23 October 2018

The Causes of Abandon Behavior

In our previous article we wrote about how physical comfort in store matters to customers, the placement and dimensions of aisles and overall layout of the store is a very crucial determinant of customer’s satisfaction.

There are numerous factors which can significantly contribute to this kind of customer behavior. Ranging from unnatural store design mentioned above, overall confounding employee management to long waiting times in queues.

LAYOUT MATTERS, BUT

Whereas not ideal store layout and customer’s physical discomfort in most cases lead to loss of the conceivably loyal customer, two remaining cases may result in shopper’s exit without actual purchase.

If a customer subconsciously feels that placement of shelves with goods is so chaotic that it makes him uncomfortable to find the desired product, there’s a high probability he’ll look up to it and buy it after all. Nonetheless, the direct consequence of this will be ‘Not Returning to Store’ behavior, as long as customer remembers lousy shopping experience.

ANNOYING QUEUES

Poor workforce management and long waiting times in queues could, on the other hand, have a harsher impact. If we were to ask, the most annoying moment of shopping would be endless waiting in the queue. Combine it with inefficient work shift optimization, and you’re on track to serious chaos during the rush hours. What could that chaos look like?

The worst case scenario is a furious customer making a swift exit without purchasing anything.

WHAT CAN BE DONE?

How to fight with this? Ideally, we may look up to Amazon’s ‘GO’ concept, where is no checkouts and queue lines whatsoever. Yet, this is the luxury which may afford only a few big players in a game (for now).

Still, there’s also another technological solution, which is capable of substantially helping retailers with avoiding long queue lines.

We at Pygmalios are proud of our seamless technology, which is among other things capable of monitoring congestion patterns.

By doing that, we can deliberately forecast when and where queues occur and effectively shorten the average queue length. The data we collect also enables you to schedule your workforce more accordingly.

Always try to move your customer to the path of least resistance.

 
David Borovsky, Marketing Intern


Read also:
The Purpose of Data Collection 
In-store Analytics Are the New Norm 

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