Hire Data Analyst for E-Commerce Stores
Senior, direct, no layers

An online store lives or dies on the gap between traffic and profitable orders, and that gap is usually measured badly. Visitor counts flatter a channel that sends browsers, order counts flatter a store that discounts heavily, and revenue flatters a range that is returned at a high rate. A store can grow its traffic, its orders and its revenue at the same time while its margin shrinks, and its standard reports will celebrate all three.

The analyst work therefore joins the order from first session to final refund. Traffic, orders, discounts, returns and fulfilment costs are matched on an order identifier, so a channel can be judged on the profit its orders keep, a product can be judged after its returns, and a discount can be judged on the margin it leaves behind. A first product that never leads to a second order is visible as a repeat problem, not as a traffic problem. Book a free discovery call to check whether your store, analytics and fulfilment records can be joined on a single order before scoping the work.

Stores typically run a store platform for orders, an analytics tool for traffic, a fulfilment or shipping tool for delivery, and a payments tool for refunds. The engagement reads exports from those sources, and the order identifier is agreed before any channel figure is produced, because a session, an order and a refund are only the same sale if the store can say how they are linked.

Discount and return records need the same care as the order itself: a return recorded in one system and a refund recorded in another must be matched to the original order, or the product will appear both sold and returned in different periods. The report states the period rule used for returns, so product figures compare fairly across months.

A store that completes this work should be able to say, for each channel, how many sessions became profitable orders, for each product, how often it is returned and why, and for each discount level, how much of the store's revenue genuinely depends on price cuts. Buying and marketing decisions can then be made on margin kept, not on traffic or order counts.

The work cannot create demand or fix a product that is returned for quality reasons. It can show which channels, products and discount habits lose money, and which first products lead to a second order, so spend and buying effort go to the traffic and range that repay them.