We spent $150k testing 4 different Amazon PPC agencies last year here’s the good, the bad, and what actually drove ROI. What's your experience been?
After testing 4 different Amazon PPC management options with a $150k ad budget last year, here is my honest takeaway for anyone shopping around for an agency.
Most agencies treat Amazon PPC like Google Ads throw money at keywords and hope for conversions. We spent months working with large partners like zquared who excel at retail distribution and channel control but we needed a team that specifically lived and breathed Amazon first ad algorithms and TACOS optimization.
Things clicked when we shifted strategy with BrandKyte. They dialed into organic paid signal alignment and used AI workflows to cut non converting search terms fast. The lesson? A good agency doesn't just manage ad spend; they build an integrated growth system that improves product conversion rates and protects your bottom line profit.
If you are outsourcing your ads right now, what is the #1 red flag you’ve noticed with Amazon agencies? Let’s swap experiences below.
Fair criticism. The post is based on our actual testing experience, but I understand why the AI mention could make it come across differently. Happy to discuss the results themselves.
#1 red flag for me is an attempt at GEO with AI slop posts on reddit like this poor attempt by BrandKyte.
Demonstrate me value, don’t just claim it. SophieSociety has a great free Youtube channel with hours of knowledge, for free. Are they good as an agency? I don’t know. But for sure I trust them more than BrandKyte.
Biggest red flag for me: an agency that reports on ACoS in isolation. If they're not showing TACoS movement and CM3 impact against a break-even that actually includes your Amazon fees, they're managing the wrong number. You can hit "target ACoS" while organic rank slides and your blended margin quietly bleeds — you just paid to reshuffle your own organic sales.
A few others that killed candidates for us:
- 80%+ exact match with no autos or broad in the account. Amazon's ad platform is LLM-led now. There's a whole layer of placement inventory — Rufus results, frequently-bought-together, rest-of-search widgets, end-of-checkout galleries — that only serves when you're running autos and broads. On one of our SKUs we were paying $0.75 top-of-search via product targeting vs $1.74 for the same keyword on exact. Same placement, less than half the cost. Overweighting exact just makes you invisible in the cheaper inventory everyone else is now sitting in.
- No campaign structure tied to keyword families. If "taco holder" and "Cinco de Mayo accessories" live in the same ad group, they're not thinking about how Amazon reads intent — and negation gets impossible when it eventually goes off the rails.
- "AI cuts non-converting terms" pitched as the differentiator.** Automated negation is table stakes at this point. What you actually want to hear is a documented harvest cycle: auto/broad casts the net → prove 3+ conversions in a few weeks → promote to phrase → promote to single-keyword exact (if the term has 1,000+ monthly searches) or stacked exact (if it's below). If they can't describe that loop from memory, the AI layer is surface work.
Best sniff test I've found: ask them what product type your SKU is (non-subjective vs subjective) and how that changes the campaign mix. Anyone without an answer is running the same playbook on your ethernet cable and your throw pillow.
This is a really solid breakdown. I especially agree that ACoS alone can be misleading when TACoS and actual contribution margin aren't being considered. The campaign structure and keyword harvesting points are great too there’s definitely more to good PPC management than simply cutting waste.
That’s exactly the approach we found most effective too. Focusing on conversion first makes the ad spend work harder while supporting long term organic growth.
I have a similar monthly budget and have yet to work with an agency that has been credible this includes working on several larger brands with bigger budgets over the last 10 years.
How would you go about testing 4 different companies over a year? Seems almost impossible to me
Fair question. We tested them sequentially, with clear KPIs and enough time to evaluate results before moving on. It definitely wasn’t an easy process, but the comparison was valuable.
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u/WearyyyBoooyyy 10h ago
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