Customer Engagement: Analytics of Customer Journey in Physical Stores

How do you quantify Customer Engagement in Physical Stores?

In Marketing, the analytics of Customer Engagement are well-known. Successful online marketers mastered the metrics of the Customer’s Journey. In Optimization of Physical Stores, we measure Customer Engagement by capturing behaviors.

In social media, we can quantify emotions based on facial recognition. We paint customer sentiments based on social posts. In the digital world, we can follow what customers do on web pages.

These concepts are harder to do in the physical world. We can track the location of smartphones. We can review transaction data. And we are getting more and more data from a variety of technologies in the Internet of Things universe. Technically, the data tells us Who, Where, and When. It’s our job to figure out the Why.

What’s Customer Experience

When we think about retailers that do “Customer Experience” well, the Apple Store comes up often. The spaceship like store, with long plain wooden tables for playing with the products, and the blue shirt associates. These are features that we have to come to identify with the Apple Store. What makes it truly unique is that this format has gone through more than 30 iterations and 7 overalls before Apple settled on their preferred theme.

If there is one thing to remember from Apple is that their stores were optimized by research and testing. We love their stores because the stores were designed based on customer feedback.

Not only we can design the layout of the store to customer feedback, we can also design the store itself. The format of the traditional store is also being challenged. Another disruption comes from the nature of the physical store itself.

A recent hot trend is the emergence of temporary pop up stores. We also see Self Service Kiosks, Touch Screens, and Stores within Stores. Levi’s Jeans, for example, avoids speaking about stores and in turn talks about 50 Distribution Points.  The key to understanding store is to view them as sales channels.

In Optimization, we dig deeper into Customer Engagement. We focus on interactions.  We can gauge engagement with a product, a display, a zone, a department, or the store itself.

The details of measuring customer behaviors depend on the technologies we use, and their accuracy.

10 Ideas to InStore Optimization

Here’s an example of how we quantify behaviors.

The Power of Stay Time

“Stay Time” is a powerful metric to capture the context of customer engagement.

This is not “Dwell Time” where the definition is more general, and is attributed to detection.  “Stay Time” refers to tracking individual objects.

Stay Time is the number of seconds a person stays in a defined location.

Because Stay Time measures in seconds, accuracy matters. We won’t discuss this topic now. It’s discussed in depth in our course on Best Practices in Accuracy.

Another topic we will avoid is Average Stay Time. The Average Time metric is misleading and does not have a practical application.

It’s important to note that Stay Time is not a sample. This is an individual metric. Because we track the behavior of a specific person, we can dive deep into optimal behaviors.

Stay Time is a phenomenal metric because it has practical applications. It helps in forecasting trends. It helps in measuring the effectiveness of virtual merchandising and InStore marketing. In almost every aspect of customer engagement, we can use Stay Time.

Case Study: Black Pants

The first example comes from measuring engagement with a Touch-and-Feel product. With “Stay Time”, we quantified customers’ interest in a pair of black jeans.

We found out that when “Stay Time” is less than 15 seconds, there is no customer engagement. The person passed by the display with no interest.

The levels of engagement were between 1 minute and 3 minutes. If the Stay Time was above 3 minutes it was a customer talking on the phone or a staff member. The customer behaviors were so consistent it was easy to optimize the engagement period.

Case Study: Cereal Box

In a supermarket, the game is different. Products such as Cereal Box are not Touch-and-Feel. In most situations, you will search for your brand in a specific place.

In this particular example, the fastest purchase point lasts 10 seconds. The maximum Stay Time for people who put the cereal box into their carts is 30 seconds. If a person was in the aisle for more than 30 seconds, something was amiss. If you were in the aisle for less than 5 seconds, it means there was no stopping, and no interaction.

The optimal engagement period depends on the product, and it depends on “Stay Time”.

Bringing It All Together

Quantifying customer engagement is a key element in Optimization. This is more than just measuring how customers interact with products, layouts, and staff. This is also a question of what retailers do.

When we design optimization projects, we define engagement metrics with action in mind. In physical stores, we can adapt customer service and product positioning in real-time.

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