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The acceleration of data-driven retail in Italy

Marco Belmondo

written by Marco Belmondo (Chief Marketing Officer at Datrix)

The retail sector is so vast and heterogeneous that it shows very different behaviors and dynamics in response to the pandemic and the resulting lockdown in Italy. The fashion segment, for example, according to Confindustria (the main association representing manufacturing and service companies in Italy), lost 29 billion Euros in 2020 compared to the previous year (30% of turnover), while the large-scale retail sector, on the contrary, gained 7.6% in the same period (IRI estimate). E-commerce, finally, has shown a growth of 55% (Netcomm estimate), but above all has recorded the arrival on the market of two million new users, a figure that will presumably make its effects felt even after the end of the pandemic emergency.
It is precisely the long-term effects that Retailers should evaluate most carefully, especially those that in some way have induced a change in the purchasing behavior of users. The “hyper-connected users”, as some analysts have dubbed them, are even more demanding in terms of expectations regarding response times and the use of digital channels by Retailers (because during the pandemic they have become more familiar with devices and applications) in an omnichannel perspective and in full respect of privacy.
For Retailers, therefore, the challenge is important: in addition to reacting to the dynamism of the moment (which, in any case, is already a considerable challenge) by strengthening omnichannel marketing, it is necessary to further improve the customer experience, learning to meet the needs of customers and potential buyers better. This is a challenge that can only be met by learning to manage and enhance data, transforming it into useful information to provide a better experience for customers.
It’s a challenge that entrepreneurs and managers seem to be well aware of, as shown by a recent survey (January 2021) by The Innovation Group. On a significant sample of Italian companies from all sectors and of all sizes, the solutions on which decision makers have invested the most in 2020 and on which they plan to invest the most in 2021 are those related to Customer Experience, cloud (in its different variants), big data and artificial intelligence.

Retailers and Omnichanneling

The priorities of decision makers during and after the pandemic are also highlighted by a McKinsey analysis carried out during the emergency period and centered precisely on the Retail sector. “The most useful strategy is offering a consistent experience to the customer, in any channel. The second fundamental point is personalization: in the future it will be increasingly important to be able to offer potential customers content tailored to them.
The last important theme is operational improvement: the pandemic has shown that we need to free up resources on the backend to be more efficient, and the good news is that there are technologies and tools that allow us to do this”.
At 3rdPlace we base our strategy in the Retail market on the three pillars corresponding to the current needs of Retail companies:

  1. omnichannel,
  2. customer centric data platform (or customer intelligent platform) based on first party data,
  3. efficiency and operational improvement (especially with AI and machine learning tools).

The tech solutions for data-driven retail strategies

In order to enhance the relationship between brand and consumer, it is necessary to collect, analyze and exploit all the data made available to the retailer. Becoming data-driven points of sale means knowing how to profile one’s own interlocutors, segmenting them according to their preferences and therefore being able to have the elements to satisfy them or even anticipate their needs.
According to a recent mapping conducted by Chiefmartec.com, there are more than 8,000 relevant marketing technologies, of which more than 1,200 are data-driven. These include Data Management Platforms (DMPs), which are primarily intended to manage advertising by leveraging third-party cookies, and Customer Data Platforms (CDPs), which instead allow for the integration of data from a much wider variety of sources, while also offering immediate action capabilities. Then there are more than 2,000 technologies classified in the Social & Relationship category, including Customer Relationship Management (CRM) and the various Customer Experience and Customer Journey Analytics platforms.
The Customer Data Platforms and their evolutions — the Customer Intelligent Platforms — are the most suitable Customer Analytics technologies to collect and manage data from different sources in a unified way and to transform them into knowledge useful to redesign the user experience in one or more stages, in one or more touch points.
Neither CRMs nor DMPs are fit for purpose. The first are intended to accommodate mostly manually imputed data and tend to be rather rigid, focused as they are on socio-demographic and transactional aspects. They also don’t cross silos, nor are they suited to handling data dynamically along individual user paths.
DMPs were born precisely to integrate the data collected with cookies and primarily for scheduling and managing marketing campaigns. They do not offer a complete view of the customer nor do they enable dynamic management of individual Customer Journeys.
A simultaneous data-driven and customer-centric approach is provided by the Customer Data Platforms, which allow you to follow the customer along the main paths of interaction with the organization, making decisions based on the data collected and analyzed.

The Customer Intelligent Platforms

Customer Intelligent Platforms such as DataLysm allow customer data to be integrated with anonymized or aggregated behavioral data to provide a complete view of the customer but also of the user. Through machine learning algorithms, these solutions of Augmented Analytics build predictive models and recommendation engines, translating knowledge into action. What’s needed is precisely a unified and dynamic view of the customer and user, connected to the specific Customer Journey.

Why more advanced Customer Analytics technologies are needed to more effectively build the Customer Journey is explained by some simple data. As a result of the pandemic, 76% of people have permanently changed their consumer habits, choosing different products and brands, changing behaviors and experiences sought and enjoyed, reveals a McKinsey study.
The impending stop to third-party cookies makes it necessary for 75% of European marketers (IAB data) to rethink how data is collected, integrated and used to create personalized shopping and usage experiences.
In a survey conducted by Merkle Inc. 59% of marketers clearly identified the impact caused by the new Google policy in managing third-party cookies. In summary, on both the demand and supply side, for 3 out of 4 people, the current structure of the channel, contact points and the way they are managed must change permanently and radically.
New Customer Analytics platforms enable exactly this necessary orchestration of marketing for dynamic Customer Journey management that responds to deep consumer change.