Product Consultancy & Integrations | Unicommerce

Scaling the D2C Integration Standard.

As a Product Consultant, I owned the critical infrastructure connecting Unicommerce to global platforms like Shopify and Magento. Below is the proof of how I scaled traffic and reduced operational friction.

25%

Total Traffic Share

67%

Ticket Reduction

338+

Brands Onboarded

Integration Strategy

D2C Optimization (Shopify & Magento)

What I noticed

The D2C revolution was moving faster than our integrations. I identified through research that while brands were shifting to Shopify and BigCommerce, our traffic from these channels was lower than the market potential. The "Alarm Metric" was the **Onboarding Drop-off Rate** for D2C brands—technical friction in the initial API handshake was causing potential clients to churn before even processing their first order.

Traffic Share: Sub-optimal Manual Config: High

The path I chose

I chose to rebuild the D2C integration logic as a "Plug-and-Play" architecture. I optimized the API workflows for Shopify, Magento 2, and BigCommerce to handle real-time sync instead of batch processing. I developed a robust architecture integrating Shopify with physical POS systems, ensuring that inventory across 338 brands remained synchronized with zero human intervention.

Focus: API Handshake Optimization Scale: 338+ D2C Brands

The human outcome

The results transformed Unicommerce into a D2C-first platform. Our optimized integrations began driving **25% of total platform traffic**. By removing technical friction, we didn't just add brands; we stabilized their inventory flow, which is evidenced by the massive adoption of the Shopify+POS workflow I built.

Traffic Lift: +25% Adoption: 338 Brands

D2C Traffic contribution

Platform Traffic Split (Post-Optimization)

Enterprise Ops

Fulfilled by Flipkart Integration

What I noticed

High-volume enterprise sellers were struggling to manage hybrid fulfillment models. I noticed that during Flipkart sale events, the **Processing Latency** was spiking, leading to order cancellations and seller penalties. The "Alarm Metric" was our **Peak-Day Throughput**—we were manually intervening in sale order processing because the legacy workflow couldn't scale with the velocity of Flipkart's "Big Billion Days."

Bottleneck: Sale-Day Spikes Manual Intervention: High

The path I chose

I executed the end-to-end integration of "Fulfilled by Flipkart" (FbF). I worked with engineering teams to redesign the functional workflow to handle automated manifest generation and slab-based labeling. We moved from a sequential processing model to a parallelized API architecture to ensure we could hit the 5,000 orders/day threshold required by enterprise clients.

Action: Redesigned Manifest Logic Metric: 5,000+ Orders/Day

The human outcome

The integration successfully enhanced daily processing to over 5,000 sale orders per client. More importantly, we eliminated the penalty risk for sellers during major events. The success of this 0-to-1 project was the primary driver for my promotion from Analyst to Product Consultant within just one year.

Capacity: 5,000+ Orders/Day Promotion: High Performance

Throughput Scaling (Daily Orders)

Processing Capacity

5k+

Penalty Mitigation

100%

Product Stability

Integration Maintenance & Returns Redo

What I noticed

Cart integrations were our primary support burden. I analyzed ticket logs and found that "Sync Errors" were generating 30 tickets per brand monthly. The "Alarm Metric" was the **Support-to-Order Ratio**—we were spending more on supporting the integration than the margin it generated. Furthermore, the **Return Management workflow** was broken, with 60% of returns needing manual reconciliation.

Tickets: 30/Brand/mo Return Friction: 60%

The path I chose

I chose to harden the API layer rather than hire more support agents. I developed a robust API architecture that included automated self-healing for common sync errors. For returns, I revamped the entire functional workflow, automating the status updates between the marketplace and the Unicommerce panel. This was about building a "Silent Integration" that didn't need constant attention.

Action: API Self-Healing Focus: Return Automation

The human outcome

The outcome was a dramatic stabilization of the product. Monthly support tickets dropped by **67%** (from 30 to 10 per brand). Return management improved by **60%**, meaning brands could process refunds and restock items significantly faster. We turned a high-maintenance integration into a high-trust product asset.

Ticket Drop: -67% Return Lift: +60% Efficiency: High-Trust Sync

Support Friction Reduction

TICKET REDUCTION

-67%

RETURNS IMPROVEMENT

+60%