Prompt #1 

Buyer Economics (input your City, State, Zip)

Role

• Act as a real estate market intelligence analyst delivering a full economic + demographic profile of the
  target area for TCP refinement.

Task

• ​​​In [Community city and Zip Code}

• Provide population, age distribution, household income, per capita income, and poverty rate.

• Add household composition (singles, families, multigenerational).

• Add migration patterns (are people moving in/out, % relocations).

• Detail employment by sector, unemployment, job growth, and work-from-home vs commuter
  splits.

• Include average wages, disposable income vs. housing costs, and wealth posture (equity,
  pensions, investments).

• Summarize major local businesses, industries, and tax conditions.

Context

• Data sources: U.S. Census, BLS, IRS migration data, state/local reports.

• Stats must be 2023 or newer.

• Compare against county + state averages.

Reasoning

• Cross-check data consistency (income vs. spending vs. affordability).

• Show how these numbers impact buying power and willingness to purchase.

• Include insight into whether this area has “room” for TCP growth.

​

Output Format
Return a Markdown table:

| Metric | Local Value | County Avg | State Avg | Council Insight |

​

Prompt #2

Buyer Psychology (Input your City, State, Zip)

Role

• Act as a real estate sales strategist and consumer psychologist delivering a deep profile of buyer psychology for (Input your City, State, Zip).

Prompt

• Provide a comprehensive and up-to-date analysis of buyer psychology for (Input your City, State, Zip),
  including:

  1. Demographic + Household Profileounts/incentives?

     • Age, income, household size, and education levels.

     • Household composition (singles, couples, families, multigenerational).

     • Migration and relocation patterns (are buyers moving in/out, % RELO).

  2. Psychographics & Lifestyles

     • Core values, interests, and hobbies.

     • Lifestyle preferences (urban vs. suburban, wellness, sustainability, community belonging).

     • Attitudes toward risk, spending, and financial security.

     • Generational lens (Boomers, Gen X, Millennials, Gen Z differences).

  3. Purchasing Motivations & Behaviors

     • Motivators: affordability, lifestyle upgrades, downsizing, retirement, schools.

     • Elasticity & payment sensitivity (monthly payment focus vs. total price).

     • Buyer urgency: are they waiting out rates or ready to act now?

     • Brand trust, peer influence, and reliance on online reviews.

  4. Communication Channels

     • Preferred communication methods (text, phone, email, social media, in-person).

     • Digital fluency: how tech-savvy they are, how they research (Google, Zillow, MLS, social).

     • Online-to-offline journey: where the digital touchpoints shift into physical action.

  5. Local Consumer Behavior Patterns

     • Spending habits: discretionary vs. essential spending, credit vs. savings reliance.

     • Leisure time: gyms, restaurants, pickleball courts, farmers markets, religious groups, community events.

     • Competitor awareness: which builders or options they are comparing.

     • Incentive sensitivity: do they only move with disc

Requirements

• Use credible sources no older than 2023 (consumer research, housing studies, BLS, Pew Research, Nielsen, etc.).

• Provide specific stats or patterns with citations wherever possible.

• Ensure insights are practical and field-ready for sales engagement.

​

Output Format
Return results in 6 labeled sections:

1. Demographics & Household Composition

2. Psychographics & Lifestyles

3. Purchasing Motivations & Behaviors

4. Communication Channels

5. Local Consumer Behavior Patterns

6. Competitor Awareness & Incentive Sensitivity