A marketing agency is engaged to bring people to the store and generally does not build or maintain it. This guide compares four partner types, the responsibilities each accepts, and how to add store-side ownership without replacing the marketing relationship.
Outsourcing decisions usually go wrong when they are taken function by function. Splitting each function into the judgment it carries and the execution it generates gives a clearer answer, and a more durable arrangement.
Budget for four ecommerce specialists rarely arrives at once, so the real decision is which capability comes first and who covers the rest. A comparison of four internal hires, one external team and the hybrid arrangement, with the utilisation, continuity and ownership factors that decide it.
Repeat purchase rate rarely moves because of a missing tactic. It moves when the measurement is honest, the reorder path is short, and the timing matches the category’s own buying cycle.
GA4 and your order table will never agree exactly. A reliable ecommerce analytics setup is one whose variance against the backend is small, explained and stable, and this guide covers how to build and validate that.
Fast stores convert better, but that is a correlation, not a promise that this store will earn more by loading faster. This guide separates the evidence from the sales pitch, shows which thresholds and data sources actually describe shoppers, and sets out which speed fixes repay the work and which rarely do.
Personalization pays where a store produces enough behavioural data and presents enough choice for it to matter. This guide sets out which types repay the cost at realistic volumes, which are usually overkill, and how to test the difference before committing budget.
Most tactics that raise average order value also put conversion or margin at risk. This guide sets out which levers fit which catalogue, and how to judge them on gross margin per session rather than on basket size.
A conversion-friction audit maps exactly where shoppers stall before you add AI, then ranks each stall by lost revenue so you know what to fix first. This guide breaks it into four friction zones, a cost formula, and clear thresholds for when automation actually pays off.
Usability findings lose every argument against a feature request unless they carry a number. How to scope an ecommerce UX audit, which four kinds of evidence to combine, how to size a finding in margin rather than severity, and which findings should be fixed rather than tested.