E-commerce Analytics

Once tracking is reliable, analysis focuses on the questions that drive growth. Funnel analysis shows where shoppers leave: a high drop-off between product views and add to cart may point to pricing, product information, images or trust issues, while drop-off during checkout often reveals friction such as forced account creation, unexpected shipping charges, limited payment options or slow pages. Product analysis identifies best sellers, products with many views but few purchases, products often bought together, and items with high return or cancellation rates when that data is available. Channel analysis compares how organic search, Google Ads, Meta Ads, email, WhatsApp, marketplaces and referrals contribute to revenue, not just traffic, helping you judge which marketing investments are worthwhile. Because each advertising platform tends to credit itself for conversions, analytics provides a more neutral, though still imperfect, cross-channel view; we explain attribution models and their limitations honestly. Customer analysis looks at new versus returning buyers, purchase frequency and, where data permits, the value customers generate over time, which informs how much you can sensibly spend to acquire a customer. Device and location analysis reveals whether mobile shoppers convert worse than desktop, which often indicates mobile usability problems, and which cities or states deserve targeted marketing or faster delivery. Seasonal and promotional analysis compares festive sales, discount campaigns and normal periods, showing whether promotions generated incremental sales or simply shifted purchases. Each insight comes with practical recommendations, such as improvements to product pages, checkout steps, campaign budgets or email flows.