How to Optimize Wait Time to Maximize In-Queue Impulse Sales

in-queue merchandisingAs a retailer, you face unique challenges when it comes to queue management and in-queue sales. On the one hand, you want to streamline your queue and keep wait times at a reasonable level. On the other hand, you want people to be in the queue long enough to consider those last minute impulse items you’ve so carefully selected and merchandised.

How can you marry these two objectives to create a queue that is optimized for impulse sales and acceptable wait times?

Merchandising analytics has the answers.

Merchandising analytics gives you a view into how well the items and “zones” within your queue are performing. When you combine this data with queue analytics, meaning information such as average wait times, customer throughput, and customer counts, you can gain a clear view of your front-end merchandising approach. From here, you can begin to play with the variables that impact wait times (staffing, open registers, etc.) and the merchandise you display (moving products around within the queue, swapping out low-performers, etc.) to create the best results for you and your customers.

Here’s a quick rundown of the steps:

  1. Capture Queue Data
    Install tracking in your queue using sensors, cameras, or other technology to capture key performance indicators, including queue length, wait time, customer count, arrival rate, service rate, and empty queues. Carefully select the monitoring technology that will work best with your existing infrastructure and budget. Also consider customer privacy and accuracy of data collection.
  2. Establish Merchandising “Zones” and Track Sales
    Break your queue into “zones” and record the merchandise SKUs you have in each zone. Begin to measure sales data in each zone.
  3. Analyze Sales Data and Queue Data
    Use merchandising analytics to transform sales and queue data into powerful insight, such as impressions per time interval, impression times per merchandising zone, arrival and service rates, and attrition/abandon rates.
  4. Run A/B Split Tests to Optimize Merchandising Mix
    Use the merchandising zones you’ve established and begin to look at your analytics data for each zone to see which performs best. Change up merchandise locations and collect more data until you have found the optimal mix.

With the insight gleaned from a merchandising analytics system, you can begin to effectively manage wait times and in-queue sales. No more guessing required. Everything you need to optimize and maintain your merchandising mix and queue can be right at your fingertips.

merchandising analytics quick guide

About
the Author
Perry Kuklin is the Director of Marketing and Business Development for Lavi Industries, a leading provider of public guidance and crowd control solutions.