By Kevin Hawkins with Korey Hawkins | Vol. 1 Post 14
Real AI is a 100% human-created weekly roundup of all things AI in real estate and emerging AI innovations in other sectors likely to impact real estate, posting a new edition every Friday.
Using AI to unlock real estate data
Content creation continues to dominate how real estate professionals use AI.
AI helps agents create better blogs, website content, flyers, social posts, listing descriptions, property photos, marketing ideas, business plans, video scripts, and more.
Using AI to perfect content has become part of many real estate agents’ workflow in one way or another. That’s not going to change, but in fact, it will accelerate.
However, while AI for content is huge, another AI use will have a far more significant impact on agent business today and tomorrow. It’s still in its infancy, but using the power of all things AI to unlock real estate data will be massive and could completely alter how agents secure new business.
AI lead gen
A lot of early use of AI in real estate was lead gen related, then described as predictive analytics. Now, dozens of real estate Proptech firms and top brokerages are using AI to identify who in your sphere of influence are most “likely to sell” and “likely to buy.”
Buyside, now Percy, was an early entry into this space. In June, tech-centric Compass integrated machine learning into its CRM to flag for its agents and clients who are “likely to sell.” Localize uses an AI Chatbot (Hunter) that engages leads and then alerts agent users when clients are ready to house hunt.
All-in-one CRM-centric platforms like Delta Media’s DeltaNET 7 are building in behavior tracking tools, leveling the playing field by making AI-powered tech more accessible to more agents.
But all these efforts are still scratching the surface because machine learning will help all this tech get better and better. Once we identify why one person buys, it’s easy to extrapolate to identify others not in our sphere nearby who are also likely to buy or sell.
Much like the story Brad Inman told in 2016 about how Google was rending baby-related ads to his daughter before she found out she was pregnant, AI will empower agents to know when clients will buy or sell before their clients have fully embraced the idea.
Vital to using this new tech is finding a way to eliminate what I call the LendingTree problem. When I first tested LendingTree in its early days, I input my data, and in minutes, I was deluged with mortgage lenders pitching me their business. It was a massive, overwhelming, horrible customer experience I would never repeat.
If AI delivers to everyone with the same predictive analytics, what is the experience of the seller who is about to buy if they are overloaded with agent inquiries?
Data-centric AI for advanced analytics
On the bright side, one untapped superpower for real estate is AI’s ability to take in disparate data, organize it, summarize it, and then recommend strategic courses of action.
Real estate data is sprawling and often siloed, from market trends and demographic characteristics to what real estate clients have purchased and other client information. Data-centric AI thrives by rapidly consuming these diverse data sets and creating a cohesive 360-degree view of the market and your clients.
The true power of AI lies in its ability to distill vast amounts of data into actionable insights. By summarizing complex data, AI can provide real estate professionals at every level with clear, strategic recommendations that can drive growth and innovation.
More importantly, AI will help real estate pros identify trends early by analyzing patterns and predicting how the market will move, helping to make the right pivots ahead of the curve instead of behind it.
Using ChatGPT 4 for real estate intelligence
Most people don’t realize it, but ChatGPT-4 can read PDFs and Excel files. It also can analyze and provide data from images. This is a window into tapping into advanced analytics, as ChatGPT is excellent at summarizing information. If you give it the proper prompts, it can create strategic recommendations based on this intelligence and provide other analyses, including charts and graphs.
While the ChatGPT-4 interface itself does not directly interpret trends from data within PDFs or Excel files, it can use Python and its powerful libraries for data analysis. Employing Pandas and Matplotlib can help decode trends from the data contained in these files.
ChatGPT explains here how it works:
- PDF Files: If you upload a PDF, ChatGPT can extract the text using Python’s PDF libraries like PyPDF2 or PDFMiner. If the PDF contains data in a structured form, like tables, it can attempt to parse that data into a format suitable for analysis.
- Excel Files: If you upload an Excel file, ChatGPT can use Pandas to read the data and put it into a DataFrame. From there, it can perform various analyses to identify trends, including summary statistics, correlation analysis, and visualizations.
- Data Visualization: Once the data is extracted and structured, ChatGPT can create charts and graphs to visualize the trends using libraries like Matplotlib or Seaborn.
You need to upload the PDF or Excel files to ChatGPT and ask it to write and execute Python code to analyze the data. Finally, ChatGPT warns that the effectiveness of trend analysis depends on the quality and structure of the data provided. Or, garbage in, garbage out.
If this sounds ridiculously hard for most real estate pros, it probably is. However, there’s a ChatGPT plugin or Proptech firm ready to simplify this kind of invaluable real estate business intelligence, likely coming soon to an inbox near you.
AI Five Fast Facts
AI Headlines Take 5
1. 6 ways real estate agents can use AI to become the ultimate authority | 11/21/23 HousingWire
How AI can help agents set themselves apart from their competition.
2. Predictive AI tools to consider in 2023 | 6/5/23 Boston Agent Magazine
A look at how predictive AI tools can help real estate agents.
3. The Tech Trends That Will Shape the World in 2024 | 11/21/23 Technopedia
Generative AI is the key trend potentially reshaping how we play and work.
4. Differentiating AI Applications in the Mortgage Space | 11/20/23 MReport
How Generative AI will impact the mortgage industry (which overall is a lagger in deploying AI).
5. Scammers using artificial intelligence and social media to target holiday shoppers | 11/21/23 CBS
The downside of AI: ‘Tis the season for bad actors and it’s more difficult to spot when you are being scammed.’
Quote of the week
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