The meeting/walkthrough covered using Google's Gemini Nano Banana AI photo editing tool to create a business targeting real estate agents by improving listing photos.
The process included scraping real estate agent leads, developing a simple web app to edit and deliver photos, and automating outreach using a CRM workflow.
Key steps and lessons in setting up the web app, integrating APIs, and managing CRM automations were demonstrated.
Discussion ended with an invitation to join a business community and emphasized the importance of launching ideas promptly.
Action Items
Immediate – Presenter: Finalize and test the web app for consistent Nano Banana integration and prompt handling.
Immediate – Presenter: Continue importing and scrubbing real estate agent leads; standardize phone numbers and remove duplicates.
Immediate – Presenter: Integrate updated app workflow with CRM (High Level) automation for photo delivery and lead nurturing.
Ongoing – Presenter: Monitor responses from initial outreach to real estate agents and refine messaging or workflows as needed.
Ongoing – Presenter: Consider future automation of lead selection, photo matching, and outreach to improve scalability.
Ongoing – Presenter: Offer setup help and business community access to interested users via tkowners.com.
Problem/Opportunity Identification: Real Estate Photo Staging
Many real estate listings have unprofessional or unstaged photos, leading to slower sales and reduced sale prices.
Staged homes sell faster and for 6-10% more, representing significant value.
AI (Nano Banana) can edit photos to look staged or professionally shot, offering value to agents.
Business Model & Outreach Process
Use AI (Nano Banana) to edit listing photos (e.g., adding furniture, improving lighting).
Develop a web app (via Lindy) to automate the upload, edit, and download process for up to 30 photos at a time.
Scrape agent leads (with phone numbers) using tools like Outscraper and standardize data for CRM import.
Import leads into High Level CRM, tag appropriately, and link to a workflow pipeline for automated follow-up.
Initial outreach involves sending edited photos to agents, demonstrating value, and moving leads through a sales pipeline.
Pricing model suggests $1 per photo charged to agents, with AI processing cost around $0.04 per photo, offering high margins.
Technical Implementation & Lessons Learned
Web app was built using low/no-code "vibe coding" with API integration; troubleshooting included API key setup and billing activation for Nano Banana.
App successfully edits photos as intended after resolving API and UI issues.
CRM automation involves tagging leads, triggering workflows upon uploading photos, and sending SMS outreach with demo images.
Early steps are intentionally semi-manual to prioritize launch over over-automation; further automation is possible over time.
CRM Workflow Details
Uploading an edited photo to a lead triggers an SMS and updates the lead pipeline.
Pipeline includes stages: New Lead, Text Sent, No Response, Response, Called, Customer, etc.
CRM enables task management, appointment booking, and note-taking tied to each lead.
Community & Support Offering
Option to join TK Owners community ($99/month, includes High Level sub-account, weekly AMA sessions, Slack group, and automation support).
Presenter encourages action and community participation but notes it's optional.
Decisions
Proceed with semi-manual MVP launch — Chose to launch the business/process using a mostly manual approach initially to prioritize momentum and learning over complete automation.
Use Nano Banana for photo editing — Decided to use this tool as the core differentiator for rapid, scalable photo improvements in the real estate sector.
Begin with $1/photo pricing — Selected an initial competitive price point to test agent willingness to pay.
Open Questions / Follow-Ups
Will the outreach strategy (sending edited photos without prior consent) yield positive engagement rates or provoke negative feedback from realtors?
What are the legal or reputational risks of sending unsolicited edited photos to potential customers?
How scalable is this approach—what bottlenecks will appear with increased volume, and which steps should be automated next?
How will the offering and pricing evolve as more agents express willingness to pay?