Author and trainer Bernice Ross writes that the addition of Python to the already-robust marketing capabilities of ChatGPT creates a winning combination for your 2024 content planning.

This January marks Inman’s fifth annual Agent Appreciation Month, which culminates at Inman Connect New York in a celebration of agents at the end of January. Plus, we’re rolling out the coveted Inman Power Player Awards, as well as the New York Power Brokers and MLS Innovators awards.

This post was updated Jan. 17, 2024.

If you want to become the dominant player in your market in 2024, it’s time to leave behind many of the old-school marketing and lead generation strategies from the past and embrace what ChatGPT’s new Python app can do to revolutionize your business.

Best of all, upgrading from ChatGPT 3.5 to ChatGPT 4.0 only costs $20 per month, and it can tell you exactly how to tap into its cutting-edge technology — no programming experience needed.

I recently sat in on a webinar with real estate coach Jerry Kidd where he briefly discussed the new apps for ChatGPT 4.0. When I asked ChatGPT 4.0 about its new apps and what they do, at the top of its list was Python. 

Python is a sophisticated programming language that according to ChatGPT “is an incredibly versatile programming language that can be used for a wide range of tasks, including data analysis, automation, and even web development. It’s known for its readability and simplicity, making it a popular choice for beginners in coding as well as seasoned developers.”

I’ve spent several days playing with the Python app and learning exactly how to structure your prompts so you can easily tap into this powerful tool. 

The simplest way to access Python

The simplest approach is to ask ChatGPT 4.0 (this is not available on 3.5) to use Python when you write your prompts. For example, “Use Python to identify the top-rated home inspectors in my market,” or “Use Python to evaluate how the current economic trends are impacting first-time buyers.”  

ChatGPT explains how this works:

When you reference “Python” in a prompt, it doesn’t automatically trigger the use of the Python tool in my environment. The decision to use Python is based on whether or not it’s necessary or helpful for answering your question. If a question can benefit from computational analysis, data processing, or any kind of task that Python is well-suited to handle, I’ll then use the Python tool to assist in generating a response.

For example, if you ask for a calculation, data analysis, or to generate a list based on certain criteria (like the low-cost recreational activities), using Python is a great choice. On the other hand, for general inquiries, advice, or topics that don’t require computational work, I’ll respond directly without Python.

The responses you receive, whether they involve Python or not, are always aimed to be the top responses based on the analysis and information available to me, tailored to meet your query as accurately and helpfully as possible.

Have ChatGPT 4.0 tell you how to create the scripts you need in Python

An area where ChatGPT 4.0 really excels is helping agents automate repetitive tasks. Rather than relying on human experts to tell you how to do this, you can now ask ChatGPT 4.0 to generate prompts in Python. Below you’ll find the exact Python prompts you can use to do the following tasks (Note: These answers were all generated by ChatGPT 4.0).

Scheduling emails

Instruction example: “Can you create a Python script for me that automatically sends out ‘Happy Anniversary’ emails to my clients on the anniversary of their home purchase? The email should include their name, the date of purchase, and a personalized message.”

(Note the command: “Can you create a Python script for me that …?”)

How it helps:

  • This script can connect to the agent’s email and client database.
  • On each anniversary, it sends a personalized email, enhancing client relationships.

Follow-up emails after open houses

Instruction example: “Can you create a script that automatically sends follow-up emails to visitors after an open house? The email should thank them for coming, include details about the property they visited, and offer to answer any questions or schedule a private showing.”

(Note the command: “Can you create a script that automatically…?”)

How it helps:

  • This ensures timely and personalized follow-up with potential buyers.
  • It helps in keeping the property fresh in the minds of visitors and encourages further interaction.

Monthly market update reports to clients

Instruction example: “I need a system that compiles and sends monthly market updates to my clients. It should include recent sales data, current listings, and trends in the areas they are interested in. Can you set up an automated process for this?”

(Note the commands: “I need a system that…” and “Can you set up an automated process for this?”)

How it helps:

  • Provides clients with valuable and current market insights, positioning the agent as a knowledgeable resource.
  • Enhances client engagement by keeping them informed about the real estate market.

Birthday and special occasion greetings

Instruction example: “Can you help me automate the sending of personalized birthday and special occasion greetings to my clients? Each message should include their name and a friendly note and be sent on the appropriate date.”

(Note the command: “Can you help me automate…”)

How it helps:

  • Personalizes client interactions by acknowledging important dates in their lives.
  • Strengthens client relationships and enhances the agent’s reputation for thoughtful customer service.

ChatGPT 4.0 goes on to explain: 

Each of these examples demonstrates how ChatGPT can be used to automate various aspects of client communication and information dissemination. This not only saves time for the real estate agent but also helps in maintaining a high level of personalized service, which is crucial in the real estate business. These automated systems can be set up with minimal technical expertise but offer significant benefits in terms of efficiency and client satisfaction.

8 additional prompts that can guide your work with ChatGPT 4.0’s Python app in 2024

Inman contributor Jimmy Burgess authored an excellent article about using ChatGPT 3.5 back in February and a follow-up article in June 2023 where he provided “Game changing ChatGPT prompts every agent should use.” Most of these prompts begin with the words “Give me.” You can change these prompts to ChatGPT Python prompts using the examples below. 

(Note: The prompts that begin with “Give me” are from Burgess. The remainder of the prompts were recommended by ChatGPT 4.0.)

To use these for your local market area, replace any prompts with “Austin, Texas” with your city, state, and/or subdivision.  

1. Rewriting property descriptions for MLS optimization

Old Prompt: “Rewrite my property description for the Multiple Listing Service so it is optimized to motivate the reader to see the property.”

Python Prompt: “Use Python to analyze high-performing property listings on the MLS and apply NLP techniques to rewrite my property description, ensuring it is optimized to attract and motivate potential buyers.”

(Please note that one of the reasons the Python prompt above is so powerful is its use of Neurolinguistic Programming (NLP), one of the most powerful tools available for making persuasive arguments.) 

2. Search engine-optimized social media post for buying vs. renting in Austin, Texas

Old prompt: “Give me an SEO-optimized post for LinkedIn, Instagram, YouTube, Facebook, and Twitter with seven reasons buying a home is smarter than renting in Austin, Texas.”

Python prompt: “Employ Python to research current real estate trends and user engagement data in Austin, Texas, and generate an SEO-optimized post for LinkedIn, Instagram, YouTube, Facebook, and Twitter, highlighting seven reasons why buying a home is smarter than renting in this area.”

(Note the command: “Generate an SEO-optimized post for LinkedIn, Instagram, YouTube, Facebook, and Twitter.” You can use this prompt to quickly create appropriate posts for each of the social media sites above.)

3. Search engine-optimized Facebook post for a specific property

Old prompt: “Give me an SEO-optimized Facebook post for the home located at [address] with the following MLS (multiple listing service) description.”

Python prompt: “Utilize Python to analyze effective real estate Facebook posts and apply SEO strategies to create an optimized post for the home located at [address], enhancing its MLS description to maximize reach and engagement on Facebook.”

4. Unique promotional strategies for real estate agents

Old prompt: “Give me 20 ways a real estate agent can uniquely promote his business.”

Python prompt: “Program Python to scrape and analyze successful real estate marketing campaigns from various platforms to suggest 20 unique ways a real estate agent can promote his business.”

(Note the command: “Program Python to scrape and analyze successful real estate marketing campaigns.” This is huge, because Python will evaluate what’s working and then apply it to the results it generates. The top results will be the ones that are the most effective.)

5. For Facebook Posts for a Realtor in a specific market

Original prompt: “Give me 10 Facebook posts for a Realtor in Austin, Texas.”

Python prompt: “Generate a list of 10 engaging Facebook post ideas for a Realtor in Austin, Texas, focusing on the unique aspects of the local real estate market, community events, and housing trends.”

(Note the use of the words “engaging” and “unique.” These two words direct Python to find data that best matches those two criteria.)

6. For LinkedIn Articles for a Realtor in a specific market

Original prompt: “Give me 10 LinkedIn articles for a Realtor in Austin, Texas.”

Python prompt: “Create outlines for 10 LinkedIn articles tailored for a Realtor in Austin, Texas, highlighting market analysis, investment opportunities, and professional insights into the Austin real estate scene.”

7. For a search engine-optimized Facebook post on buying in a specific market despite interest rates

Original prompt: “Give me an SEO-optimized Facebook post with five reasons a potential homebuyer should consider buying a home in Austin, Texas despite an increase in interest rates.”

Python prompt: “Draft an SEO-optimized Facebook post that presents five compelling reasons for potential homebuyers to consider purchasing a home in Austin, Texas, even with rising interest rates, focusing on long-term investment benefits and the resilience of the Austin housing market.”

(Note the words “SEO optimized,” which should help to drive SEO on your posts.)

8. For a search engine-optimized Instagram post on buying in a specific market despite rising prices

Original prompt: “Give me an SEO-optimized Instagram post with five reasons buying a home in Austin, Texas right now is smart even though home prices have gone up over the last few years.”

Python prompt: “Construct an SEO-optimized Instagram post detailing five key reasons why it is a wise decision to buy a home in Austin, Texas at present, despite the recent increase in home prices, emphasizing factors like the city’s growth, lifestyle, and future investment potential.”

2 use cases illustrating how ChatGPT works hand-in-hand with Python

I asked ChatGPT to evaluate this article and make additional recommendations for Inman readers. While ChatGPT 4.0 made a number of technical suggestions, the one that I thought was most useful was “practical examples.” I then asked it for specific case studies that weren’t programming-based. Here’s how it responded:

Here are a couple of hypothetical use cases where real estate professionals could leverage ChatGPT and Python without needing to delve into the programming details themselves.

Lead generation through targeted campaigns

Scenario: A real estate agent wants to create a targeted campaign to reach potential sellers in a neighborhood where home values have risen significantly.

How ChatGPT and Python help: The agent uses ChatGPT to draft a compelling message that emphasizes the increase in home values. They then utilize the Python app to analyze demographic and property data to identify homeowners who have lived in their homes for more than 10 years (a group more likely to sell). The Python app can also help automate the sending of these personalized messages at scale.

Market analysis for buyer education

Scenario: An agent seeks to educate potential buyers on the benefits of purchasing in a specific area, targeting those who are undecided or considering different neighborhoods.

How ChatGPT and Python help: ChatGPT can generate informative content on the benefits of living in the target area, including community amenities, schools, and growth potential. Python can be used to pull in recent market data, providing up-to-date statistics and trends to bolster the agent’s message, which can be distributed via email or social media campaigns.

In each of these scenarios, the agent doesn’t need to understand the inner workings of Python or data analysis. Instead, they can focus on what they do best — connecting with clients and closing deals — while ChatGPT and Python handle the data-heavy lifting in the background.

The key takeaway for your readers is that these tools can be used as a personal assistant that automates and personalizes tasks that would otherwise take up valuable time, allowing them to focus on direct revenue-generating activities.

If you’re not already working with ChatGPT, put it at the top of your New Year’s resolutions for 2024. The agents who are early adopters are going to trounce their competition — make sure you’re one of those early adopters now.

Bernice Ross, president and CEO of BrokerageUP and, is a national speaker, author and trainer with over 1,500 published articles. Learn about her new and experienced agent sales training programs at plus her latest initiative to help women build wealth and secure their financial independence at 

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