I built TickClip because shopping advice is optimized for clicks—not buyers

I’ve spent years working in affiliate marketing and helping generate more than $500,000 in affiliate revenue.

That experience taught me something uncomfortable: nearly every shopping platform benefits when the consumer buys, even when the smartest decision is to wait—or not buy at all.

So I built TickClip, a buyer-first AI shopping assistant designed to answer one question:

Is this product actually worth buying right now?

TickClip analyzes signals such as price history, product quality, seller trust, customer reviews, discount authenticity, and market conditions. It then provides one of three clear verdicts:

• Tick: Buy it now

• Clip: Wait for a better price or more evidence

• Skip: Avoid this purchase

Each verdict includes a score, confidence level, supporting evidence, counter-signals, fair-price context, and relevant alternatives.

The larger vision is to make TickClip a fiduciary decision layer for e-commerce—technology that represents the buyer’s interests at the moment of purchase.

We are deliberately moving away from the traditional “everything is a deal” model. TickClip can tell users not to buy, and its verdicts are not influenced by affiliate commissions.

I’d love feedback from the Indie Hackers community:

1. Would you trust an AI assistant to tell you not to buy something?

2. What evidence would make a Buy, Wait, or Skip verdict credible to you?

3. What is the biggest source of regret in your online purchases?

You can try it at https://www.tickclip.ai

I’m especially interested in honest criticism—this is a difficult trust problem, and I want to build it around how real buyers make decisions.