Creating a great checkout experience by keeping the queue to the perfect length
Queue management

A good shopping experience due to an optimal queue length

Queue management

The art of anticipating peak times

The cash desk is one of the last contact points between customer and store personnel. It is thus a major opportunity for shaping the shopping experience in a positive manner for brick-and-mortar retailers. For 49 percent of customers, a long waiting line is a major shopping killer. Therefore, managing the queue length efficiently is a major part of creating a convenient checkout process.

The lack of active, deliberately planned in-store traffic observation and queue management leads to a mismatch – or at least a delay – between the number of cash desks that are open and the number required.

Some customers who notice long queues in front of cash desks terminate their purchase without completion. Filled abandoned baskets and shopping carts within the store might be an indicator of this. As a consequence, the store not only loses direct revenue, but its reputation also suffers.

Having to queue in a long waiting line for payment and checkout reduces customer satisfaction significantly. This increases the danger that consumers’ negative feelings spread out to their perception of the brand as a whole. Ultimately, this could lead to consumers avoiding the brand’s stores altogether.

When store personnel suddenly need to interrupt their current activity to go in front to open up an additional checkout, this is inefficient in terms of intra-day activity planning.

How retailers benefit from queue management:

Perfect staff planning: Having the right amount of staff available on demand is crucial for smooth checkout processes. A database-led recommendation helps store management allocate personnel to suitable activities and time slots.

Gaining control: The store manager and staff know the current and expected consumer traffic at the checkout. Thus, they are in control of the situation instead of being surprised by sudden peaks, which might swell to long queues.

Operational efficiency: Now it is possible to optimally schedule intra-day activities such as re-filling shelves, commissioning, empting the reverse vending machine, setting up promotional displays, and of course opening or closing cash desks. In this way, the staff avoids unnecessary journeys within the store.

Reduction of checkout waiting times: The solution reduces checkout waiting times for customers. The main goal is to optimize store personnel’s intra-day activities so that there is no need for additional staffing. This also means that reducing waiting times prior to national holidays, when all cash desks are already busy, is a bigger challenge.

Fast and discreet communication: If the solution detects room for improvement in terms of waiting times, store personnel discreetly receive a notification on their device of choice. The customer is not distracted by internal announcements via loudspeaker and focuses on their shopping instead of worrying about potential checkout queues.

Pleasant atmosphere: Manageable waiting lines reduce stress for store personnel and customers alike. Relaxed people and a pleasant atmosphere open up the possibility for some nice chitchat, which boosts everyone’s mood.

Use case overview: queue management

  • A straightforward approach is the installation of sensors, infrared cameras, or cameras with people tracking in the checkout area. Alternatively or additionally, the usage data of various IP-enabled devices within a store – such as shopping carts, fridges, or service counters – can be combined in order to predict customer traffic at the checkout area.
  • All devices are connected to one backend via protocols and APIs. It is possible to include devices from different suppliers. They can either be connected directly to the cloud, or indirectly via gateways.
  • The data captured from these devices is processed within one solution. Processing can either be done locally on a gateway (for real-time evaluation or data privacy reasons) or in the cloud (for storage and anticipation of reoccurring patterns). In addition, it is possible to enrich this data with historical data or other relevant data sets, such as time of day, holidays, weather, etc.
  • If a retailer chooses a camera-based solution, no images or visuals will be saved, only the pure processed data, which will ease the concerns of privacy-sensitive customers.
  • Data sets are sent to a central dashboard for documentation and reporting purposes. This central dashboard eliminates siloed IoT reporting views and dashboards.
  • Employees receive a notification on their device of choice – e.g. smartphone – for real-time interaction.

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