I'M MEME

How I'M MEME Took ACoS from 32% to Under 18%and Grew Ad Revenue by 54.19% on Amazon Japan

In 90 days, SellerApp turned I'M MEME's cannibalized campaign structure into a coordinated system with search term analysis, negative targeting, keyword research, AI automation, and biweekly strategy sessions working in concert. Ad revenue grew by 54.19%; ACoS fell from 32.22% to 17.59%.

Amazon Japan beauty brand advertising

Executive Summary

I'M MEME had been running its own Amazon Japan advertising in-house for over a year before SellerApp got involved. The brand runs the full ad stack, SP, SB, SD, and SBV, fulfilled through FBA, anchored by its hero Multi-Stick Shading in Light Cool Bronzer.

The breaking point was a bad quarter, as ad spend climbed while conversions stayed flat. The internal team was spending nearly 70% of their work week pulling search term reports and manually adding negative keywords to stop campaigns from bidding against each other, time that should have gone into brand building and product localization instead.

Within 90 days of bringing in SellerApp, ad revenue grew 54.19%, ACoS dropped from 32.22% to 17.59%, conversion rate jumped 80%, and CTR improved 42%. Impressions fell from 3.37M to 1.95M, a deliberate cut of low-intent traffic, not a loss of reach to the traffic that actually converts.

About the Brand

IM’MEME is a K-beauty makeup brand founded in 2012 by Hyungseok (Dino) Ha, under parent company MBX (formerly Memebox). Their brand focuses on empowering self-expression through portable, creamy, and buildable makeup products. They are selling makeup on Amazon Japan through FBA as an enterprise-level seller, anchored by the Multi-Stick Shading in Light Cool Bronzer.

The brand was already running a hybrid setup, with in-house management supported by external help, and using every major Amazon ad type available, including Sponsored Products, Sponsored Brands, Sponsored Display, and Sponsored Brand Video.

I'M MEME's account came with real scale, a sizable catalog, and a campaign reach that required SellerApp's automation tooling to manage properly, not just another set of hands doing the same manual work.

What Challenges I'M MEME Faced Before Partnering with SellerApp

The account wasn't underinvested or under-resourced. It was working against itself, and the team didn't have the visibility to see where.

Challenge 1: High ACoS Despite Constant Manual Optimisation

The team was actively managing the account, adjusting bids and campaigns regularly. Despite that effort, ACoS held at 32.22%. This wasn't a lack of effort, as the team was spending close to 70% of their week on manual bid changes and search term cleanup and still couldn't move the numbers. Manual optimization had hit a ceiling that more hours couldn't break through.

Here's the kind of problem that doesn't show up in a dashboard, but our account manager has solved it:

A single product needs bids across four text variations to capture the same intent, and without tight match-type control, those variations cannibalize each other too. リップティント (Katakana for "lip tint") and its Romaji equivalent could both trigger ads from overlapping campaigns, the brand bidding against itself for the same shopper twice over.— Bhavey Ratra, Account Manager for IM’MEME, SellerApp

Challenge 2: Manual Ad Optimisation Eating Up Campaign Manager Time

Every adjustment, bid, budget, and search term review was done by hand, consuming close to 70% of the team's week. That left almost no time for brand building, creative strategy, or the localization Japan specifically demands.

Challenge 3: No Visibility Into Top-Performing Search Terms

Without clear reporting on which search terms were actually converting, budget had no reliable signal to follow. Decisions were being made on instinct, not data.

What SellerApp Changed

SellerApp's approach combined AI-driven automation, search term analysis and negative targeting, keyword research and rank tracking, and bi-weekly strategic consultations applied directly against the challenges above. As a managed services engagement, this meant SellerApp's proprietary automation tooling was running directly against a catalog and campaign footprint too large to manage by hand.

1. Ad Group-Level Negative Targeting to Stop Cannibalisation

Campaigns were restructured with negatives applied at the ad group level. The lip glow oil example is the clearest illustration, like adding "oil" as a negative keyword to the generic lip glow campaign stopped the internal bidding war on "hyaluronic lip glow oil" outright. CPC on that exact term dropped by a 54% cost reduction with zero loss in visibility.

2. Daily-Level Automation in Place of Manual Bid Management

Automation was enabled to handle bid and budget adjustments on a daily basis, replacing the manual review cycle the in-house team had been running. Japan's auction prices move fast enough that a person checking in once a week is always behind. Daily automation closed most of that gap, freeing the campaign manager from the grind that had been consuming 70% of their week.

3. Negating Low-Intent Search Terms Proactively

265 high-risk search terms, including broad queries like "lip stain," were identified and negated before they could bleed significant spend. Of the total ad spend, confirmed waste was capped at 3.33%. Left unaddressed, that same set of terms was projected to balloon to as much as 141% of total ad spend in wasted spend based on average per-term bleed; proactive negation insulated the budget from a much larger loss.

4. Bid Automation and Dayparting

Bid automation and dayparting were deployed to flex spend with actual performance windows instead of static, manually set bids, directly supporting the daily-automation shift above.

5. Keyword Research and Rank Tracking

Continuous keyword research and rank tracking gave the account an ongoing read on which terms were earning their spend, directly replacing the visibility gap on search term performance that had been a standing challenge.

6. Bi-Weekly Strategic Consultations

Regular consultations kept tactical execution tied to I'M MEME's actual business goals rather than running as an isolated optimization exercise.

Before partnering with us, the team tried doubling down on manual tweaks, but human eyes simply cannot compete with an algorithmic auction in real time. If they had just hired another person, they would have been burning money on both ads and payroll.

A human can pull a report once a week, but in Japan's hyper-competitive market, bid prices shift by the hour. By the time you manually find a cannibalizing keyword, the budget is already gone.— Sayantan Chatterjee, Sr. Product Manager, SellerApp

Results & Business Impact

Over a 90-day period, fixing the campaign structure down to the script level and automating what had been manual, hourly work produced a measurable shift across every core metric, not just the headline numbers.

Ad revenue grew to a 54.19% increase. ACoS dropped to a 45.41% reduction reflecting genuine efficiency gains rather than just reduced spend.

Conversion rate climbed from 11.34% to 20.51%, an 80% improvement, while CTR moved from 0.8% to 1.13%, up 42%. Impressions fell from 3.37M to 1.95M, which reflects low-intent impression share being deliberately removed, not lost reach on traffic that converts.

TACoS, total sales, and organic rank were not tracked or reported for this engagement and are not included here, rather than being estimated.

SellerApp's AI-powered bidding system played a key role in optimizing our Amazon Japan PPC performance, helping us achieve an ROAS of over 500% and significantly improving advertising efficiency.— Jaida (장예진), I'M MEME

Key Takeaway

I'M MEME's team was doing their best in the work, close to 70% of their week, by their own account. The threshold they hit was a campaign structure that let keywords compete against each other, across products and across Japanese scripts, with no visibility into which search terms were actually converting.

Fixing that wasn't about working harder on the same structure. It meant rebuilding it: ad group-level negatives, script-level segmentation built for how Japanese shoppers actually shop and search, proactive negation of high-risk terms before they could bleed spend, and automation running daily where a person used to check in weekly.

For any enterprise brand running a full ad stack in a market this competitive, the pattern holds: when ACoS plateaus despite constant manual attention, more hours won't fix it.

The structure underneath needs to be rebuilt, and in markets like Japan, that structure has to account for how the market itself behaves, not just how the ad platform works.

If this sounds even slightly familiar, let's look at your account structure together. Book a demo with SellerApp.