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Retail Analytics. How to monetize the data generated by your stores

  • Data dominates all our decisions: which products we display, which ones we promote, or when we do so.
  • For brands and distributors, stores are a source of highly qualified data and a complement to their digital platforms.
  • In this post, we’ll give you the keys to put them at the service of your decision-making process.

Information is power, particularly in Retail

There are three reasons that explain the exponential growth of eCommerce in recent years. Convenience and cost are the two most obvious. The third one may not be quite so obvious, but it’s just as important, if not more: data.

Digital media provide us with 100% reliable and real-time information about everything that happens inside and outside our store. This knowledge can easily be put to use when deciding absolutely everything that has to do with our business, and it can even adapt the content of the point of sale in real-time for the user:

  1. What products do I replace and which ones do I get rid of.
  2. Which ones should I promote.
  3. Adapt these promotions to the type of user who walks by a digital medium.
  4. What type of consumer is attracted to each one.
  5. Where are those consumers: in digital and physical terms.
  6. Which campaigns would work best with each of my buyer personas (types of consumer).
  7. And, if we have created suitable data architecture, why does everything happen.

Can Retail emulate this ability to capture data?

One of the most viralized cases of analysis of Retail data was the Target one, a multi-brand chain in the US, where it was speculated how Target, through a follow-up of the products bought by women in its stores, was able to analyse their consumer trends and predict when they were pregnant, anticipating their next acquisitions with a more effective, targeted advertising strategy.

It was never clear, even to this day, if the original article analysing the case was, in fact, covert advertising from agencies devoted to exploiting data, but it does illustrate perfectly the potential that data has for Retail in our business.

And best of all, the cost of these systems gets lower every day.

What data can be collected in a physical store

To explain this relatively new and complex world in the most orderly way possible, in this article we will establish two categories that help us understand the types of data that it’s possible to collect in a store.

The first, according to its origin:

Direct data

This is the data obtained from the direct interaction of the consumer with the store. When people touch a screen, go near a piece of furniture, play a game, fill out a form, buy an item…

The main use we make of this data is to measure the effectiveness of the design, experience and products that make up the store, by answering questions such as:

  • Does the route we have established in our store work?
  • Are there any dead areas or products that are not looked at?
  • Is the consumer willing to interact with our brand beyond the purchase of products?
  • What is the profile of the typical consumer going into the stores (gender, age, products that they are most interested in etc.)?
  • Why is cross-selling of certain products not working?
  • What makes customers decide not to finally buy a product? 

Indirect data

They are those that we collect thanks to the fact that the consumer, inside our stores, makes use of their mobile phone and bridge platforms. This is passive data, collected without the consumer actually having any specific interaction.

They mainly help us to quantify and qualify the attendance in the store: type of consumers, at what time does each of them visit the store, average duration of the visit…

With that understanding, the next logical categorization is the technology used to collect them.

Bluetooth beacon: they react to the presence of a mobile phone with our brand app installed, which allows the user to launch hyper-personalized promotions. Additionally, the Bluetooth Beacon lets you know when a customer using our App visits a store.

Mobile telephony microcells: version 2.0 of analogue meters. They quantify the consumers within our store in real-time. 

This information is very valuable since very specific information is obtained from the consumer (where the people who come here are from, where they live, where they work, gender, age, purchasing power, etc.), as well as information about the point of sale, such as the recurrence of customers in the store, the conversion rate or the percentage of people who walk past the store.

Cameras with algorithms for analysing consumer behaviour: by integrating artificial intelligence into security cameras at points of sale, consumer behaviour within the point of sale can be comprehensively analysed in real-time. Very valuable information is obtained for the most efficient businesses and sales actions, such as how customers go through the different sections, which are the products they stop to look at the most and show the most interest in, how they interact in physical spaces, which ones are the hot and cold spots of the business, as well as the busiest hours in each section.

Various sensors:they can be proximity, beam, pressure, movement sensors… They allow us to identify and quantify the consumer. They are also used to launch animations or content interactions, messages on the screens, etc.

RFID: one of the most widespread technologies in Retail.

It could be described as electronic labelling of products, but they can be used for much more than to merely carry in-store inventory. They allow us to launch interactivity and track consumers throughout our store when they carry a product with them.

WiFi: the data provided by the open WiFi network in our business, as a free benefit for our clients. It’s especially useful when one of our target audiences are tourists, who usually need it the most. This provides us with both counting and browsing data, helping us understand which websites or apps they visit in relation to our store.

 Now technology allows data to be collected in physical stores, in a similar way to that obtained from online retailers, equalising the analysis capacity between the online and offline world.

How to monetize the data obtained

The first step is to set a specific objective behind each piece of information that we want to collect. Ask the right questions.

Especially because a single piece of information won’t usually be of much use. It’s by cross-referencing the concrete data that we really begin to extract the Retail Consumer Insights. That’s when we learn about our consumers.

We will see this compiled in our dashboards, which automate this cross-referencing. But let’s get to the real point about the main benefits that we can obtain from Retail Analytics.

  1. Profiling your consumers: we can quantify and segment the people who come into our stores, in order to detect if the desired target audience is the one that actually comes in, or not. Also when it comes to launching promotions and campaigns, both physical and online.
  2. Analysing routes and average times spent in the store to discover why.
  3. Understanding how many products people interact within the store and why, and which ones do not reach the checkout.
  4. Customising the contents of the store based on the data detected (profile, gender, age, products used…).
  5. Re-targeting on social networks by segmenting those who have been to your store.

 If you want to know more about content and digital signalling in this post we tell you all its secrets.