3 Concepts of Data-Driven Growth of Physical Stores

The Physical Store is not Dead.

Conversion Optimization (CRO) for Physical Store requires a process. Three disciplines help us design a framework, regardless of tracking technology and solution provider. The first is Growth Hacking. Second is Behaviors. And the last is Analytics.

What’s Growth Hacking?  

Growth Hacking is a well-developed methodology in the online world. There are many methods, processes, and ways to scale online. The driving force is experimentation, or fast-fail processes.

The most prominent example is Facebook. With a startup frame of mind, Facebook is wired for growth. The Onboarding goal, for example, was to connect 7 friends in 10 days. And their core metric is Active Monthly Users.

Growth Hacking is techniques for exponential growth. It is not about a silver bullet, rather a process of testing and getting people hooked to your product. If you try to translate the methods directly to physical stores, they fail. This is because physical stores, as we discussed before, have their unique characteristics.

In the supermarket slide, we see an example where customer activities are tagged as Engage and Flow. The “tagging” is a first step in a systematic approach to growth in physical stores.

Behaviors in Physical Stores

Activities have context. But how do we measure context? The advantage of tracking people is we can describe context in terms of location and time. We can also use location and time to capture social behaviors.

Customer Engagement, for example, is defined by if distance from a display, and the stay time. The social factor is captured when two or more people walk in the same direction together. We can therefore track the behaviors of buying groups, such as girlfriends, or mother and kids. Also we can capture the interaction between and associate and a customer.

And we can add elements of Behavior Science. For example, we can see “optimal engagement” – measured by location and time – changes if we move displays or change products. Changes in pricing, visual merchandising and digital monitors to name a few, play a part in the psychology of buying.

The important part to remember is that metrics are building blocks. They describe the nature of the activity in terms of location, time, and social factors. In other words, metrics describe how people behave in physical stores.

Analytics in Physical Stores

Analytics is the information resulting from the systematic analysis of data or statistics. Tracking data describe activities in the physical store. In other words, we get information on the customer journey before the checkout.

Dwell Time and Stay Time, for example, are metrics that have different descriptions. Dwell Time is about detecting, hence counting, people. Stay Time is about counting seconds. Digital Screens and Touch Screens are another example for different data sets. The quality of analytics, therefore, depends on the nature and consistency of the metrics.

If metrics are building blocks, then the next step is Key Performance Indicators (KPIs). The idea is that KPI is a metric that captures a specific element of store operations. KPIs include Comp Sales, Sales Conversion, Service Intensity and Inventory Turnover.

North Star is a concept coming from Growth Hacking. It is the single metric that best captures the core value that your product delivers to customers. And it is a useful concept in projects.

In optimization of physical stores, our objective is to capture each step in the customer journey. We use data from tracking technologies to describe the activities. And we use concepts from Growth Hacking and Behavior Science to translate data into action.

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