers, loyal customers, at-risk customers).

Step 6: Implementing Systematic Marketing Plans

Develop and implement systematic marketing plans to nurture your relationships with your contacts. As highlighted in the course materials, consider the following:

1. 12 Direct: Direct mail marketing pieces sent out once a month over a one-year cycle. Targeted to Haven’t Mets.
2. 8 x 8: Cements your relationship with eight touches in the eight weeks after you’ve made contact. Entry point for all Mets.
3. 33 Touch: Maintains relationship with Mets over a one-year cycle.

The 8 x 8 Plan - A Detailed Breakdown

Goal: Position yourself as the go-to real estate expert in the minds of new contacts.

Principles:

• Immediate Application: Start the plan immediately after meeting a new contact.
• Combination of Touches: Incorporate personal visits, phone calls, items of value, and handwritten notes.
• Referral Focus: Every touch should include a quick reminder and instructions on how to give you referral business.

Weekly Schedule:

The 33 Touch Plan

Goal: Nurture and sustain relationships with existing clients and contacts.

Elements:

Step 7: Tracking and Analyzing Results

Monitor the effectiveness of your contact management efforts.

1. Conversion Rates: Track the percentage of contacts who convert into clients.
2. Return on Investment (ROI): Calculate the ROI of your marketing campaigns based on the cost and revenue generated.
3. Customer Lifetime Value (CLTV): Estimate the total revenue you can expect from a customer over the course of their relationship with your business.

Customer Lifetime Value (CLTV) Estimation Formula:
CLTV = (Average Transaction Value) x (Number of Transactions) x (Retention Time)

Step 8: Continuous Improvement

Regularly review your contact management processes and make adjustments as needed.

1. Gather Feedback: Ask clients for feedback on your communication and service.
2. Stay Updated: Keep abreast of the latest trends and technologies in contact management.
3. Experiment: Test different strategies and approaches to optimize your results.

Common Challenges and Misconceptions

Challenge: Data Overload

Collecting too much information can be overwhelming and lead to analysis paralysis.

• Solution: Focus on collecting only the data points that are essential for your business goals.

Misconception: “More is Always Better”

While having a large database is beneficial, the quality of your contacts is more important than the quantity.

• Solution: Prioritize attracting and nurturing high-quality leads who are likely to convert into clients.

Challenge: Data Decay

Contact information can become outdated quickly due to changes in phone numbers, email addresses, and job titles.

• Solution: Implement a system for regularly updating and verifying contact information.

Misconception: Automation is a Substitute for Personalization

While automation can streamline your contact management efforts, it should not replace personal interactions.

• Solution: Use automation to enhance, not replace, your personal touch.

Conclusion

Building a powerful database is an ongoing process that requires a strategic approach, a commitment to data quality, and a focus on building meaningful relationships. By following the methodologies outlined in this chapter and avoiding common pitfalls, you can create a database that drives business growth and maximizes your success in the real estate industry.