01
An item sold after it ran out because stock reached the storefront a few minutes late.
We decide which system owns stock, move updates to events instead of periodic exports, and make the storefront reserve at the moment of purchase.
Industries
Catalogue, checkout and the truth about attribution
Selling online puts three fragile things next to each other: product data that lives in several systems, a checkout that must not fail, and a measurement story that has to survive consent.
Trace one order end to end
30 minutes with an engineer, no sales call
What is different here
Peak day exposes every assumption
Catalogue and inventory rarely have one owner. Stock sits in a warehouse system, prices in a spreadsheet or an ERP, content in the storefront, and each of them believes it is right. Sync is where the truth is decided, and the failure shows up as an oversold item or a product nobody can find. Checkout sits at the end of that chain, where a slow third party call becomes an abandoned order rather than a log line.
Then there is load and the aftermath. Traffic in this sector arrives in spikes tied to campaigns and seasons, so capacity has to be tested before the day rather than discovered on it. Returns and disputes are part of normal operation and need their own workflow. And with consent aware tracking, part of the demand data is simply missing, so attribution has to be modelled honestly instead of reported as if every path were visible.
Common technical situations
Situations that shape the work when you sell online
02
Checkout fails intermittently and the errors point at a third party you do not control.
We trace the full order path, add timeouts, retries and a safe fallback, and make the failure visible before customers report it.
03
Your ad platforms each claim the same orders, and the total is larger than your revenue.
We define one server side source of order truth, then compare platform claims against it so budget decisions use one number.
04
Last season's traffic peak degraded the site and nobody knows which part gave way first.
We load test the real journey ahead of the next peak, then fix the narrowest constraint and re test rather than adding capacity everywhere.
How our lines apply
The three lines across catalogue, checkout and demand
The same team owns the integration, the platform under it and the measurement on top, so attribution arguments end with data rather than opinion.
Software development
Catalogue and inventory sync, order and returns workflow, checkout reliability with fallbacks, and the admin surface operations needs during a busy week.
IT services
Capacity work before the peak, caching and delivery, monitoring on checkout and stock freshness, and an incident path for the days that matter most.
Digital marketing
Consent aware measurement, server side order truth, search and answer engine visibility for category and product intent, and paid judged on contribution rather than platform claims.
What we would need from you
What a project here requires from your side
Access
Read access to the storefront platform and its admin
Credentials for the inventory or ERP system in scope
Read access to analytics, tag manager and ad accounts
A staging store with a representative catalogue
Data and context
How stock, price and product content are updated today, and by whom
Order, return and dispute volumes across a normal week and a peak week
Your consent banner behaviour and what it currently blocks
The campaign calendar for the next peak
Decisions
A named owner for the system that holds stock truth
A decision on what checkout does when a third party is down
Agreement on which single number budget decisions will use
We do not need customer personal data to do this work. Where a sample is unavoidable we ask for it anonymised and agree the handling in writing.
Questions
Questions retail and marketplace teams ask us
Next step
Pick the sync or the checkout you least trust
Book a technical assessment
30 minutes with an engineer, no sales call