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AI applied to Retail: why you should go Phygital

Luca Ricci

Over the last few decades, the relationship between Brand and consumers has changed a lot, in particular since the rise of first digital media. Companies have got two great opportunities at the same time: the first was communicating directly with their potential audience, and the second was accessing an ever-increasing amount of data, so that they could understand behaviors and trends within their markets.

However the approach to these new opportunities has always looked like a wave movement, alternating great evolutions and then great involutions: from the enthusiasm for the world wide web and the “virtual” world to the comeback of physical stores, from the mobile revolution to the digital explosion due to the pandemic. 

Today we are witnessing a highly complex scenario, populated by increasingly hybrid and phygital consumers: these new customers are quite fluid and not really attached to brands, they know digital purchases are much easier, but they also like the real in-store shopping experience.

Phygital: why companies need to reconcile digital and physical to be really data-driven

Nowadays, the real challenge for companies is to adopt the best Direct to Consumer technologies, allowing the customer to interact with the brand in a digital way, without preventing the physical in-store experience. On the contrary: the best solution is completing and enriching it on other touchpoints.

This is why increasingly advanced e-commerce solutions are available today, featuring augmented reality platforms, and mobile app solutions that let you visit the physical store, while interacting with the branded digital services.

Even if it is certainly complex, today more than ever it is still necessary to reconcile all customer data: online, mobile and in-store.

How can you manage to collect, process, enrich and activate them correctly? AI is a fundamental tool for empowerment.


AI in hybrid user experiences: from customer intelligence to RFM analysis

What should retail players do, considering both physical and digital touchpoints, to better understand and cluster their customer base?

The first step is adopting a suitable customer intelligence solution, such as Trend AI, in order to map online searches, trends and intentions, seasonality and query steps, from the information provided to the actual transaction.

Moreover, they should also use a specific tool to collect the user’s browsing data, through Google Analytics, on all their digital properties, and analyze the purchasing behavior through their internal CRM. They can also monitor In-store behavior, thanks to SDK solutions in-app.

The next step is reconciling user data. Today companies often have huge datasets at their disposal, but these are disconnected from one another, without any chance to get meaningful insights.

Companies are unable to properly follow users throughout their customer journey, acknowledging when they switch from one device to another, going from the physical to the virtual world and vice versa.

Facing the challenge of piecing together all the steps and associating them with a specific user means they fully understand all the trends, threats and opportunities of their customers, in order to activate them in the best possible way.

Only by choosing the most suitable tracking technologies and setting them at their optimal configuration, according with your business objectives, you achieve this result.

Finally, here comes the data modeling, to associate the best behaviors and interests with customers of greater potential and value. Thanks to dedicated tools such as Retention AI, you can cluster customer groups according to their behavior, interest and RFM analysis, so as to optimize the retargeting campaigns, email marketing and push for repurchase carried out through advertising platforms.