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Artificial Intelligence in Marketing

Published on .

Based on the inspiring talk of Jeremy Waite, Marketing visionary of IBM Watson Marketing at WebTomorrow 2017 in Ghent.

Fun fact: 90% of all global data has been created within just the last 12 months. And this astonishing number is ever increasing at an exponential speed. It’s close to impossible to comprehend how much data is actually being released every second. As a result, people are getting overwhelmed. But than how, as a marketer, can you read and analyze all this data about your consumers and your market, making sure you focus on relevancy and efficiency?

A straightforward answer to this question is by using Marketing Automation tools. These tools make use of all the data people are releasing in the world. They help personalize your message to the customer, resulted in tailored 1:1 communication. But what if consumers do not want to share their data anymore?

Dark data

Amidst the ongoing online privacy debates, consumers do not want to share their data with the whole wide world and especially not with corporations any longer. More and more ‘dark data’ is going around. This data is not visible for marketers or marketing automation tools, as it is predominantly hidden behind privacy walls. People have the right to protect their privacy and not share data, but this makes it significantly harder for companies to personalize their offerings to the consumer.

We notice that today’s trend is actually a contradictive two-way scenario: one way the consumer expects a great experience and wants to be treated in the way he or she prefers, ergo tailored and individualized communication. On the other hand, the consumer doesn’t want to share data with companies anymore, so these companies face a hard time figuring out what the consumer prefers.

“Cognitive is the new CRM”

As the data companies receive is not 100% complete, campaigns cannot solely be based on this data any longer. It seems, in these data-driven times, that marketers increasingly have to return to trusting their guts when making decisions, which is a stark contradiction in terms. So, on what are your decisions based? Personalization is only easy when you receive insightful data.

When we have to follow our guts and intuition, we are dealing with personification instead of personalization. According to personification, it is of the essence to grasp the emotions and feelings of your consumer towards your brand, rather than being focused on obtaining all data, which is likely skewed.

Personification: The attribution of human nature or character to inanimate objects, e.g. data. Follow your guts, know the emotions/feelings of your consumer.

Today, AI [Artificial intelligence] can help marketers to read data even though consumers are keeping a tight lid on exposing their personal data. AI tools, mostly an advanced functionality of Marketing Automation platforms, will help you read the emotions and feelings your consumer is displaying. It will be by far the smartest assistant you can imagine. It will help you to reach the right person at the right time, on the right channel with the right message, without receiving personal information.

Pharmaceutical and AI

The pharmaceutical industry, Adagio’s key playing field, is also increasingly looking to AI and data science in general. AI and advanced data interpretation has already been quite common in regards to drug development cost-cutting and early go/no-go decision on pipeline candidates. However, Sales and Marketing roles have been left out and would distinctively benefit from extensive data-driven decision making in business, which are well enabled by AI processes. This entails the use of new tools, platforms, capabilities and competencies.

Boehringer Ingelheim’s Global Chief Data Scientist, P. Diesinger, believes that the “combination of AI, big data and new perceptions of deep analytical methods” is a new and reinforcing approach for the whole industry. Today, the bulk of the industry’s key performers already rely on marketing automation platforms, exhibiting differentiating levels of expertise. Nevertheless, the use of AI, predictive modeling, data pattern analysis etc. still seems a distant world.

One last word: data

Even though AI receives and deserves all the hype it gets nowadays, one has to take into account a crucial word of caution: data.

As we have reiterated many times again, data is the life blood of your digital environment and, as such, the quality of that data is pivotal. If not, even AI will not serve you many benefits. So before engaging on a quest for AI implementation and usage in your organization, make sure you have the basics of data management, quality and optimization in place. In the end, your car won’t go far with bad fuel. So why would your organization?