The Artificial Intelligence that redesigns customer experience

Interview with Luca Altieri, Marketing Director, CMO at IBM Italia

Luca Altieri
Direttore Marketing, CMO @IBM Italia

IBM chooses to use the term "Augmented Intelligence" or "Cognitive" rather than "Artificial Intelligence". This is because intelligence is unique, and it belongs to human being.

We have moved from a society dominated by agriculture, to the industrial revolution, to a data-driven economy. What we have witnessed in each of these phases is the development of some tool or technology aimed at increasing our performance, thus improving results.

With AI, we will be more and more human: it is not going to take people’s place, but will support them in making decisions, and becoming increasingly effective and efficient. The human being will remain at the center in the future, as it has always been in the past.


We are in hyperhistory

Luciano Floridi, professor of Philosophy and Information ethics at Oxford University, in his book "The Fourth Revolution" divides the timeline into three phases: prehistory, history and hyperhistory.

Prehistory indicates an absence of ICT (Information and Communications Technology), history coincides with its development, still without a widespread and pervasive spread of it, while hyperhistory can be really called an "information society", in which technology and its ability to manage and process data are part of our daily lives

What trends were highlighted?

  • Technology has become accessible to everyone, with disruptive impact on how we live and do business. Digital has revolutionized the market: big brands are facing unexpected competitors, which have appeared on the horizon in just a few years. For example, Hilton would have envisaged themselves competing with Sheraton, but surely not with Airbnb. This means that without a technological leverage supporting your business, you are out of the game.
  • The exponential proliferation of data raises the matter of how to manage and process it. As Floridi states, storing data is the default option, the problem comes up when you have to choose what to get rid of: data is the "new oil" only if you know how to get useful information out of it.
  • The impact of Artificial Intelligence: in IBM, the term Increased Intelligence is preferred, as these systems can increase the potential skills of the individual (see IBM Watson).

Thanks to AI, companies can succeed in six critical areas:

1) Interaction: people are engaged with new, interactive and emotional shopping experiences

2) Engagement: there’s only one channel, and that is the consumer

3) Differentiation: interaction between customers and company changes, messages differentiate from each other, as they are targeted at the individual

4) Innovation: to keep up with the market, continuous innovation is necessary

5) Efficiency: technology makes production and business operations more efficient

6) Social responsibility: companies can support human progress and environmental sustainability

AI can be applied in any business sector. You can already see it at work in Content Management: in the optimization that comes from centralizing all assets on a single hub, automatically identifying their topics through tags that make them easily retrievable and shareable across teams, and creating associations with the customers who have visited them.

Algorithms, in fact, can study the consumer behavior towards content: this strategy is called Content Intelligence, and there are tools such as the Intelligent DAM which natively integrate it.

The data collected in this way, together with that already in the company's possession, make up a complete Single Customer View of the user's navigation path. At the same time enhancing the system itself, to learn which is the most suitable content to present to a certain visitor at any given time and eventually guide them towards conversion.

Q: Good morning Luca! What do you think of the application of AI to content production? Can such automation lift employees of repetitive tasks with low added value (like the manual classification of assets), leaving them more time to focus on valuable, creative activities?

A: Yes, we aspire to reduce our efforts in all those operations that can be automated, so that we can devote ourselves with clear minds to activities with higher added value. This is one of the objectives not only of AI, but of technological progress and innovation as a whole.

The introduction of machines started with the industrial revolutions and led to a constant reduction of manual and low added value work, that’s being repeated through the evolution of technology. We’re in the 4.0 industry now, and the most innovative solutions can’t not involve the implementation of AI.

Q: How important is it to collect data about content usage, having a complete view on the user’s navigation path regardless of the channel, and therefore forming an accurate representation of their interests?

A: It is fundamental. Nowadays we are bombarded with data, but we must divide between the two forms it can take: there’s structured data (eg. name, surname, ID code etc.) which is easily recognizable within a database, and unstructured data (photos, videos, social posts etc.), everything that is exchanged on the Net.

Most circulating data belong to the second type; AI can obtain useful information out of it, recognizing not only content but also the mindset of the person who published it (eg. systems Sentiment Analysis). The success lies in being able to manage different types of data in an integrated way, because although we are flooded with it, only 20% of data is publicly available. The remaining 80% is within companies (e.g. consumer preferences, purchasing history, demographics, etc.), so these internal and external sources need to be combined.

In Marketing, different types of data must be merged, from structured data like that coming from the consumer purchase profile (e.g. obtained from their Fidelity Card) to that which is available on the internet (e.g. what they say, what they like on social networks) and also other data that may seem irrelevant, but influences us (e.g. weather).

This is essential in order to create greater empathy with our customer, who will receive a personalized offer, not shaped from a generic profile but on concrete features characterizing that person and the context they move in.