I built InteliAds because KDP Amazon Ads are too easy to waste money on.
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Hey Product Hunt,
I’m building InteliAds, a tool for KDP authors and self-publishers who run Amazon Ads for their books.
Here’s the thing.
Amazon Ads can work, but managing them every day is painful.
You have keywords spending money.
You have search terms getting clicks but no sales.
You have ACOS going too high.
You have good keywords that should be scaled, but they get forgotten.
And then you still need to check CPC, CTR, ROAS, bids, spend, orders, and campaign performance.
So the real problem is not only running ads.
The real problem is knowing what to do next.
Should this keyword get a lower bid?
Should this search term be negated?
Should this target be paused?
Should this winner be scaled?
That’s why I built InteliAds.
It helps monitor Amazon Ads 24/7 using simple IF/THEN rules, so authors can reduce wasted clicks, control bids, pause weak targets, find winning search terms, and protect their book margins.
Right now, it is rule-based, not full AI yet. I wanted the first version to be simple, controlled, and safe, because authors should not feel like a black box is spending their money.
I’d really love feedback from KDP authors, self-publishers, Amazon Ads users, or anyone who has managed PPC campaigns for books.
What would you need to see before trusting a tool like this with your campaigns?
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This is smart, especially because you are not jumping straight into full AI autopilot.
When money is involved, black-box automation gets scary fast. Authors need to understand why a keyword was paused, why a bid changed, or why a search term got negated.
I’m building Traction for small businesses, and we keep coming back to the same idea: automation is only useful if the business owner still understands what is happening and why.
Rule-based actually feels like the right first version here. It gives people control before you ask them to trust the system with spend.
If I were testing this, I’d want to see:
what rule triggered
how much money it may have saved
what action it recommends
whether I can approve before it changes anything
a simple history log so I can trust it over time
Curious — are you planning to start with recommendations first, or let users auto-apply rules from day one?