Always migrate your audience to the path of least resistance. –Kintan Brahmbhatt@Amazon
If you want to optimize your store for profit, think not only on ‘what is right’ but how to fix what is “wrong”. This is not about a lack of interest, a real-world bounce behavior. This is about Customer Displeasure. We are going to think about why interested customers abandon the store.
Winning retailers win because they obsess over every detail of the shopping journey. This includes friction such as checkout, bottleneck and abandon behaviors.
In optimization, we focus on each touch point in the store and ask three questions. One – what customers are doing? Two – what can we do better? And three – is there an obstacle and how can we fix it? If you are looking for quick wins in optimization projects, most of the time we can find a win by learning to see obstacles as opportunities.
The champion of transforming obstacles into sales opportunities is Amazon. You may recall that Amazon growth soared with 1-click purchase. In order for a customer to benefit from 1-Click they had to have their payment and delivery information in Amazon. This in turn led to the basis of Prime Membership. Every successful step has a strong component of preventing friction – think Dash Buttons and Alexa Voice Shopping.
When asked about obstacles, most retailers point to the checkout process. Despite advances in mobile payment solutions, there are situations where we will probably continue to see queues, for example in supermarkets with many items basket, or passport checkouts in airports, and even in front of self service kiosks.
Managing queues is especially important because in many retail stores this is the last touch point with the customer. This is also where Time Based models are useful. Measuring the Average Wait Time is much less effective than managing to 95% of customers served less than 3 minutes. This is also an area where costs are directly tied to customer satisfaction.
Queues also play an important part in retail services, such as Quick Service Restaurants, transportation hubs, and retail banking. In these situations, the first encounter with the customer is the line. There’s a slew of literature why people tolerate long lines in situations like concerts or the release of iPhone, but in most cases the goal is to prevent the formation of queues.
Bottlenecks are common obstacles to shopping, which are often overlooked by retail executives. Since full coverage of stores is almost non-existent, the responsibility of dealing with bottlenecks is handed down to the local store manager.
I have been witness to many events where an action had the unintended consequences, from a display table that erupted customer flow to the checkout, to a coffee counter in high traffic, and stocking shelves during lunchtime.
Bottlenecks are often a result of poor communication between corporate and stores.
On the extreme side of customer displeasure we find the abandon behaviors. These are extremes in the sense that customers will actively display displeasure. There are 4 types of abandon behaviors.
The first is a straight forward leaving the line or activity. This is simple to monitor, yet the reasons for the abandon are not always so clear. An example is the need to fill up a form or simply jumping to another line.
The most common behavior is not entering a line because it is “too long” or “too slow”. These perceptions play an important part. For example, a high end bank in London had serious abandon issues simply because people in line for the ATM closed the entrance to the bank.
The most revenue-lost abandon behavior is when it relates to the brand. And frankly, these metrics are usually a highly guarded secret by the retailers.
Abandon behaviors are about preventing displeasure. This is not about non-engagement. Abandons are not similar to online bounce scenarios. These are situations that create frictions in the path to purchase.
The Duality of Trajectory
Trajectory is a fantastic analytics tool. It captures the direction of motion. And it allows us to identify behaviors that customers and staff are not expected to do.
When it comes to measuring abandons, we should avoid the sales hype. We should focus on how we are going to use the information to test store operations and marketing.
Case Study: Abandon the Queue
This is a story about a store that no longer exists. It is about a customer who left in the middle of the queue. He did not leave because there were not enough cashiers. He did not turn because the line was not moving fast enough. The reason he left had to do with the way the queue was setup.
The store had high-rise displays, and when you walked into the entry point of the line, you did not see the exit point. As you walked around the bend, you would have found out that the line was much longer than you had expected. This is exactly what happened to this man. As he turned the corner, he saw that instead of 10 people in line, there are 40 waiting to check out. And he left the queue in anger.
Trajectory Analytics is a great tool to have when we design Concept Stores or run A/B testing.
Trajectory is a double usage metric. It has positive connotations when we talk about customer engagement. It can also be useful to identify what’s wrong. We use it in queue management, staff behaviors, bottlenecks, and detours. We use it in situations where we test for customer flow and store operations.
Case Study: Promoting Halloween
I’d like to give you an example where the direction of motion helped assess the business benefits of a project. A store setup a large table with costumes and black/orange cup cakes in the center of the main aisle. It was a prominent display and many customers stopped to take a look. Yet, the position of the table caused a shift in the natural flow of traffic in the store. In turn, this created bottlenecks in various parts of the store.
Again, Trajectory is a metric we use for operations, and we use it for marketing, and in the context of obstacles.
Here are examples of how we can identify abnormal behaviors. If a person moves from a point inside the queue back to the entry line, this is a wrong direction. If we track a customer going up to the third floor and then direct to the elevator, this is a sign of confusion.
Situations of returned visits to the same location can show interest but indecision. When a person loiters back and forth that is a loss prevention behavior. When people enter a department through the back instead of the main aisle, this is a question of layout.
Trajectory metrics allows us to track situations where the direction of motion is unexpected. If this occurs, we need to check out the cause for such behaviors.
Bringing It All Together
In optimization projects, we care a great deal about customer flows. We pay much attention to how customers navigate between web pages. On the same level, we should pay attention to how customers move in the store. And when it comes to traffic flows in aisles, between departments, and other zones, we need to think about obstacles.