The reality of phone retail
IntenDiNG OF PURCHASE
KNOWTHM’s recent Belgium study of the Waiting Experience – how customers perceive their waiting experience and its impact on their overall perception – revealed that 23% of shoppers with an intention to purchase do not complete their journey because of time constraints.
Shoppers go to a phone store to fulfill an immediate need. But if they arrive only to find that they have to wait, they all too often discover they do not have enough time to purchase the product they came in to buy.
Wait time – the negative impact on NPS
According to our study, a shopper’s Net Promotor Score (NPS) drops by 1.15 per minute after 13 minutes of waiting. When forced to wait longer than that to be served, a shopper’s overall satisfaction (CSAT) will fall to less than 50%. What’s more, customers remember a negative experience for at least two years.
An unsatisfying experience weighs in a shopper’s decision to return to a store, negatively impacting a phone retailer’s future performance. Since prolonged wait times depress NPS, satisfaction and sales, putting customers in full control of their time is the single most efficient way to improve store performance.
NPS drop for each extra minute spent
Phone stores can lose up to 1 400€ ($1,708*) per day
Our study indicated that 10% of shoppers intending to purchase a phone will
not wait long enough to meet with a sales associate – and 13% of them will
not buy due to lack of time, even after meeting with an associate.
In a typical phone store with 130 walk-in visits/day and an 18% closing rate, this attrition of the purchasing funnel will lead to the loss of seven (7) customers per day.
|No. of shoppers||% of walk-ins||% intendig to purchase|
|Walk-in shoppers intending to purchase a phone||30||23%||100%|
|Walk-in shoppers able to purchase a phone||23||18%||77%|
|Walk-in shoppers unable to meet with an associate||3||2%||10%|
|Walk-in shoppers able to meet with an associate but unable to complete a transaction||4||3%||13%|
|Average number of phone purchases lost per day||7||5%||23%|
|Average basket size||200€ ($244/£180)|
|Lost sales/day in a typical phone store||1 400€ ($1,708*/ £1,260**)|
(* Based on an USD exchange rate of 1.22.
** Based on a GBP exchange rate of .9)
SmartQueue cuts wait times by up to 50% and improves store performance
Fig.1 Traditional FIFO Queuing
Fig.2 SmartQueue by KNOWTHM
By adding context to the conventional FIFO service rule, SmartQueue calculates service time by accounting for: travel time to store, probability of purchase, state of the queue, store service capacity and the priority of other shoppers in the queue.
For the same store with identical traffic patterns (130 visits and one peak lunch hour per day), a conventional FIFO queuing algorithm will consistently generate wait times exceeding the 23-minute threshold past which individual NPS ratings fall to zero (Fig.1).
By comparison, during peak hours, SmartQueue reduces wait times by 30% to 50%, letting retailers serve more customers and keep them more satisfied (Fig. 2).