Motodrift had 500+ SKUs, a growing warehouse, and a team drowning in manual catalog management. We automated the operations, rebuilt their Google Shopping, and gave them time back to focus on growth.
Motodrift sells serious riding gear — helmets, jackets, gloves, boots, body armour. Their catalogue is wide and technically complex: multiple brands, each with size variants, model-specific compatibility notes, and frequent inventory changes. As the business grew, the operations didn't scale with it. Two team members were spending most of their week doing manual data entry between their ERP, a spreadsheet, and Shopify.
Every product update — price change, inventory adjustment, new variant — was manually entered into Shopify. A single brand price update could take half a day. Human error rate was causing live pricing mistakes.
Product feed to Google was only updating once a week via a manual export. Out-of-stock items were still showing in Shopping ads. Inventory errors were costing real money in wasted click spend.
Riding gear sizing is complex and brand-specific. Without any guided sizing tool, customers were guessing. Return rate on jackets and helmets was 18% — almost entirely size-related.
Order processing was manual — staff would check the order, check stock in the warehouse system, then raise a pick. Average time from order to dispatch was 3 days. For gear ordered before a ride, this was brand-damaging.
6 workstreams, delivered by one team.
Built a custom automation that reads directly from their ERP export format, validates against Shopify's product schema, and pushes updates automatically. What took 2 hours of manual work now runs in 8 minutes, unattended.
Deployed a webhook-based inventory sync between their warehouse management system and Shopify. When a product is picked in the warehouse, Shopify inventory updates within minutes. No more overselling.
Rebuilt the Google product feed with real-time stock status, correct category taxonomy, and enriched attributes (brand, size, material). Launched structured Shopping and PMax campaigns with proper negative keyword architecture.
Built a Shopify-native size finder that walks customers through brand-specific sizing questions. Recommends the correct size based on measurements and brand charts. Displayed on all applicable product pages.
Integrated Shopify order notifications with their warehouse system. New orders trigger an automatic pick request. Fulfillment time went from 3 days to same-day for orders placed before 2pm.
Built a product relationship system: gloves recommended with jackets, helmet recommended with visor cleaners. The size quiz also opens cross-sell opportunities. This drove the AOV improvement.
The sequence of work, week by week.
Mapped every manual workflow. Documented ERP structure, Shopify data model, and Google feed gaps.
Bulk upload automation and inventory sync built, tested, and validated against staging store.
New product feed structure. Shopping and PMax campaigns launched with corrected data and campaign architecture.
Size recommendation tool built and deployed on priority product pages. Cross-sell logic implemented.
Operations team now uses those hours for customer service and growth activities, not data entry.
From near-zero structured campaign to consistent 3.1x attributed ROAS within 90 days.
Size quiz cross-sells and product relationship recommendations drove AOV from 3,200 to 4,320.
For orders placed before 2pm. Customer satisfaction scores improved measurably post-implementation.
Carryup, a Shopify-only design and engineering studio based in Bengaluru. Our engagement with Motodrift: Website Design & Development, Maintenance, Ops Optimisation.
motodrift.com runs on Shopify.
Bulk upload automation pipeline; Near-real-time inventory sync; Google Shopping + Performance Max rebuild; Custom size recommendation quiz, and 2 more workstreams. The full scope is broken down in the "What we built" chapter of this case study.
We only publish case studies where we can show real, verifiable metrics tied to Shopify data — but every brand's starting point is different. Motodrift's results reflect what was possible given their specific gaps; your results will depend on where your store, tracking, and funnel currently stand.
We won't promise a specific number without seeing your data first. What we can promise: a diagnostic that tells you honestly whether the same class of fix applies to your store.
Tell us about your brand — we'll tell you honestly what it would take to build it, and where the revenue opportunity is.
