Real Estate Project Updates

As always, I got amazed with other themes, like:

• https://github.com/codexcodethemes/cybernetic-free
  • https://cybernetic-free-version.netlify.app/

git clone https://github.com/codexcodethemes/cybernetic-free
npm install 
npm audit fix

npm run dev #localhost:4321
#rm -rf .git

Apparently, at /src/static/images/index.tsx you can choose the Hero images.

Create the tailwind.config.js and add:

/** @type {import('tailwindcss').Config} */
    module.exports = {
      content: ["./src/**/*.{astro,html,js,jsx,md,mdx,svelte,ts,tsx,vue}"],
      theme: {
        extend: {},
      },
      plugins: [require("daisyui")],
    };

Install firebase CLI as static deployment:

npm install -g firebase-tools

firebase login
firebase init
#firebase deploy

#firebase hosting:channel:list
#firebase hosting:channel:delete <channelId>

It will be under someprojectname.web.app and you can revoke permissions at https://github.com/settings/connections/applications/89cf50f02ac6aaed3484

And 2 .yml files with a GHA Workflow for the Firebase deployment are already configured

To add the OpenGraph Image so that it will be visible when sharing:

1. https://github.com/mearashadowfax/ScrewFast

MIT | Open-source Astro website template with sleek, customizable TailwindCSS components.

2. https://github.com/unfolding-io/nebulix

Nebulix, a Fast & Green Theme Based on Astro + Static CMS + Snipcart

git clone https://github.com/unfolding-io/nebulix
#.env

With very interesting components at /src/content/project/crafting-the-perfect-cosmic-mojito.mdx

#/src/content/project

#mogrify -format jpg *.avif #the images have to be jpeg or jpg to be zoomable

http://localhost:4321/work/crafting-the-perfect-cosmic-mojito/

3. https://github.com/themefisher/astrofront-astro

MIT | AstroJS-Powered Shopify Storefront Boilerplate with TailwindCSS and Nanostores. With Shopify ecommerce integration.

git clone https://github.com/themefisher/astrofront-astro

npm install
#npm audit fix
npm run dev #you will need shopify credentials for the .env

4. https://github.com/oxygenna-themes/foxi-astro-theme Which has an interesting /blog section with tags

MIT | Foxi is an Astro theme crafted with Tailwind CSS, designed for blazing-fast performance and seamless user experience. Perfect for creating modern, responsive SaaS websites with minimal effort.

You can see the blogs at /src/pages/blog folder, after:

git clone https://github.com/oxygenna-themes/foxi-astro-theme

npm install & npm audit fix
npm run dev #localhost:4321
#npx astro add mdx #npm install @astrojs/mdx

#npm install vue @panzoom/panzoom @vueuse/core @nanostores/vue @vueuse/components @vueuse/integrations vue3-toastify body-scroll-lock vue3-popper

// astro.config.mjs
import { defineConfig } from 'astro/config';
import mdx from '@astrojs/mdx';

export default defineConfig({
  integrations: [mdx()],
});

Remember that you need to migrate also the content collection for /src/pages/blog and to update /src/content/config.ts to define what are the fields expected on the new collection (for example we can call it properties instead of blog).

npm install -D tailwindcss@latest @tailwindcss/vite@latest daisyui@latest

• Post are writen with .mdx
• OpenGraph is included (als when sharing posts, but not the post image)
• Responsive blog section (kind of directory) where posts get filtered by tags
• Interesting header section (which follows you on laptop or mobile)

Deployed at: https://realestate_tool.jalcocertech.com/

docker build -t realestate_tool_v4 . #1m16s at x13 and 3m12s at pi4gb
#docker exec -it realestate_tool_v4 /bin/bash

services:
  realestate_photo_tool:
    image: realestate_tool_v4
    container_name: realestate_tool_v4
    ports:
      - "8506:8501"
    working_dir: /app
    restart: always
    networks:
      - cloudflaretunnel_tunnel
    command: streamlit run OpenAI_MigrateWebInfo_v4st.py
    #command: tail -f /dev/null

networks:
   cloudflaretunnel_tunnel:
     external: true

Once deployed:

npm install
npm run dev
#npm run build

npm install -g http-server
http-server dist #http-server .vercel/output/static

# npm install -g serve #serve the built files with npm
# serve -s dist #http://localhost:3000

As per the general webs checks docs.

1. Sitemap and Robots:

curl -s https://dm-real-estate.com/sitemap.xml -o /dev/null -w "%{http_code}\n"

curl -s https://dm-real-estate.com/robots.txt | head -n 10 #see the first 10 lines

2. Notify Search engines:

curl "https://www.google.com/ping?sitemap=https://dm-real-estate.com/sitemap.xml"
curl "https://www.bing.com/ping?sitemap=https://dm-real-estate.com/sitemap.xml"

3. WebCheck.xyz

4. DNS Config: The site is accesible from the base domain name as well as the www. subdomain

5. Responsiveness and ping

• Uptime Kuma
• https://github.com/KSJaay/Lunalytics?ref=selfh.st

1. Value-Based Pricing:

• Concept: Price is determined by the perceived value the AI application offers to clients.

This focuses on the outcomes and benefits users receive, such as finding the perfect property faster, making more informed decisions, and potentially increasing sales or client satisfaction for real estate professionals.

• Implementation:
  • Tiered Pricing based on Features & Value: Offer different subscription tiers with varying levels of features and recommendations. For example:
    • Basic Tier: Core recommendation engine with a limited number of property analyses or saved searches. Priced lower, suitable for individual clients or small-scale use.
    • Pro Tier: Enhanced recommendation capabilities, more detailed property insights (e.g., investment potential, neighborhood analysis), higher limits on usage. Priced higher, targeting real estate agents or frequent users.
    • Enterprise Tier: Fully customized solutions with advanced features like personalized reporting, integration with CRM systems, dedicated support. Priced significantly higher, aimed at real estate agencies or large organizations.
  • Outcome-Based Pricing (Potentially): This is more complex to implement but could involve pricing based on successful outcomes facilitated by the AI, such as a closed deal or a highly satisfied client. This would require robust tracking and agreement on what constitutes a “successful outcome.”
• Pros: Captures the true value of the AI, potential for higher revenue per user, aligns pricing with client benefits.
• Cons: Can be challenging to quantify the exact value for each user, may require strong communication and demonstration of ROI.

2. Subscription-Based Pricing:

• Concept: Users pay a recurring fee (monthly or annually) to access the AI application and its features. This provides a predictable revenue stream for the business.
• Implementation:
  • Tiered Subscriptions (as described in Value-Based Pricing): Different tiers offer varying features, usage limits, and support levels at different price points.
  • Per-User Pricing: Charging a fee for each user who accesses the application. Suitable for teams and organizations.
  • Usage-Based Pricing within Subscription: Offer a base subscription with a certain number of “credits” or “queries” per month, with additional usage incurring extra charges. This can balance predictability with variable usage.
• Pros: Predictable recurring revenue, encourages continuous engagement, allows for tiered feature access.
• Cons: Users need to see ongoing value to justify the subscription, risk of churn if the value isn’t consistently delivered.

3. Freemium Model:

• Concept: Offer a basic version of the AI application for free with limited features or usage. More advanced features and higher usage limits are available through paid upgrades.
• Implementation:
  • Free Tier: Provides core recommendation functionality with limitations (e.g., fewer properties analyzed, less detailed insights, watermarked reports).
  • Premium Tiers: Unlock advanced features, remove limitations, and offer better performance.
• Pros: Attracts a large user base initially, allows users to experience the value before paying, potential for organic growth through word-of-mouth.
• Cons: Requires a significant number of free users to convert to paid subscriptions to be profitable, the free version must provide enough value to attract users without cannibalizing paid features.

4. Usage-Based (Pay-as-you-go) Pricing:

• Concept: Users are charged based on their actual consumption of the AI application’s resources (e.g., number of property analyses, API calls, reports generated).
• Implementation:
  • Credits System: Users purchase credits that are consumed based on their usage of different features.
  • Tiered Usage Rates: Different price points for varying volumes of usage (e.g., lower cost per analysis for higher volumes).
• Pros: Flexible for users with varying needs, transparent pricing based on actual use, can be attractive for infrequent users.
• Cons: Revenue can be unpredictable, users might be hesitant to use the application extensively if costs accumulate quickly, requires careful tracking and billing infrastructure.

5. Hybrid Models:

• Concept: Combining elements of different pricing strategies to create a more tailored approach.
• Implementation:
  • Subscription with Usage Overage: A fixed monthly fee with additional charges for exceeding certain usage limits.
  • Freemium with Usage-Based Premium Features: Basic features are free, while advanced, resource-intensive features are charged based on usage.

Key Considerations for Your Pricing Strategy:

• Target Audience: Who are you primarily serving (individual buyers, renters, real estate agents, agencies)? Their willingness to pay and perceived value will differ.
• Value Proposition: Clearly articulate the benefits and ROI of using your AI application. How much time and effort does it save? How much better are the recommendations?
• Competitive Landscape: Analyze the pricing of existing real estate recommendation systems and AI tools. How does your offering compare in terms of features and price?
• Cost of Development and Operation: Ensure your pricing covers the costs of developing, maintaining, and scaling the AI application, including data acquisition, model training, and infrastructure.
• Customer Acquisition Cost (CAC): Factor in the cost of acquiring new users when determining pricing.
• Churn Rate: Monitor how many users stop using the application and adjust pricing or value proposition accordingly.
• Scalability: Your pricing model should ideally scale as your user base and features grow.

There are few static deployments options:

npm install -g firebase-tools

firebase login
firebase init
#firebase deploy

#firebase hosting:channel:list
#firebase hosting:channel:delete <channelId>

You just need to follow these commands:

npx wrangler pages project create #this will install the wrangler CLI package
#npx wrangler pages project list # See the projects you already have
#npx wrangler pages deployment list 

#npm run build #build the file manually

#https://developers.cloudflare.com/pages/configuration/build-configuration/#framework-presets
npx wrangler pages deploy dist # normally will be dist, but whatever <BUILD_OUTPUT_DIRECTORY>

##npx wrangler pages project delete your_project_name