Omnichannel Complexity
Problem: Store, warehouse, and e-commerce inventory often disagree, yet customers expect buy-online ship-from-store.
Why it matters: Stock-outs lose sales, and overselling damages trust.
32 projects, 2B+ transactions processed
Retail & E-Commerce
Retailers compete on speed, personalization, and omnichannel experience. We have architected 32+ D2C, B2B2C, and marketplace platforms processing $2B+ in annual transactions.
- Timeline
- 10-16 months
- Budget
- $500K-$1.2M
- Team
- 6-10 engineers + 1 product consultant
The Challenge
Why this industry matters now.
Conversion Rate Optimization
Problem: Checkout abandonment averages around 70%, and many teams lack A/B testing and analytics infrastructure.
Why it matters: Every 1% conversion improvement creates direct revenue leverage.
Personalization & Recommendation
Problem: Most retailers show the same products to everyone while leading platforms personalize discovery.
Why it matters: Personalization can lift AOV by 15-25% and conversion by 5-10%.
Supply Chain & Fulfillment
Problem: 2-day delivery requires forecasting, inventory optimization, and smart order routing.
Why it matters: Shipping is a major cost center, and routing optimization saves 10-15%.
Fraud & Payments
Problem: E-commerce fraud losses can run 0.5-1.5% of revenue, and aggressive controls hurt legitimate conversions.
Why it matters: Fraud detection must be accurate and nearly invisible to buyers.
How We Solve It
Methodology that turns sector knowledge into execution.
01
Unified Commerce Platform
One source of truth for inventory, pricing, orders, and customer data across web, mobile, stores, and marketplaces.
02
Headless Commerce & API-First
Catalog, checkout, order, and inventory APIs allow faster web, mobile, kiosk, and partner-channel launches.
03
Personalization & ML Recommendations
Recommendations, triggered email, semantic search, and personalized discovery improve AOV and repeat buying.
04
Demand Forecasting & Fraud Controls
Forecasts optimize inventory and fulfillment while ML fraud scoring protects revenue without slowing checkout.
Compliance
Regulatory Framework
NexaCore keeps payment data tokenized through Stripe or Adyen, implements GDPR consent, CCPA opt-out flows, accessible interfaces, and encrypted customer data.
| Regulation | Scope | Impact |
|---|---|---|
| PCI-DSS | Payment card data | Encryption, tokenization, secure transmission, audit logs |
| GDPR | EU customer data | Consent, minimization, DPA, access and deletion rights |
| CCPA | California resident data | Opt-out, disclosure, sale limitation |
| COPPA | Under-13 data | Parental consent and limited tracking |
| ADA | Web accessibility | WCAG 2.1 AA interactions and content |
Technology Recommendations
Platforms we recommend because they survive the run state.
Commerce
Shopify for SMB, custom headless React + Node + Postgres, Spryker, or SAP Commerce
Order Management
SAP Order Management Cloud, custom OMS, ShipBob, Flexport integrations
Personalization
TensorFlow, Databricks, Dynamic Yield, Segment
Payments
Stripe, Adyen, PayU, Apple Pay, Google Pay
Search
Elasticsearch, Algolia, or embedding-based semantic search
Detailed Case Study
D2C Fashion Brand (Anonymized)
"The conversion lift alone is $1.2M annual incremental revenue, and our launch speed became a competitive advantage."
Situation
- $12M revenue fashion brand growing 40% YoY but constrained by Magento complexity.
- Checkout conversion was 1.8%, inventory was spreadsheet-driven, and mobile underperformed desktop.
- Chargebacks ran at 0.9%, costing roughly $100K annually.
Challenge
Rebuild on headless architecture, unify inventory, add personalization and fraud controls, and reach 3.5% checkout conversion in 10 months.
Our Solution
- Months 1-3: headless platform design, API architecture, and migration planning.
- Months 4-7: Next.js frontend, Node.js APIs, PostgreSQL commerce core, and Stripe payments.
- Months 8-10: personalization, fraud detection, inventory sync, beta launch, and public cutover.
Results
- Checkout conversion improved from 1.8% to 3.7%, adding $1.2M annual revenue.
- Chargeback rate dropped from 0.9% to 0.15%.
- Cart abandonment fell from 72% to 58%.
- New collection launch time moved from 2 weeks to 3 days.
Technology Stack
Next.jsNode.jsPostgreSQLGraphQLStripeTensorFlowKlaviyoSegment
ROI Framework
Typical Engagement
- Checkout conversion improvement of 50-100%
- AOV lift of 15-25%
- Cart abandonment down 10-20%
- Fraud loss reduction of 60-75%
Discuss Your Retail Roadmap
We'll map the first 90 days, identify the riskiest integration points, and give you a realistic budget and timeline.