Key Metrics That Can Make or Break Your Pickup Program

Adoption of in-store and curbside pickup is growing rapidly, increasing nearly 43% from 2015 to 2017 with 50% of shoppers having used a buy-online-pick-up-in-store (BOPIS) service in the last 12 months, according to JDA. While a large number of businesses have adopted a mobile ordering program to stay competitive and meet customer demand, scaling your program can be challenging. When evaluating the performance of these programs, there are new metrics that you should monitor regularly, especially at launch.


 

Customer Wait Time

What is it? Wait time is the time period from when your customers pull into your parking lot to when they receive their order.

If there is one metric you should be obsessing over with your mobile order ahead program, it’s customer wait time. The time a customer waits to pick up their order directly impacts their satisfaction and likelihood to make a repeat purchase. We’ve found that customers are 2x more likely to repeat if their wait time is under 2 minutes.

There are a few things you can do to lower your customer wait time. First, operators need a technology solution that is designed for pickup, not ordering. A queue of orders sorted by actual pickup time reduces wait times for most customers. Store personnel with a sorted work list and visibility into order status, arrival ETAs, and customer wait time perform better. Second, operators with accurate and reliable arrival notifications integrated into current systems are able to trim minutes off wait from every order. Third, business managers at all levels need real time and historical wait time data so they can continually monitor performance at each location and address process or training issues quickly.

 

Dwell Time

What is it? Dwell time is the time period that your customer is at your location from wheels/feet on premises to wheels/feet off premises.

For most order ahead programs, dwell time is critical to knowing a full picture of the number of parking spots needed for customers that are picking up orders. If customers are dwelling, overall throughput of the program can decline. Poor throughput doesn’t just affect your order ahead customers. If you do not have available designated pickup parking spots, your order ahead customers are going to park elsewhere, reducing the number of spots available for in-store shoppers, and decreasing customer satisfaction for both in store and pickup customers.

Typically, the easiest way to reduce dwell time is to reduce customer wait time. Longer than expected dwell times can signal problems with a pickup program or unexpected customer behavior after pickup. It can be an issue to address through customer communication or an opportunity to upsell customers on additional items, since they are still at your location.

It is important to note that sometimes customer wait cannot be measured because current systems do not support capturing the handoff of pickup orders to customers. Dwell time then becomes the key metric. Dwell time can be measured solely with location technology and does not require changes in processes and systems. For take-away orders in food & beverage and BOPIS in retail, dwell time is a good surrogate for wait time.

 

Customer Satisfaction

What is it? Customer satisfaction measures how satisfied customers are with your service and how likely they are to remain loyal to your business.

One of the most popular methods for measuring customer satisfaction is the Customer Satisfaction Score (CSAT). It is easy to implement and requires a single question “How satisfied were you with your experience?” along with a corresponding survey scale. Businesses will get best results from their CSAT if it is sent immediately after the user completes their pickup so that it is fresh in their mind. By sending the CSAT regularly, businesses can track customer satisfaction over time and spot issues at specific locations.

A more sophisticated measure of customer satisfaction is the Net Promoter Score (NPS).  Since the growth of order ahead programs is a function of repeat rate and referrals, it is well suited to gauge the customer’s experience and likely behavior.

NPS is calculated with a single question “How likely is it that you would recommend [brand] to a friend or colleague?”, typically on a 0-10 scale. Those that respond with a 9-10 are considered Promoters and are more likely to purchase often, remain customers longer, and refer friends and family. Those that score 0-6 are considered Detractors and are unhappy customers who may impede growth through negative word of mouth. Those that respond with 7-8 are considered Passives and are satisfied but unenthusiastic and are more likely to move to a competitor. Subtracting the percentage of Detractors from the percentage of Promoters yields the Net Promoter Score.