Retail systems built for the peak and for the margin.
Commerce platforms, loyalty programmes and omnichannel operations — built for the day traffic is many times normal.
- Audit before opinion
- Fix what pays first
- Build the durable pieces
- Rehearse the worst hour
- Trade, measure, tune
Retail is engineering under pressure.
Retail is engineering under pressure: milliseconds move conversion, stock accuracy is money, and one peak day funds a quarter. We build commerce and loyalty systems designed for the peak — and the operational tooling that keeps stores, warehouses and digital honest with each other. The failure modes are specific to the sector. A checkout that gets slower under load loses revenue in proportion to the traffic you paid to acquire. An inventory number that is right in the warehouse and wrong on the product page turns a good day into a week of refunds and apologies.
Very little of that is solved by a new platform on its own. The value sits in the seams: how orders route between store and warehouse, how a promotion is priced and then settled with the supplier, how a return finds its way back into sellable stock, how the loyalty balance a customer sees at the till matches the one finance is carrying as a liability. We work on those seams, and we size everything for the worst hour of the year rather than the average one.
Peak is not a season for us either — our own loyalty engine is designed for the same trading peaks. What we bring to your estate: rehearsed load, graceful degradation, and one number for stock and one for liability. GDPR / KVKK compliant, on the cloud and region you choose.
What we work on.
Four areas where the engineering has a direct line to margin in retail.
Commerce platforms
Headless storefronts and checkout engineered for Core Web Vitals and conversion — measured, not assumed. Every route carries a performance budget enforced in the pipeline, so a marketing tag or a hero image cannot quietly cost you a tenth of a second on the category page. Built with React and Next.js at the edge, over commerce services that can be replaced one at a time. See web application development.
Loyalty & retention
Points, tiers, offers and personalisation on our Loyalty & Retention engine — the economics tuned to retail margins. Earn rates are set per margin band rather than per basket, offers are targeted by prediction with a holdout so uplift is measured against a control group, and the points liability is a report over the ledger rather than a monthly spreadsheet exercise.
Omnichannel operations
Order management, click-and-collect and returns — one inventory truth across store and web. Availability is calculated from a single stock model with reservations, safety buffers per channel and an audit trail on every adjustment, so an oversell is an exception with a cause rather than a mystery. Store, warehouse and marketplace all read the same number.
Trade & campaign systems
Promotion planning and settlement with Sales Performance — replacing spreadsheet season with governed workflows. Promotions are planned against budget, approved by the people accountable for them, executed as priced rules, and settled with suppliers from the same record — so accruals, claims and deductions all reconcile to one version of what was agreed.
What we build, in detail.
The peak is a design input, not a hope.
Peak trading is the one day where architecture becomes visible to the board. We model the load from your own curves — last year’s minute-by-minute traffic, the campaign shape, the email send that lands at ten past nine — and rehearse against it before the season. Then we break things on purpose: the payment provider times out, the recommendation service goes dark, search falls over. What matters is what degrades and in what order. Checkout is protected above everything else, personalisation and recommendations shed load first, and the caching strategy is decided per route rather than globally.
- Load rehearsals against synthetic peaks built from your real curves, run before the trading season
- Graceful degradation designed in order: checkout, then browse, then personalisation
- Sized for your real peak-to-normal ratio, with the cost of that headroom made explicit
One stock number, and everyone can see where it came from.
Omnichannel pain is usually one problem wearing different hats: several systems each believe they own the stock figure. We put a single availability model in the middle, fed by the warehouse, the stores and the marketplaces, and expose it as one contract everyone reads. Reservations hold stock for the length of a checkout, safety buffers are set per channel rather than argued about per incident, and every adjustment carries a reason and an actor. When a number changes, the question ‘why does the site say two and the store says none’ has an answer on one screen.
- Reservations with expiry, so an abandoned basket returns stock automatically
- Per-channel safety buffers as configuration, tuned by category rather than set once and forgotten
- Every adjustment audited — receipt, sale, return, count, correction — with the source system named
Promotions that settle as cleanly as they launch.
A promotion is easy to launch and expensive to close. The plan lives in one spreadsheet, the price change in the commerce platform, the supplier agreement in an email, and the claim arrives three months later with a number nobody recognises. We put the whole life of the promotion on one record: planned against a budget, approved by the person accountable, executed as priced rules the checkout applies, then accrued and settled with the supplier from the same data. Deductions and claims reconcile to what was agreed, and the margin impact is visible while there is still time to act on it.
- Approval thresholds by value, category and funding source — configuration, not a mail thread
- Accruals raised when the promotion runs, not when the claim lands months later
- Every change carries an actor, a timestamp and the version of the rule that priced the basket
One estate, three sets of expectations.
Conversion is a performance budget.
The commerce work that pays is rarely a redesign. It is the checkout step that takes four seconds on a mid-range Android, the category page that ships three hundred kilobytes of unused script, the search that returns nothing for a plural. We instrument the funnel first, fix in order of measured impact, and hold a budget on the routes that matter — an LCP target agreed with you on commerce landing routes, enforced in CI so a regression fails the build rather than the quarter.
- Field data from real devices, not a lab score on a developer laptop
- Performance budgets enforced in the pipeline on the routes that convert
- Experiments with a holdout, so a change is judged against a control and not against last month
The systems the shop floor actually uses.
Click-and-collect, ship-from-store and returns succeed or fail on the tooling a colleague uses with one hand while carrying a basket. We design for that: few taps, offline tolerance in a stockroom with no signal, and a clear escalation when the data disagrees with the shelf. Order routing balances distance, stock cover and store capacity, so a single shop does not absorb every online order in its region during peak.
- Order routing by distance, cover and capacity — rules the operations team can tune themselves
- Offline-tolerant store tasks that sync and resolve conflicts predictably
- Returns that put sellable stock back into the pool the moment it is scanned
One definition of margin, liability and stock.
Retail finance spends its month reconciling systems that were never designed to agree. We build the governed layer underneath — one definition of net margin, promotion cost, stock value and points liability, with lineage back to the transaction that produced each figure. Reports read from that model rather than from four extracts, and when a number is challenged the answer is a drill-down instead of an investigation. Built by our data engineering practice.
- Governed models with lineage from source system to reported figure
- Points and promotion liability reportable at any moment, not only at close
- Power BI or your existing BI tooling on top — we do not sell you a new stack you did not ask for
The estate a retailer actually runs.
Commerce platform
Headless storefronts over the platform you already run, with the catalogue and checkout services isolated behind contracts
ERP & merchandising
Product, price, cost and supplier master synchronised through governed contracts rather than nightly file drops
POS & store systems
Transaction feeds, returns and store stock movements streamed into the same availability and loyalty models
WMS & 3PL
Stock, receipts, despatch and carrier events, with reconciliation on the numbers that disagree
Marketplaces
Listing, order and settlement flows with per-channel stock buffers and fee-aware margin reporting
Payments & PSPs
Tokenised, PCI-aware payment integration with idempotent capture, refunds and reconciliation to settlement files
CRM & marketing
Segment sync and delivery via email, push and SMS with consent state checked at send time
Data platform & BI
Event and ledger feeds into Snowflake, BigQuery or your lakehouse — see data engineering
What engineering for the retail peak means in practice.
- Peak rehearsals against synthetic Black-Friday load, built from your own minute-by-minute curves and run before the season — with the results and the remaining risks written down rather than described.
- Inventory-consistency engineering across channels. One availability model, reservations with expiry, per-channel buffers and an audited reason on every adjustment. Oversells become exceptions with causes.
- PCI-aware payment integration. Tokenisation, scope kept deliberately small, idempotent capture and refunds, and reconciliation against the settlement file rather than against hope.
- Personalisation with consent — KVKK / GDPR treated as design inputs. Consent state is checked at send and at decision time, and a withdrawal takes effect everywhere it should, including in the models.
- Performance budgets enforced in CI. A regression on a converting route fails the build. Field data from real devices decides, not a score from a developer laptop on office wi-fi.
- Graceful degradation planned in order. Checkout is protected first; personalisation, recommendations and non-essential calls shed load before anything customer-critical does.
- Change frozen only where it has to be. We ship behind flags through trading season, so a fix is a toggle rather than a release, and the freeze covers infrastructure rather than the whole business.
- Margin visible while it can still be changed. Promotion cost, fee-aware marketplace margin and points liability reported continuously, not discovered at close.
From an audit to a rehearsed season.
Audit before opinion
We measure before we recommend: field performance on the converting routes, checkout drop-off, stock accuracy against a count, the integration map and where the numbers already disagree. The output is a ranked list of what costs you money, with the effort against each.
Fix what pays first
Usually a focused rescue rather than a replatform — checkout latency, availability accuracy, a broken returns path. Shipping something measurable first earns the right to talk about the larger programme, and often changes what that programme should be.
Build the durable pieces
The availability model, the loyalty configuration, the promotion workflow, the storefront routes that carry a budget. Delivered in slices behind flags, each one live and measured before the next begins.
Rehearse the worst hour
Synthetic peak from your real curves, every dependency failed on purpose, degradation order confirmed and the runbook exercised with your team. Anything that does not hold is fixed or explicitly accepted, in writing, before the season.
Trade, measure, tune
Through the season we operate to defined SLOs with incident cover to the hours the run contract sets, and afterwards the numbers — conversion, accuracy, redemption, margin — decide what gets built next. See engagement models.
Frequently asked questions
Where else we go deep.
Bring us a problem from your industry.
Describe what is going wrong today. An engineer reads it and replies in writing with a concrete path.