Have you put up a website and tried some of the following simple, common monetization techniques? Let's talk case studies. Please give us some feedback as a comment, for starters.

 

1. What's your website about? Feel free to keep it anonymous.

2. Do you charge for advertising? How do you go about marketing, rates and ad placement (framework)? For example, do you tell potential advertisers your visit volume? What's your success been? What's worked best and worst?

3. How about Google Adsense and Adwords? Have you used them and what has your experience been?

4. How do you go about implementing Search Engine Optimization and what has your experience been?

5. Do you have an online store? Are you a reseller or a source of products? Do you use a framework or component for your store/cart/checkout?

6. What's your endgame strategy? Do you plan an exit? Do you have a monetization plan or did you just start the site with the intention of selling it at some point?

7. What are your feelings about putting up a custom site vs using the piggyback technique with a Facebook, etc?

8. Do you have other monetization approaches like membership fees, etc? What has your success been?

9. Please tell us some tips and lessons learned. Ask some questions. We're eager to learn from your experiences and give you feedback. These are just a few questions that came to mind. Feel free to tell us what you know.

10. Is your website a primary frontpiece for the startup or is it an extension of something else, perhaps a bricks and mortar business or a partnership?

 

That's a start!

 

 

Views: 50

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Nuxt Introduces Native Request Cancellation and Async Handler Extraction for Performance Gains

Nuxt 4.2 elevates the developer experience with native abort control for data fetching, improved error handling, and experimental TypeScript support. With a 39% reduction in bundle sizes and a streamlined app directory, this release enhances performance and project organization, positioning Nuxt as a leading choice for full-stack web applications built on Vue.js.

By Daniel Curtis

OpenAI and Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI Foundation

OpenAI and Anthropic have donated their AGENTS.md and Model Context Protocol projects to the Agentic AI Foundation (AAIF), a new directed fund under the Linux Foundation. Block contributed their agent framework, goose, as another founding project, and several other tech companies have joined as Platinum members.

By Anthony Alford

Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads

Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services.

By Craig Risi

Article: Building Streaming Infrastructure That Scales: Because Viewers Won't Wait Until Tomorrow

In streaming, the challenge is immediate: customers are watching TV right now, not planning to watch it tomorrow. When systems fail during prime time, there is no recovery window; viewers leave and may not return. One and a half years ago, at ProSiebenSat.1 Media SE, we faced the challenge of scaling streaming applications for international users.

By Daniele Frasca

Target Improves Add to Cart Interactions by 11 Percent with Generative AI Recommendations

Target has deployed GRAM, a GenAI-powered accessory recommendation system for the Home category, using large language models to prioritize product attributes and capture aesthetic cohesion. The system helps shoppers find compatible accessories, integrates human-in-the-loop curation, and achieved measurable improvements in engagement and conversion.

By Leela Kumili

© 2025   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service