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Big Data,  Technology

Big Data and Omnichannel Applied to Retail

Converting a store into a smart retail simply means using technology and Big Data to measure and sell more in omnichannel. Do you want to know how?

The model is gradually migrating towards a conception based on the client as a complex entity and on the purchase as a transversal process that runs through different channels and devices.

To a large extent, Big Data is helping to better understand and implement omnichannel in retail or eCommerce. How? In this post we tell you.

Why Big Data?

We tend to see ourselves as independent individuals with our own characteristics that make us unique.

This is true, but so is the fact of living in a society and a market that is governed by common rules for all. And we fit into different segmentations, user groups with common characteristics and very similar usage and consumption patterns.

What Big Data does is get all these raw data, organize and classify them to interpret them and transform them into trends. Part of massive information to act in a concrete way.

Why omnichannel?

I pointed it out in the introduction: considering an omnichannel strategy is to change the vision of the business to the level of the user. It supposes to stop analyzing the supports as if the clients that buy limit their interaction to a single channel and all the touchpoints of the Customer Journey will pass in it.

Within the omnichannel, the retail should be integrated prominently when there are physical stores. It is urgent that we forget the historical differentiation between online and offline: everything is part of the same business and has to be aligned based on these criteria.

Applying Big Data to retail

Let’s start from the basis that even small companies can implement omnicocality. What can be more complex on paper is to see how to find the fit of Big Data in retail.

We are much more familiar with the concept of analytics in the web environment. We have much more clear how it works and how it is measured through tools such as Google Analytics. We establish KPIs, we trace the conversions, the traffic, we have a geographical segmentation …

This would allow us to know our client and know what their behavior is, and we could extrapolate it to the retail. But it is not such a scientific method, and it is also overlooking certain variables and constraints that are not identical between the different channels.

In this case, the ideal is to resort to specific tools for retail. Software and hardware solutions that measure, interpret and report from within the store environment. This process of digital transformation of physical stores takes us to what is already beginning to be called smart retail.

EXAMPLE: We can premiere in smart retail using video or geo-positioning of products, for example.
 
These programs allow to measure the influx to the store or create heat maps (as in the measurement that is done on the websites). By having patterns of customer concentration, we can determine if we have a problem or where it is ideal to locate our promotions. And, even, doing it in real time, with which they generate alerts so that our staff can more efficiently manage the store.

All this results in a very detailed type of reports, very valuable information at the time, for example, to organize the employees' schedules. We will be able to anticipate the needs that we are going to have regarding personnel based on the data, and we will be more efficient in terms of management.

Beyond the video, other proximity marketing technologies such as beacons can be used. These small devices interact directly with the customers’ mobile phones, allowing them to launch notifications and promotions when they pass them (whether they are located in a linear, a header or any type of POS).

In 2018, it has been made public that Google is starting to send beacons to some stores within a somewhat experimental program (Project Beacon has called it, in a lack of originality). Those chosen by the search engine to participate receive one of these small devices with the pertinent explanation on how and where they should be located.
 
Beyond the technical side of the matter, there is a strategic explanation: Google wants to know precisely the physical location of customers and display advertising actions.

Will we see a Retail network within Google Ads adding to the search, display and shopping? Can we do campaigns directly for our customers from the Google platform? I would say that it is highly probable that this will end up happening.

This reflection leads directly to another equally relevant one. And it is none other than the specific weight that the mobile is acquiring in absolutely every strategy. If Google has bet openly for beacons, Amazon forgets them and puts at the center of its retail strategy the native app of its marketplace.

This was already key in the process of buying your Amazon Go store, which has a lot of experimental. But in some way it has been the precedent of something totally different.

Recently, this giant has launched a series of pop up stores in which customers can walk around the store, try the products and buy them by scanning one of their Smile Codes (simple QR codes) using their phone's camera and application. It is already without checkout and you do not have to load with the products. It is a very powerful and promising idea.

Conclusion

Thanks to Big Data, retail gains a lot in the strategic level by making decisions based on data. From the inventory or the disposition of the products in store to forecasts, optimization of resources, loyalty … But within the smart retail there is also space for the capture and direct conversion, which have a lot to do with omnichannel.

Do you find it interesting? Do you see possibilities to implement this strategy within your business? How would you do it?

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