Al-Amania Cleaning & Pest Control
Al-Amania
Bilingual booking platform for a Riyadh commercial cleaning + pest control business. Prayer-time-aware scheduling, WhatsApp-first confirmations, and a dispatcher dashboard that routes crews across Riyadh in real time. Dispatch-call volume down ~60%.
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Results
Booking conversion
Scheduling clashes
Dispatch-call volume
The Challenge
Al-Amania services offices, warehouses, compound villas, and retail across Riyadh — a city where the working rhythm is shaped by five daily prayer breaks, summer heat windows that restrict outdoor work, and a Fri–Sat weekend instead of Sat–Sun. Generic booking software (Calendly, Zoho) didn't map to any of this. Staff coordinated across two WhatsApp groups and a paper wall-planner to avoid clashes.
Arabic wasn't a nice-to-have — roughly 70% of the customer base would only book through an Arabic UI. But the site also had to be equally strong in English for corporate property managers (largely expats) who preferred English for contracts. Machine translation wasn't acceptable — the language needs to feel like the business, not like a plugin.
Field ops had no live visibility: supervisors didn't know which crew was at which site at any given moment. If a team finished a deep-clean early, there was no fast way to shift them to the next job. Customers were calling the dispatcher just to ask where their team was.
Our Solution
Built a genuinely bilingual booking flow — full-RTL Arabic alongside English, sharing one codebase via next-intl. Both flows are first-class: fonts, iconography, and date formatting swap on locale, and service descriptions/testimonials are hand-written in each language rather than auto-translated.
The scheduling engine is aware of the full Riyadh context: the five daily prayer windows auto-pull per date, outdoor pest-control appointments are offered morning slots during summer months, and Fri–Sat is the default weekend. Slots the customer picks are confirmed over WhatsApp within two minutes — no forms-only email chain.
Dispatcher dashboard shows a live map of Riyadh with each crew's current job, drive-time to the next site, and completion status pinged from the team's phone. A deep-clean finishing 40 minutes early auto-flags the nearest pending job as a swap candidate.