E-commerce & Retail Solutions

Data Engineering & AI Systems for E-commerce & Retail

From fragmented customer data to real-time demand forecasting. We build the cloud infrastructure required to lower CAC, boost LTV, and eliminate stock-outs using advanced AI and modern data stacks.

25%+

LTV Increase

18%

CAC Reduction

99.9%

Data Pipeline Uptime

10 Days

To Project Kickoff

Core Bottlenecks

Solving Core E-commerce Bottlenecks

Fragmented Customer Identity

Unified Customer 360 (CDP)

Consolidating data from all touchpoints into a single customer profile for personalized experiences.

Inventory Inefficiency

AI Demand Forecasting

Predictive models that optimize stock levels, reduce overstock, and eliminate costly stock-outs.

Attribution Blindness

Multi-Touch Attribution Modeling

Advanced attribution models that reveal the true ROI of every marketing channel and touchpoint.

Capabilities

Engineering & AI Capabilities

Personalization Engines

Real-time recommendation systems that deliver hyper-personalized product suggestions, increasing conversion rates and AOV.

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Dynamic Price Optimization

ML-driven pricing algorithms that maximize margins while remaining competitive across channels and market conditions.

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Customer Churn Prediction

Predictive models that identify at-risk customers before they churn, enabling proactive retention campaigns.

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Engineering Output

Custom Analytics & BI Solutions

We design and build custom analytics infrastructure that turns raw transaction logs into executive-level insights.

LTV/CAC Ratio

3.8x

+12.4%

Tracking customer lifetime value against acquisition costs in real-time.

Inventory Health

94%

optimal

Predictive stock levels across all SKUs and warehouses.

Real-time Conversion

4.2%

Live funnel visualization from visit to purchase.

Channel ROAS

5.2x

Multi-channel attribution across paid, organic, and social.

Provisioned via: Snowflake • dbt • Python • Segment

Integration Timeline

How We Integrate

01

Audit & Strategy (Week 1)

Comprehensive evaluation of your data sources, tech stack, and business objectives to define a clear roadmap.

02

Infrastructure Setup (Weeks 2-4)

Deploying data pipelines, warehouse configuration, and integration with Shopify, Magento, or custom platforms.

03

AI Deployment (Weeks 5-8)

Rolling out predictive models for demand forecasting, personalization, and customer churn prediction.

Enterprise-Grade Tech Stack
SHOPIFY PLUS
MAGENTO
SNOWFLAKE
SEGMENT
DBT
AWS

Who it is for

For e-commerce, retail and direct-to-consumer brands whose customer, order and inventory data sit in separate systems.

A good fit

  • Orders live in Shopify Plus, Magento or a custom platform, while stock and marketing data live elsewhere.
  • The same customer shows up as several records across channels.
  • Overstock and stock-outs keep recurring because there is no reliable demand forecast.
  • Marketing cannot see which channels actually pay back.

Not a fit if

  • You need engineers inside your own team. Staff Augmentation covers that.
  • Your first job is moving a legacy database to the cloud. Data Platform Migration covers that.
  • You need a new storefront or a marketing agency, not a data layer.
ROI & Impact

Expected ROI Within the First Quarter

3.5x

Improvement in ROAS

Optimized ad spend through precise attribution modeling.

40%

Reduction in Manual Reporting

Automated pipelines and self-service dashboards.

Zero

Data Latency

Real-time streaming architecture for instant insights.

FAQ

Frequently Asked Questions

Get in touch

Start with one problem worth solving

Tell us the outcome you need and the systems involved. We reply within one business day and tell you whether there is a useful first step, or why there is not. No pitch either way.

Email us directly

sales@3alica.com