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In which branch do customers wait the longest?

We measure hourly visitor curves, wait time, and counter coverage — and show service gaps across branches on one screen.

In branch networks, experience is shaped less by the transaction itself than by the wait before it. Customers join a queue, the transaction runs long, and open counters do not match the hour’s density. Headquarters often cannot see which branches are truly busy and which carry surplus staff. Loyaltfy uses existing cameras to measure hourly curves, wait time, walkaways, and counter coverage anonymously — and makes branches comparable on one scale.

Saatlik
Ziyaretçi eğrisi
Dakika
Bekleme süresi
Kişi sayısı
Sıradan ayrılan
Yoğunluk / açık gişe
Gişe kapsama
Which business type are you?

Problems we hear most often in this industry

Müşterinin sırada ne kadar beklediğini kimse dakika olarak bilmiyor.

Açık gişe ve danışman sayısı, o saatteki gerçek yoğunlukla uyuşmuyor.

Sıraya girip işlem yapmadan çıkan müşteri hiçbir rapora yansımıyor.

Hangi şubenin gerçekten yoğun, hangisinin personel fazlası taşıdığı merkezden görünmüyor.

How we solve them

True wait time

Measure time from joining the queue to reaching service — including the worst cases, not only the average.

Hourly density curve

See how many people arrive by hour; align shifts and lunch breaks to that curve.

Counter coverage

Measure how many counters are open as density rises; see the gap between demand and capacity.

Cross-branch comparison

Put every branch on the same indicators; find where service standards diverge.

Use cases
Set open-counter counts from the real morning and lunch peaks
Report weekly walkaways who leave without a transaction
Alert branch managers when wait-time thresholds are crossed
Compare wait time and volume across regional peers
Find overstaffed branches and move capacity to busy ones
Run before/after measurement after layout or ticket-system changes

FAQ for Service & Branch Networks

If your answer is not here, ask us — we reply the same day.

Send your question

No. In banks and service points this is the most common question, and the answer is clear: no facial recognition, no identity matching, no person-level records. The system sees that someone joined a queue and how long they waited — not who they are. Only numerical results reach us, not video.

From entering the waiting area until reaching the service point. Alongside the average we report longest wait and the share above threshold — because branch experience is often shaped by extremes, not the mean. If ticket-system data exists, both can be read together.

Prefer size-independent metrics: average wait, threshold-breach rate, walkaway percentage, and peak-hour counter coverage. Those let a small dealer and a large flagship compare fairly. Branches can also be grouped by region and ranked within group.

Other industries

Let’s talk about what we can measure for Service & Branch Networks

We’ll review your camera setup and propose modules and a rollout plan for this industry.