Our goal is to optimize conversions in the Customer’s Journey. Our focus is the path from entry to exiting the physical store.
To test the impact of optimization techniques such as product positioning or in-store marketing, we need data. With data from tracking technologies, we quantify customers’ activities by location, time, and social interaction.
What Exactly is Behavior Science?
There are many areas where we find the footprints of behaviors. The most known is Behavioral Economics – a merge of psychology and economics. Daniel Kahneman and Amos Teversky won the Nobel Prize in 2002. And Richard Theler won this year.
We need Behavior Science to find opportunities for optimization.
The point is that whatever people do inside the store is measured. A metric is the package that translates tracking data into story.
Here’s an example.
The Details of A Metric
“Arrivals” is one of the key metrics in people tracking, and one of the easiest to use.
One of the tricks in Behavior Analytics is in the details of metrics.
Thus Arrivals is – “Arrivals is the sum of individuals who enter the store, by specific doors, one way, within a period of time”.
We are not talking about Visitors. The metric of Visitors can refer to Arrivals, Exiting, and other types of traffic. In the online world, Visitors is even more amorphous.
Also we are not talking about Buying Groups, only individuals.
We are also referring to counting people, not necessarily tracking objects. “Arrivals” refers to detecting, and recognizing objects, as people.
Another important factor in the definition is that we are not talking about a sample. “Arrivals” refers to the sum, the total number of people, of all the population within a period of time.
Once you defined the details, you know how to work with the metric.
In the context of the physical store, “Arrivals” signifies the beginning of the InStore Funnel. When people enter the store, they become sales potential.
Some might ask about Proximity.
The Capture Rate plays an important part in the full funnel and mall analytics. Yet we should go back to the original definition of Arrivals. The metric describes the actual entry to the store, thus “Arrivals” is the accurate start of the InStore funnel.
Our next step is actions. In other words – How to use “Arrivals” in optimization?
“Arrivals” triggers many events. The metric helps in understanding demand. It is also a factor in Occupancy. And it is part of the algorithms to structure lunch breaks for employees. Arrivals is often used to calculate Sales Conversion.
We also use “Arrivals” in Queue Management Systems to determine the number of active cashiers.
The metrics of “Arrivals” has many benefits because it ignites the InStore Funnel. Another way is to ask how this metrics impacts store operations.
For example, we consider Demand in context to Period of Time. The schedule is best adapted not to the current number of Arrivals, rather to previous period.
In peak periods such as lunchtime or the afternoon, it is clear you should have onsite staff. Yet the best practice is to schedule more people in the previous period. This due to how queues form.
By putting People First, metrics become powerful tools in store optimization.
Optimize to Perceptions
The data from “Arrivals” is one feed we use to understand crowd behaviors. Another metric is Occupancy.
The core idea behind such metrics is they quantify human perceptions. The sense of “crowds” is a perception.
People react to crowds differently. There are diverse cultural norms. As a retailer, you don’t want the shop to be empty. Yet do you want stores to be over-crowded? However we may define a “crowd”, it plays a part in how people feel about the shopping experience.
Other concepts such as Field of View and Sounds are also a component of what we define as “Customer Experience”.