Retail

Turn browsers into buyers.
Every visit.

Click-and-collect flow, returns desk management, peak demand predictions, and staff scheduling — so every customer interaction converts.

28% higher conversion rate
28% Higher conversion
41% Reduced abandonment
14 days Avg. deployment
The problem

Where queues become lost sales.

Click-and-collect creates congestion

Online shoppers arriving for pickups collide with in-store browsers at the service counter. Fulfilment desks back up; in-store sales staff are pulled away.

Returns queues damage loyalty

A long returns queue is the last thing a customer sees. Studies show customers who abandon a returns queue are 3× less likely to repurchase.

Peak demand catches stores flat-footed

Lunch rushes, weekend spikes, and sale events overwhelm static staffing rotas. Managers react — they never anticipate.

How it works

Three steps to a converting store.

01

Customer joins the right queue

Click-and-collect, returns, and service desk queues run in parallel. Each has its own capacity rules and priority weighting. No cross-contamination.

02

Predictions surface before peaks hit

BoringQMS models historical footfall and queuing data to forecast demand 30–60 minutes ahead. Managers receive staffing prompts before the rush, not during.

03

Staff scheduling closes the loop

Shift rotas sync with predicted demand curves. Gaps are flagged the day before. On the day, live queue depth adjusts desk assignments automatically.

Features

Built for the pace of retail.

📦

Click-and-collect queuing

Dedicated fulfilment queue keeps online customers separated from browsing shoppers. Staff see order reference at call-up — no scrambling in the stockroom.

↩️

Returns desk flow

Returns queue runs its own priority rules. High-volume return days get automatic capacity boosts. Customers join via QR code before they reach the door.

📉

Peak demand predictions

Machine-learning model trained on your store's own footfall history. Accuracy improves week over week. Alerts land in Slack or via SMS before queues form.

🗓

Staff scheduling integration

Push demand forecasts to your existing rota tool (Deputy, Planday, or custom CSV). On-shift staffing recommendations update in real time as queue depth changes.

"We lifted conversion 28% in Q4 — our best peak trading season in five years. The demand predictions meant we were staffed correctly every single day."

Store Operations Director, National Retail Chain

Lift conversion 28%.

We map your store's current flow, model conversion impact for your footfall volumes, and deliver a pilot plan — free of charge.