Beauty and Personal Care
India
How Minimalist Used AMC Insights to Improve DSP Performance
21%
Growth in ad-attributed sales
+30%
New-to-Brand share
35%
Lower ACOS on DSP than Sponsored Ads
15.6%
Reduction in TACOS
Minimalist had reached a point where increasing Sponsored Ads investment was becoming less efficient. Attempts to scale beyond the existing level resulted in higher ACOS, while Amazon Marketing Cloud data also showed that only 33% of attributed sales were coming from repeat customers.
Using Adbrew, the team was able to bring together AMC reporting, audience analysis, Sponsored Ads performance, and DSP execution in one workflow.
This made it easier to review customer behavior, identify useful audience segments, and act on those findings without treating each part separately.
What AMC showed
Through AMC reports available in Adbrew, the team identified a clear difference between branded and generic search behavior.
The New-to-Brand report showed that branded searches such as “minimalist” had a lower New-to-Brand share, while broader category searches such as “salicylic acid” brought in a higher share of new customers. This helped distinguish terms that were more useful for retention from those that were better suited for new customer acquisition.
The Path to Purchase report showed that the Sponsored Brands → Sponsored Products sequence had the lowest ACOS among the paths analyzed. This influenced how budget was distributed across Sponsored Ads formats.
The team also used the ASIN Overlap report to understand what customers tended to buy after purchasing another Minimalist product. These relationships helped identify cross-sell and follow-up purchase opportunities.
Adbrew made these reports easier to review regularly, so the team could move from analysis to campaign decisions without relying on one-off reporting.
How those insights were used in DSP
The team used AMC insights to define the audiences that would be activated through DSP.
Conversion campaigns focused on audiences such as product detail page viewers and cart abandoners.
Consideration campaigns used Amazon in-market audiences, competitor audiences, and lookalikes of high-value repeat customers.
AMC audiences were also created around shopper behavior, including product page engagement and cart activity, and then used in conversion-focused DSP campaigns.
Within Adbrew, the team could review the AMC findings, create or work with relevant audiences, and connect those insights more directly to DSP campaign planning.
What changed after launch
The first two weeks of DSP showed that the campaigns were reaching only 70% of the planned daily impression goal.
The team found that relevant Amazon in-market audiences had not been activated. After adding those audiences and relaunching the campaigns:
Conversion campaign ROAS increased from 3.61 to 5.42
Detail Page View Rate increased from 0.1283% to 0.1667%
The team also reviewed inventory sources, excluded underperforming placements, tested creatives, adjusted bids and CPM limits, and monitored audience overlap to reduce inefficient delivery.
Adbrew helped make this process more practical by giving the team a place to monitor performance, review reports, and act on the changes identified during optimization.
Results
The combined AMC and DSP work led to measurable improvements across acquisition, retention, and advertising efficiency.
DSP ACOS was 35% lower than Sponsored Ads ACOS
Repeat purchase share increased from 33% to 37%
Overlapping ASIN pairs increased from 616 to 736
New-to-Brand share on the “minimalist” search term increased from 39.81% to 59.86%
Conversion campaign ROAS increased by more than 50% after audience changes
The takeaway
AMC helped the team understand which search terms were bringing in new customers, which ad sequences were more efficient, which products customers tended to buy together, and which shopper groups were worth activating through DSP.
Adbrew made that workflow easier to manage. The team could review AMC reports, find useful audience and performance insights, activate audiences, and monitor campaign performance from the same platform.
That reduced the gap between finding an insight and actually using it in campaign execution.
