E-Commerce Insights — Poland

E-commerce market research focuses on online retail — e-shops, marketplaces, sales platforms, and the supporting services ecosystem (logistics, payments, digital marketing). It analyzes online buyer behavior across the complete purchase journey: from inspiration and search, through offer comparison and selection, to transaction completion, delivery, and post-purchase support.

Poland’s e-commerce market is growing dynamically — its value has exceeded 100 billion PLN, and online shopping penetration among internet users surpasses 75%. Allegro remains the dominant player, but Amazon.pl, vertical platforms (e.g., Zalando in fashion), and brand-owned direct-to-consumer (D2C) stores are gaining ground. Key trends include: quick commerce expansion (delivery in minutes), social commerce (shopping via TikTok, Instagram), AI-driven personalization, and growing consumer expectations around sustainable logistics.

Common e-commerce research projects include: online store and mobile app usability (UX) testing, cart abandonment cause analysis, conversion factor studies, customer satisfaction and loyalty measurement (NPS, CSAT), competitive benchmarking (how do we compare against competitors?), pricing research (online vs. offline price sensitivity), and customer journey mapping — documenting the full path from ad exposure to repeat purchase.

Methodologically, e-commerce research benefits from respondents’ natural online activity, making recruitment straightforward. The most commonly used methods are: CAWI on consumer panels (fast, affordable, with visual stimulus presentation capability), UX testing (moderated and unmoderated — respondents complete tasks on the site while researchers observe pain points), eye-tracking (gaze analysis on product pages), qualitative interviews (exploring purchase motivations), and behavioral data analysis (heatmaps, session recordings).

A key challenge in e-commerce research is the gap between declarations and behavior — buyers claim price is most important, but behavioral data often reveals that other factors drive decisions (seller trust, delivery speed, return policy). That’s why the most effective projects combine declarative data (surveys) with behavioral data (analytics, UX testing).