Best Paid-to-Click (PTC) Websites in [2025]

How We Calculate Our PTC Site TrustScores

At Bzillion.Club, our mission is to provide a transparent and reliable platform for our users to discover quality PTC (Paid-To-Click) websites. To achieve this, we've implemented a sophisticated yet fair system for calculating a "Trust Score" for every site listed. This helps you make informed decisions and ensures that genuine, high-quality sites are recognized.

Our "Trust Score": A Smart Approach to User Feedback

Unlike a simple average of upvotes, our Trust Score uses a statistical method called Bayesian Average. Why? Because a simple average can be misleading, especially for new sites with very few votes. Imagine a new site with 1 upvote and 0 downvotes — a simple average would give it a perfect 100% score, which isn't fair or realistic.

Here's how our Trust Score works:

1. Community Baseline (M): We calculate a global average upvote ratio (let's call it 'M') across all websites listed on our platform. This 'M' represents the general sentiment or quality baseline of the PTC sites in our directory.
2. Confidence Factor (C): We introduce a 'Confidence Factor' (C). Think of 'C' as a set of "placeholder votes" that are initially assigned to every site. These placeholder votes reflect our initial confidence in the site being close to the community baseline.
3. The Calculation:
   The Trust Score for each individual website is calculated using this formula:
   $$ \text{Trust Score} = \frac{(\text{C} \times \text{M}) + \text{Website Upvotes}}{(\text{C}) + \text{Website Total Votes}} $$
   • For New Sites / Sites with Few Votes: When a site has very few actual user votes, the 'C × M' part (the community baseline with our confidence) plays a larger role. This prevents new sites from instantly plummeting (or rocketing) based on just one or two votes, giving them a fair chance.
   • For Established Sites / Sites with Many Votes: As a site accumulates more and more user upvotes and downvotes, its actual 'Website Upvotes' and 'Website Total Votes' start to heavily outweigh the 'C × M' component. This means the Trust Score increasingly becomes a true reflection of the community's experience with that specific site.

   This method provides a robust and dynamic score that accurately reflects user sentiment while also being resilient to manipulation and fair to sites at all stages.

Why This System Builds Trust:

• Fairness: New sites aren't instantly penalized or given an unrealistic boost.
• Accuracy: Scores genuinely reflect community sentiment once enough votes are in.
• Resilience: The Bayesian approach makes it harder for a few fake votes to significantly skew a site's rating.
• Transparency: Our logic is clear, allowing you to understand how scores are derived.

We believe that a transparent and intelligent ranking system is crucial for a healthy and trustworthy PTC community. By understanding how we calculate these scores, you can be confident in the information we provide and continue to help us build the most reliable PTC directory.

Your votes matter! By actively upvoting and downvoting sites based on your experience, you contribute directly to the accuracy and fairness of our entire system.