u/jaxharlangolf

Update on the ads tool I've been building (mentioned it here before) — added something new this week that I think solves the real objection people have to automated Amazon Ads tools.

The tool already generates a weekly action list based on your actual royalty economics — what to negate, what to bid up, what to cut. That part's been running on my own library for months.

What's new: you can now approve those recommendations and have the tool actually make the change in your Amazon Ads account, instead of copying each one in by hand. But nothing happens automatically — you review, you approve, you get a plain-language confirmation of exactly what's about to change before it sends. It's meant to remove the tedious copy-paste part, not remove you from the decision.

Being straight about where this is: it's brand new, tested carefully on my own account this week including real live changes, but only one other person has used it so far. Looking for a few more beta testers to help validate it before I'd call it ready for wider use — if that's you, reply here or DM me.

Update on the ads tool I've been building (mentioned it here before) — added something new this week that I think solves the real objection people have to automated Amazon Ads tools.

The tool already generates a weekly action list based on your actual royalty economics — what to negate, what to bid up, what to cut. That part's been running on my own library for months.

What's new: you can now approve those recommendations and have the tool actually make the change in your Amazon Ads account, instead of copying each one in by hand. But nothing happens automatically — you review, you approve, you get a plain-language confirmation of exactly what's about to change before it sends. It's meant to remove the tedious copy-paste part, not remove you from the decision.

Being straight about where this is: it's brand new, tested carefully on my own account this week including real live changes, but only one other person has used it so far. Looking for a few more beta testers to help validate it before I'd call it ready for wider use — if that's you, reply here or DM me.

I've been posting here about break-even ACOS and TACOS for a while. I build a tool called Troven Ads Optimizer that does the calculation side of it, and I'm looking for a handful more people to use it.

What it does: connects to your Amazon Ads account through Amazon's official API, pulls your campaign data weekly, and gives you a prioritized list of what to change — negations, bid changes, pauses, and converting search terms worth promoting to manual exact. Each recommendation shows the arithmetic, so you can check it rather than trust it.

The part I care about most: it calculates break-even ACOS per book from your actual KDP royalty data, not a rule of thumb. A $14.99 paperback and a $4.99 ebook have completely different break-evens, and most bid advice ignores that.

What it doesn't do: it reads your data and recommends. You apply the changes yourself in the Amazon console. Nothing happens to your account without you doing it.

Who it suits: nonfiction, $300+/month in ad spend, running ads at least a few months. It's a poor fit for KU-heavy fiction, because Amazon never attributes page reads to keywords — no tool can fix that and I'd rather say so than sell you something.

It's free during beta. I'm not taking payment yet. In exchange I want honest feedback, including when it's wrong — my current beta user emailed me last week saying he couldn't figure out what it was telling him, and that one email produced four fixes.

Two testers so far. Looking for a few more, not a crowd.

DM me if interested.

I've been posting here about break-even ACOS and TACOS for a while. I build a tool called Troven Ads Optimizer that does the calculation side of it, and I'm looking for a handful more people to use it.

What it does: connects to your Amazon Ads account through Amazon's official API, pulls your campaign data weekly, and gives you a prioritized list of what to change — negations, bid changes, pauses, and converting search terms worth promoting to manual exact. Each recommendation shows the arithmetic, so you can check it rather than trust it.

The part I care about most: it calculates break-even ACOS per book from your actual KDP royalty data, not a rule of thumb. A $14.99 paperback and a $4.99 ebook have completely different break-evens, and most bid advice ignores that.

What it doesn't do: it reads your data and recommends. You apply the changes yourself in the Amazon console. Nothing happens to your account without you doing it.

Who it suits: nonfiction, $300+/month in ad spend, running ads at least a few months. It's a poor fit for KU-heavy fiction, because Amazon never attributes page reads to keywords — no tool can fix that and I'd rather say so than sell you something.

It's free during beta. I'm not taking payment yet. In exchange I want honest feedback, including when it's wrong — my current beta user emailed me last week saying he couldn't figure out what it was telling him, and that one email produced four fixes.

Two testers so far. Looking for a few more, not a crowd.

DM me if interested.

A few weeks back I posted about the tool I built to automate weekly ad optimization for my own books. Since then I've had a couple of real beta users running it too, and a few things have become pretty consistent across all of us — figured I'd share since it's the kind of stuff that's hard to know until you're actually tracking it week over week.

TACOS matters more than ACOS. ACOS only measures ad spend against ad-attributed sales — it has no idea whether the book is also selling organically. TACOS = spend ÷ (ad sales + organic sales + KENP page reads). It's the number that actually tells you if a campaign's earning its keep, especially once a book has any organic rank at all.

Don't judge any single week. Every one of us has had weeks that looked terrible in isolation, then leveled out once there was enough data to see the real trend. If you're checking daily or even weekly without context, you'll make bad decisions off noise.

Auto campaigns are for discovery, not profit. Expect them to look rough while they're finding your real converting search terms. The payoff comes from pulling proven terms into manual exact campaigns where you control the bid — not from the auto campaign itself ever looking great. And once you move a term over, negate it in the auto campaign too — otherwise you're bidding against yourself for the same search, splitting spend across two campaigns competing for the identical click.

Impressions without clicks usually means a listing problem, not a targeting problem. Had a case this week where a campaign was getting huge visibility and barely any clicks — turned out to be mismatched cover/positioning, not the ad itself.

Still taking on a few more beta users if any of this is useful to you directly — free for 60-90 days, just want honest feedback. Happy to answer questions here either way.

I built a tool that automates my own weekly Amazon Ads optimization — looking for a few beta testers

Not sure if this is the right place, mods feel free to remove if not — this isn't a book, just sharing a tool.

I've been running Amazon Ads on my own KDP books for a while now, and built something to automate the weekly grind: pulling reports, flagging keywords/ASINs that are burning spend with zero purchases, recommending bid adjustments, catching stuff that's easy to miss when you're doing it by hand every week.

Looking for 5-10 nonfiction authors to try it free for the next couple months — the only ask is honest weekly feedback (what's useful, what's not, what's flat wrong) and permission to reference anonymized results later. No cost, no catch.

Rough fit: Been running ads for at least a few months already so there's real data to work with, spending at least a couple hundred a month on ads currently.

Drop a comment or DM if you want in — happy to answer questions here too.

Been optimizing KDP ads for about 6 months across a few golf titles and changed my approach to underperforming match types after making a costly mistake early on.

My original approach when substitutes or complements started burning spend with no conversions: pause the match type entirely. Felt decisive. Turned out to be too blunt.

The problem is that Amazon's auto campaigns let you set separate bids per targeting group — close match, loose match, substitutes, complements each get their own bid. So when complements is generating noise, you don't have to kill it. You can drop it to $0.75 and let it run at a price that makes sense for the occasional genuine buyer, without paying full price for all the adjacent browsing that won't convert.

The distinction that changed how I think about it: complements traffic isn't wrong intent, it's weak intent. Someone browsing golf equipment might still buy a golf book. At $0.75 that's a reasonable bet. At $1.50 it's not.

Same logic applies to substitutes — comparison shoppers who chose a competitor book this week might choose yours next week. Reducing the bid keeps you visible without subsidizing the misses.

The rule I use now: reduce the targeting group bid to minimum first, watch for 3-4 weeks. If it converts even once or twice at that low bid, leave it running. If nothing after 4 weeks, then pause. The negation list handles individual bad search terms regardless.

Curious whether others have found the targeting group bid controls useful or if you just pause match types outright when they underperform.

Been running ads across a few golf titles for about 6 months now and spending around $400–$500/month US. Some weeks feel like money well spent, other weeks I wonder if I'm burning cash.

Curious where others are at — especially nonfiction authors. Is $300–$500/month typical for someone with 3–5 books? Are there people spending significantly more and seeing proportional returns?

Not looking for advice necessarily, just want to know if I'm in the right ballpark or way off compared to what others are doing.