Results
Results that show up on the income statement, not the slide deck.
Magecore documents client results in TCO reduction, conversion, LTV, and operational savings. The cases below are representative and anonymized, with sector, timeline, and intervention type indicated in each metric.
Every project is measured by the CFO's criterion: documented financial return.
Case 01 · Retail (Mid-Size)
M1 to Adobe Commerce Cloud migration
Operation with significant revenue still on Magento 1.
Previous migration attempts failed; internal team demoralized and board applying pressure.
Magecore diagnostic (AI-assisted, 2 weeks)
- 38% of IT budget on reactive M1 maintenance
- 14 obsolete extensions impacting performance
- Slow checkout inflating CAC
- R$ 1.8M/year in invisible costs mapped
-41%
Infrastructure TCO over 12 months (mid-size retail, post M1→Adobe Commerce Cloud migration)
-1.8s
Checkout time after optimization (same case, 6 months post go-live)
+22%
Conversion rate over 12 months (mid-size retail, after Strangler migration)
R$2.1M
Documented annual savings (mid-size retail, 12 months post-intervention)
Case 02 · B2B SaaS (Enterprise)
Re-engineering highly customized Adobe Commerce
B2B scale-up with growing churn due to instability.
67% of tickets originating from 3 modules. Board pressure for efficiency.
Magecore diagnostic (AI-assisted, 10 days)
- Monolithic architecture with 47 undocumented customizations
- 3 critical modules = 67% of incidents
- LTV down 18% over two quarters
- Failure pattern detected by AI
-62%
Support tickets over 9 months (enterprise B2B SaaS, after re-engineering 3 critical modules)
+31%
LTV over 12 months (enterprise B2B SaaS, post platform stabilization)
-28%
Churn over 12 months (enterprise B2B SaaS, after incident reduction)
2.3x
Valuation over 18 months (enterprise B2B SaaS, post architecture intervention)
Case 03 · Fashion (Mid-Size)
Precision Assessment — when not migrating was the right call
Adobe Commerce / Magento 2 with conflicting diagnostics from three agencies.
CEO without data to decide.
Magecore diagnostic (AI-assisted, 8 days)
- Platform was not the bottleneck — integrations and infra were
- Third-party APIs with cascading latency
- Undersized infrastructure during seasonal peaks
- R$ 680K/year savings possible without platform change
R$1.2M
First-year savings (mid-size fashion, after optimization without platform migration)
R$800K+
Migration cost avoided (mid-size fashion, decision based on 8-day assessment)
-58%
Load time over 3 months (mid-size fashion, after integration and infra tuning)
8 days
Assessment duration (mid-size fashion, AI-assisted diagnostic)
Anonymized and rounded data. Details under NDA.