How 7–8 Figure Amazon Brands Structure PPC Accounts (And Why Most Agencies Get It Wrong)

What “Account Structure” Actually Means — and Why It Determines Everything Else

Account structure is the way the campaigns, ad groups, keywords, match types, and ASINs are organized. This is the determining factor for whether your data is readable, whether your budgets are controllable, and whether scaling decisions are evidence-based rather than guesswork.

Poorly structured Amazon PPC accounts have ambiguous data, which means if three products share one campaign and only one of these keywords drives 80% of the spend, you can't tell which of the products converted and which ones are costing you money. This is because you're getting a blended signal, which tells you almost nothing.

The consequences of this are clear. Aggregate ACoS will look healthy while two or three products will be running at a loss, subsidized by the third. While the account might look successful, the brand is bleeding.

These structural mistakes are very predictable and are present in the majority of accounts that are run by agencies.

The 5 Most Common Amazon PPC Structural Mistakes Agencies Make

1. Grouping Multiple ASINs Into a Single Campaign

A brand with 12 products has 4 different campaigns that contain 3 products. Their budget is split between them based on which ad wins the auction and not by margin or strategic priority.

Without product-level separation, you can’t tell which ASIN is actually earning its budget, and you can’t allocate the spend on TACoS per product. Every time you try to scale a winner, you will end up dragging the budget towards the products that don’t deserve it.
When Spade to Fork came to us at Olifant, they had no product-level profitability tracking, which left the brand with a one-size-fits-all approach. This left them unable to prioritize winners or fix underperformers.

2. Running All Match Types in the Same Ad Group

When broad, phrase, and exact match keywords for the same product are sharing a single ad group, the campaign looks well-organized on the surface, but the data underneath is a mess.

These match types have completely different purposes. Broad match is a tool that is meant to surface new converting search terms; exact match is targeting shoppers with high intent that are ready to buy your product.

When you treat these two equally, the budget allocation between them is invisible because you can’t tell how much is going toward discovery versus how much is going toward conversion.

Broad match campaigns need aggressive negative keyword lists to prevent irrelevant search terms from eating away the budget. Exact match campaigns need almost none.

When both share the same ad group, applying negatives to one affects the other, and from there the whole system breaks down.

This is because broad match requires low bids to stay efficient during the discovery, and exact match justifies aggressive bids because the conversion data already supports them.

When you treat these two identically, it means you are overbidding on low-intent traffic and underbidding on clicks that convert.

3. Chasing Broad, High-Volume Keywords Instead of High-Intent Long-Tails

Most 7–8 figure Amazon brands lead with broad and high-competition category terms such as “protein bars," “jump rope," or "matcha powder” because these keywords carry the highest search volume. The problem with this is that there is high competition, which drives the CPCs up and the conversion rates down.

Brands at 7-8 figures rarely have the budget to outspend the category leaders on the broadest terms, but more importantly, they don’t need to. This is because high-intent, long-tail keywords already attract shoppers that are already close to a buying decision.

These keywords come with less competition, lower CPCs, and better conversion rates than broad category terms most agencies default to.

When Balanced Tiger came to Olifant Digital, their previous agencies had made the exact mistake, which involved chasing ultra-competitive keywords that drained the budget without delivering returns.

After we rebuilt their entire account structure and shifted targeting to high-intent long-tail keywords, their ACoS dropped by 50% and their revenue grew 171% in just two months.

4. No Negative Keyword Strategy

Most agency-managed accounts have no systematic negative keyword process. Their search term reports get reviewed occasionally rather than daily, and this means non-converting terms accumulate the spend month after month without being detected.

At $100K per month in ad spend, that’s a serious budget leak, but even at $20K per month the compounding effect is real and measurable.

A negative keyword list is not something you build once and forget. It is a living document that needs to be refined based on fresh search term data because brands that don’t do this frequently are leaving money on the table.

5. Reporting on ACoS Instead of TACoS

Most agencies provide ACoS reports, ad revenue, and total ad spend. But organic revenue is never mentioned, which means you don’t have a clear picture for your account.

An account can run a perfectly healthy 18% ACoS on paper while TACOs (Total Advertising Cost of Sales) are quietly rising in the background and organic rank is stalling.

This is the exact thing that Onsen Secret experienced before they partnered with Olifant Digital. Every attempt at scaling shrunk their profitability, while ACoS numbers in the monthly report looked fine.

The agency was optimizing for the wrong metric, and they had no visibility into what was happening to the business. After we restructured the strategy around TACoS-led reporting and shifted optimization decisions accordingly, their profit tripled.

How 7–8 Figure Brands Actually Structure Amazon PPC Accounts

ASIN-Level Campaign Architecture

Every product gets its own dedicated portfolio. Inside that portfolio, Olifant Digital builds all the campaigns for that specific product. This structure makes it immediately clear which campaigns are live, which keywords are being targeted, and exactly how each product is performing.

A brand with 10 products needs 10 separate portfolio structures, not 2 to 3 shared campaigns. This is what makes it possible to scale each product simultaneously without losing visibility or control.

Without having this architecture, every optimization decision will be made in the dark.

The 1-1-1-1 Method: One Campaign, One Ad Group, One Keyword, One ASIN

The 1-1-1-1 method means that one campaign contains one ad group, which targets one keyword against one ASIN. With this method, you eliminate blended signals, shared budgets, and attribution ambiguity entirely.

When a keyword performs, you scale that campaign with confidence because you know exactly what is driving the result. When it stops performing, you cut it or adjust the bid without that decision having any impact on the rest of your account.

This level of control is not possible to achieve in a multi-keyword, multi-product campaign structure, because when multiple ASINs and match types share a campaign, adjusting one variable will shift the performance of several others at the same time. This will turn every optimization decision into a guessing game.

The 1-1-1-1 method removes that guesswork by keeping every data point isolated and every decision clean

When we rebuilt MatchaBar’s Amazon account by using this structure, the brand added $114,305 in monthly revenue.

Balanced Tiger experienced 171% revenue growth and a 50% ACoS reduction in just two months after we applied the same approach to their account.

A clean account structure is not an organizational necessity, but it’s a foundation that makes profitable scaling decisions obvious, rather than uncertain.

Match Type Segmentation Across Separate Campaigns

At scale, each match type runs in its own dedicated campaign because they serve a different purpose, and this is why they also need a different management approach.

Broad match works as a discovery layer that feeds new converting search terms into tighter match types over time.

Phrase match handles controlled expansion, which happens around converting themes.

Exact match is where the full budget aggression is justified based on proven conversion data.

All the different tiers carry a different budget allocation, logic, and negative keyword strategy, and none of this can be managed correctly if they are all sharing the same ad group. The moment they get combined, they become impossible to control independently.

Competitor ASIN Targeting as a Standalone Campaign Layer

Product targeting via competitor ASIN should never be treated as an add-on to existing keyword campaigns.

When it’s structured correctly, it intercepts shoppers that are already in a competitor’s product detail page and who are considering making a purchase.

These are not just casual browsers but shoppers that have already searched and clicked and are evaluating a product in your category. This puts them at a much higher point of purchase intent than the average visitor. And since you are targeting a specific product page, rather than competing in a broad keyword auction, the competition is significantly lower, and the cost to reach a high-intent shopper is more efficient.

When Olifant Digital built this as a dedicated standalone layer for Spade to Fork, the competitor ASIN targeting campaigns became some of the top performers in the entire account, delivering low ACoS while growing ad sales by 132% on their own.

Sponsored Display for Retargeting — Not as a Search Replacement

Sponsored Display is a retargeting tool whose purpose is to re-engage shoppers who have already viewed a product page but did not make a purchase. It is used as a dedicated retargeting layer, because when it’s used on top of a correctly structured account, it compounds the conversion rate without inflating keyword CPCs.

The Budget Logic That Scales: The 60/30/10 Framework

Every properly structured Amazon PPC account allocates their budget in the specific ratio:

• 60% to exact match campaigns: This is where most of the budget should go because exact match operates on proven and high-converting keywords where the data is already clean and the conversion rates are already validated.
• 30% to phrase match and competitor ASIN targeting: This tier serves as a controlled expansion layer, which targets adjacent intent and captures relevant search variations that feed into the exact match tier over time.
• 10% to broad match discovery: This is the research budget, designed to surface new converting search terms at low volume and low risk before a serious spend is committed to them.

This exact framework directs the majority of the budget toward known conversions while maintaining a disciplined discovery pipeline. Brands that invert this ratio end up paying to run search term experiments at full scale with no proof of what converts.

What Olifant’s 1-1-1-1 Method Delivers in Practice

MatchaBar — $114,305 Added in Monthly Amazon Revenue
The structural problem: Multiple agencies left poorly structured campaigns, which drained the ad spend. MatchaBar had no clear architecture, had an unprofitable ACoS, and had no visibility into what was driving the performance.
The fix: When they partnered with Olifant Digital, we first rebuilt every single campaign by using the 1-1-1-1 method. This enabled the team to scale what worked and cut what didn’t work without wasting budget. Daily optimization and weekly A/B testing on the hero images ran in parallel.

Result: After these changes were applied, the end result was $114,305 added in monthly Amazon revenue.
Founder Graham Fortgang: “Working with Olifant has transformed our business. They have a marketing strategy for every quarter, and it’s clear what we should be working on together.”

Read the full case study here

Balanced Tiger — 171% Revenue Growth, ACoS Cut 50% in 2 Months

The structural problem: Balanced Tiger’s previous agencies all chased broad, ultra-competitive keywords that drained their budget without providing anything in return. Their account was stalling growth, which left no room for launching new SKUs.

The fix: We eliminated keywords that didn’t convert. We rebuilt their entire account around the 1-1-1-1 method with high-intent, long-tail targeting and added bundled product offerings to lift the average order value.

Result: After we applied all these changes to their account, they experienced 171% revenue growth, ACoS was cut by 50%, and the average order value doubled in two months.

CEO Adriano Bordoli: “Extremely effective! Excellent communication and project management on their side to implement widespread changes over a short period of time.”

Read the full case study here

Spade to Fork — 46% Revenue Growth in 44 Days, ACoS Down 19%

The structural problem: Spade to Fork only had a few campaigns per product but had no product-level profitability tracking. ACoS was climbing year over year, but no competitor targeting layer existed.

The fix: We rebuilt their product-level ASIN campaigns using the 1-1-1-1 method across the full catalog. Next, we added competitor ASIN targeting as a standalone campaign layer, and we included daily optimization from day one.

Result: The final result for Spade to Fork was a 46% revenue increase in just 44 days. Their ACoS went down 19% and ad sales grew 132% through competitor ASIN targeting alone.

CEO Jeff Kathrein: “Olifant works extremely closely on our account, and I am impressed with their support and know-how.”

Read the full case study here

Frequently Asked Questions

How should a 7-8 figure Amazon brand organize its PPC campaigns?

A 7-8 figure Amazon brand should organize its PPC campaigns by ASIN level.

This means each product should get its own dedicated structure with separate campaigns for each match type.

Exact match campaigns focus on proven and high-converting keywords. Phrase and broad match campaigns handle discovery and expansion, and dedicated competitor ASIN targeting campaigns intercept high-intent shoppers who are already on competitors' product pages evaluating their options.

The 60/30/10 budget split across these tiers is a reliable starting framework for most catalog sizes and categories.

Why do most Amazon PPC agencies get account structure wrong?

Most PPC agencies get account structure wrong because usually they inherit the disorganized accounts and optimize within the existing structure rather than rebuilding it.

Rebuilding not only takes time, but it requires difficult conversations with the client, and the process also produces no visible short-term wins.

This is what makes this process avoidable, because most agencies have a client relationship that is measured on monthly ACoS numbers rather than the quality of the underlying architecture.

Also, it is far easier to send a report showing aggregate ACoS rather than explaining to a client why their account needs a full structural overhaul before there are any meaningful results.

The outcome of this is an account that looks like it’s actively managed on the surface, but it’s running on a foundation that will never support profitable scaling past a certain spend level.

What is the difference between ACoS and TACoS in Amazon PPC?

In Amazon PPC, ACoS measures the ad spend as a percentage of the ad-attributed revenue. TACoS is a metric that shows you the ad spend against the total revenue, which includes both paid and organic.

On an account that is properly structured, you should see TACoS declining over time, as the organic rank starts to build from PPC velocity. If TACoS starts rising when ACoS looks flat, this means the organic revenue is stalling and the account is degrading even if the agency’s report looks clean.

How often should Amazon PPC campaigns be optimized?

Brands that are spending at scale should have daily optimizations, rather than weekly. This is because bid adjustments, negative keyword additions, and budget reallocations need to respond to the live data.

A term that drains the spend at high ACoS on Monday can cost a meaningful budget by Friday on the weekly review cycle. This is why weekly reviews are a structural disadvantage for brands that operate on 7-8 figures.

Ready to See What Your Current Structure Is Costing You?

If your account still runs on the same structure it launched with, the ceiling you are hitting is structural and not a budget problem. Get a free marketing plan with Olifant Digital, and we will break down your current campaign architecture and identify exactly what it is costing you.

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