Customadeonly

Executive Summary

Founded in 2013, Customadeonly has spent over a decade manufacturing high-precision wheel spacers and adapters for the automotive aftermarket, using automated CNC machining to deliver products built to exact tolerances every time.

By mid-2023, the brand had scaled to nearly 1,000 active FBA SKUs, but the ad account hadn't kept pace. All product types were running inside the same campaigns with no segmentation by ASIN or fitment. An estimated 15–20% of impressions were landing on buyers whose vehicles were incompatible with the product being shown, a structural flaw invisible in any native Amazon report.

SellerApp rebuilt the account architecture from the ground up, combined with precise bid optimization across the restructured campaigns. Monthly revenue grew from $159K to $379K, monthly orders tripled from 2,809 to 8,421, and ACoS held flat at exactly 10.1% throughout.

About the Brand

Customadeonly is a private label brand that manufactures and sells wheel spacers and adapters for automotive use on Amazon through FBA and FBM. Wheel spacers are components that fit between a vehicle's hub and wheel to adjust fitment, track width, and clearance, a product where getting the specifications wrong isn't just a missed conversion; it's a safety issue.

Every SKU is defined by bolt pattern, hub bore, thread pitch, and offset. Every buyer arrives with a specific vehicle and specific measurements already in mind. A 5x120 spacer built for a BMW 5 Series does nothing for a buyer with a Subaru that runs on a 5x114.3 bolt pattern. Showing the wrong fitment earns a return, a one-star review, and a customer who doesn't come back.

By mid-2023, CustomadeOnly had grown to nearly 1,000 active FBA SKUs across dozens of bolt-pattern and hub-bore configurations, covering a wide range of vehicle makes and model years. The catalog was large, technically complex, and growing fast. And it had outgrown the campaign structure meant to support it.

Rethinking the Growth Strategy for CustomMadeOnly

Customadeonly came in with a clear goal, and that was to grow sales.

ACoS was holding at 10.1%, and the account looked manageable on the surface. But the conversion rate sat at 5.4%, and traffic volume wasn't translating into the revenue growth the catalog size should have been generating.

SellerApp focused on understanding why traffic wasn't converting before touching a single bid. That meant looking at which products were being promoted, which searches triggered them, and whether the buyers reaching the listings were actually compatible buyers.

At the same time, the goal wasn't just efficiency but to build a foundation where organic and paid performance could grow together and where a catalog of nearly 1,000 SKUs could be managed with precision rather than by increasing ad spend.

Challenges Customadeonly faced before SellerApp

On the surface, the account looked steady. ACoS was stable, traffic was flowing, and activity levels were high. But underneath that, the numbers pointed to something the standard dashboard wasn't surfacing.

Challenge 1: Traffic Without Conversion

Before SellerApp, the account had wheel spacers, adapters, and multiple bolt-pattern families (5x114.3, 5x120, and 6x139.7), all running inside the same campaigns. A search for "5x120 BMW wheel spacers" could trigger an ad for a 5x114.3 Subaru product.

The click was charged. The buyer couldn't purchase. Multiplied across hundreds of SKUs and thousands of daily impressions, this was the single largest source of structural waste.

Within each product type, there was also no segmentation by fitment. Hub bore, thread pitch, and offset were not used to structure ad groups, which meant buyers with highly specific requirements were being served products that didn't match their vehicle specs.

Challenge 2: All Products were combined into one campaign

Every product type, including wheel spacers, adapters, and multiple bolt-pattern families, was running inside the same campaigns. There was no segmentation by ASIN. There was no segmentation by fitment. A broad automotive search query could trigger any variant in the catalog, regardless of compatibility.

This made it impossible to isolate what was working. Performance data was blended across hundreds of ASINs, which meant the signals needed to optimize were buried inside averages that told you very little about what was actually happening at the product level.

Challenge 3: Invisible Structural Waste

Generic automotive terms like "wheel spacers," "hub spacers," and "car spacers" and searches from buyers with incompatible vehicle makes were triggering ads continuously. Some terms had accumulated dozens of clicks over 30 days with zero purchases. Lug nut queries, a completely separate purchase intent, were also triggering wheel spacer ads. None had been negated. Every click was paid for. None were buying.

How SellerApp Turned Spend Into Results for Customadeonly

Once the diagnosis was clear, the strategy moved away from broad optimization and toward precision at every level of the account. Rather than making isolated adjustments, SellerApp rebuilt the structural foundation so every subsequent optimization had something solid to act on.

1. ASIN and Fitment Segmentation First

Before SellerApp: One campaign type, all products mixed wheel spacers, adapters, 5x114.3, 5x120, and 6x139.7 all triggering against the same search queries.After: Each product type broken into its own campaign. Each fitment bolt pattern, hub bore, and thread pitch is is broken into its own ad group. A search for "5x114.3 25mm hub-centric spacer" now only triggers products with that exact spec. Cross-fitment clicks stopped immediately.

This single change created the visibility that made everything else possible. For the first time, the team could read per-fitment performance, not blended averages across 600 ASINs.

2. ASIN Tiering Across the Full Catalog

With campaigns now readable at the ASIN level, every SKU was evaluated against four signals: 90-day conversion rate, BSR trajectory, inventory health, and organic rank momentum. The top 20 or so Tier 1 ASINs, those with real sales velocity across five bolt-pattern families, received 70% of the total budget. Tier 2 ASINs with growth potential received 20% via structured discovery campaigns. The remaining long tail was deprioritized and stopped being funded at equal standing.

3. 100+ Negative Keywords, Built From Real Data

A master exclusion list was built from 30 days of actual search term data. Any term that earned a click without a conversion was flagged, no exceptions, no second chances.

Coverage was thorough, including incompatible vehicle makes, competitor bolt patterns, lug-nut queries (a separate purchase intent), and informational searches that were never transactional. Over 100 negatives were deployed at the campaign level, not just the ad group level, so exclusions applied to every match type.

Total impressions dropped approximately 20% immediately. That was the goal.

4. Vehicle-Specific Targeting at the Top of Search

Tier 1 campaigns were rebuilt around exact-fit search term queries like "5x114.3 25 mm hub-centric spacers for Subaru WRX" rather than broad category terms. A buyer searching at that level of specificity already knows their bolt pattern, their offset requirement, and their budget.

Top-of-search bid modifiers were set at +50–75% for these high-intent, vehicle-specific queries. The right buyer was at the top of the page when they were ready to purchase.

5. Rule-Based Bid Automation

The final layer was a self-managing bidding system designed to maintain performance between human reviews. Non-converting clicks auto-down-bid after hitting defined thresholds. High performers auto-scaled within efficiency guardrails.

Repeat-converting search terms were promoted automatically to exact-match campaigns. Placement-level modifiers constrained the rest-of-search spend when it underperformed.

The system kept the account continuously calibrated, rather than drifting between optimization cycles.

Execution Framework

Execution ran on a weekly cadence throughout the engagement.

Search term reports were reviewed every week. Underperforming and irrelevant queries were negated on an ongoing basis to prevent wasted spend from compounding. Converting terms were isolated into dedicated exact-match campaigns for tighter control.

ASIN-level performance was tracked independently from campaign-level aggregates, with budget shifting dynamically toward the bolt-pattern families delivering stronger conversion rates each week.

Bid adjustments were made continuously based on the latest conversion data, not held for monthly reviews. High performers scaled. Non-converters reduced. The account stayed calibrated without drift.

Inventory levels and organic rank momentum were monitored alongside campaign performance each week to keep spend aligned with operational reality.

Results and Business Impact

When SellerApp took over in July 2023, the account was converting at 5.4% with monthly revenue of $159K, not obviously broken but not operating anywhere near its potential.

The fix wasn't more spending. It was a better structure.

Within the first several months, ASIN segmentation and negative keyword cleanup began redirecting budget toward traffic that was actually converting. The results compounded as the structure took hold.

Monthly revenue grew from $159K to $379K: a 138% increase driven by efficiency and targeting precision, not increased investment. Monthly orders went from 2,809 to 8,421, a 200% increase. The conversion rate climbed from 5.4% to 9.0%, and monthly clicks grew 84% to 27,393, both pointing to stronger alignment between who was seeing the ads and who was ready to buy.

Monthly revenue grew from $159K to $379K: a 138% increase driven by efficiency and targeting precision, not increased investment. Monthly orders went from 2,809 to 8,421, a 200% increase. The conversion rate climbed from 5.4% to 9.0%, and monthly clicks grew 84% to 27,393, both pointing to stronger alignment between who was seeing the ads and who was ready to buy.

ACoS held at exactly 10.1% throughout: the same figure as when SellerApp started, now applied to a revenue base that had more than doubled. ROAS held at 9.9x across a business that had tripled in orders.

Key Takeaway

CustomadeOnly's problem was never traffic. The impressions were there. The clicks were there. What wasn't there was structural alignment between what the campaigns were serving and who the buyers actually were.

The turnaround came from doing less, better. Fewer campaigns carry everything, but each one is built around a specific product type and fitment. Fewer keywords, but the right ones. Spend time following conversion signals instead of chasing impression volume.

The account needed to stop paying to reach the wrong ones.

By the time SellerApp stepped in, the structural misfiring had been running long enough to normalize. The metrics looked like a targeting problem. Underneath, it was architectural. Fixing targeting without addressing the campaign structure would have produced only a temporary improvement, followed shortly by the same outcome.

A 1,000-SKU catalog needs a 1,000-SKU-level structure, one that can see performance at the ASIN and fitment levels, not just in aggregate. Without that, optimization is guesswork dressed up as strategy.

If you see your account in this story traffic that isn't converting, spend that keeps rising, and a catalog that's outgrown its own structure, the problem is worth a closer look.

Don't just take our word for it.