
From the online store to the mobile shopping app.
+300
Projects delivered
15+
Years of experience
100%
Senior team
Barcelona is Spain's digital retail hub. Fashion, lifestyle and consumer goods brands have made Barcelona their technology base for building eCommerce platforms and mobile shopping apps. The ecosystem ranges from D2C startups building their first store to corporations migrating from legacy platforms — Magento, PrestaShop, Salesforce Commerce Cloud — towards more agile architectures and proprietary mobile apps.
Dribba builds eCommerce platforms and shopping apps for companies in Barcelona: mobile store apps with Flutter for iOS and Android, commerce backends with catalogue and order management, ERP and WMS integrations, and personalised shopping experiences with AI. eCommerce built correctly from the start — with the right architecture — scales without friction when demand spikes arrive.
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Frequently asked questions
When retention and CLV (Customer Lifetime Value) are key business metrics. A proprietary app enables push notifications, personalised experiences, offline access and frictionless payments that mobile web cannot match. The decision depends on the proportion of repeat customers: for eCommerce with high repeat purchase volume, the app typically offers the best ROI. For first-time purchases, mobile web is sufficient.
Yes. Integration with ERP systems (SAP, Odoo, Microsoft Dynamics) and WMS (Manhattan, Blue Yonder, Mecalux) is a standard component in the eCommerce projects we develop. Integration can be done via REST API, EDI or system-specific connectors. Complexity varies: from modern API integrations (2–4 weeks) to legacy system adaptations (2–3 months).
Three key factors: (1) load speed — conversion rate drops 7% for each additional second of load time; (2) checkout flow smoothness — checkout should have the minimum possible steps, with Apple Pay and Google Pay integrated; (3) real-time personalisation — AI recommendation engines that increase AOV. Dribba measures and optimises these metrics in every project.
AI semantic search understands the user's intent rather than doing exact keyword matching. It allows searching for 'summer wedding dress' and finding relevant results even if the catalogue uses different terms. Implemented with embedding models (OpenAI, Cohere) + vector databases (Pinecone, pgvector). Increases search conversion rates by 15–40% depending on the vertical.
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