When people spoke about personalization, all they meant was that a mail was introduced with a person’s name (‘Dear Franck…’) rather than an anonymous greeting (‘Dear Sir or Madam’).

Heidi Unruh, Global VP Content Marketing at e-Spirit, said “Today, consumers are bombarded with countless advertising and marketing messages, making it more and more difficult for brands to engage with the customer. Artificial Intelligence might be a solution to this issue.” (source)

Indeed, hyper-personalization will become an important trend in the world of AI. Once again, data is central to making this happen. The more data there is available, the more relevant information and products become. This evolution means the end of the road for the marketing approach of segmentation. Segmentation divides the market into a number of groups with similar needs. This allows the marketeer to match both communication and product characteristics to the needs of each different segment. Based on this approach, marketing teams assume a high degree of homogeneity within and between segments.

If your market has five segments, this means you have just five types of customer. Each of these groups has its own specific requirements. Imagine that your product is targeted at men between the ages of 25 and 35, not married and with a fulltime job. As an old-style marketeer, you will consider all these men as being more or less identical.

However, if you had the opportunity to observe this group in real life, you would soon realize that they are far from identical! Segmentation was a good solution when personal data was lacking. But this data is now available — and it shows that every consumer has a different personal context, which means that their consumption and communication needs are often very different.

The “Evolved Consumer” challenge

For Alina Charania, Client Strategy Associate at rDialogue, “Today, consumers actively seek information before buying and don’t place their trust easily in brands. Moreover, consumer behavior is heavily reliant on Reviews, User Generated Content & Influencers. However, there is still a gap even after consumers clearly state their expectations of brands. According to the Bond Brand Loyalty Report of 2017, only 25% of loyalty program members are satisfied with the level of personalization they get. Furthermore, according to a recent Accenture study, 41% of U.S. consumers have moved away from their preferred brands due to a lack of personalization and trust.” (source)

Why is customer trust eroding?

How Does AI-Based Personalization Work?

It’s useful to understand how AI-enabled personalization works. According to Rajat Narang and Abdurrehman Malekji, Absolutdata, here are the main steps:

The need for historical data.

Machine learning can be compared to how a child learns. Both begin to differentiate between right and wrong through instruction and prior knowledge. We add scenarios (historical data) into the machine and let it know what is correct. It must know why a customer decided to purchase a given item, etc. After, we’ll be asking it to make connections between historical data patterns and its current inputs. Decisions are fine-tuned using a feedback loop.

A crucial part of AI self-learning is the feedback loop, a process that provides continuous feedback on the decisions the system makes. The AI system needs to know if the historical decisions were correct or not, and it needs to be smart enough to tweak its own algorithm and provide more accurate results. It basically should self-learn to help marketing teams.

(source)

Diving Deep into Data

Heidi Unruh reminds us that “Once you have the broad categories sorted, we need to continue refining them into smaller segments, known as micro-segments. Accurate micro-segmentation is essential to create content that truly resonate with customers because it enables the company to get a clear picture of what the audience needs, what they value and how they behave. Advanced customer segmentation uses cross-channel behavioral insights and data from internal and external sources to discover and define audience segments, enabling you to deliver highly personalized marketing messages.” (source)

Craig Teich, Executive Vice President of Global Sales at Connexity, said “The more information a brand has on its customers, the more data it has to ‘pattern match’ similar individuals and identify new micro-audiences outside of its own database. In order to identify and target new customers, marketers can also leverage third-party data sources to identify consumers with similar attributes to their own best customers.” (source)

What is the difference between Personalization & Hyper-Personalization?

Priyam Jha, Content Marketer at Webengage said “Personalization is the incorporation of personal and transactional information like name, title, organization, purchase history etc. to your communication. Hyper-personalization goes one step further and utilizes behavioral and real-time data to create highly contextual communication that is relevant to the user.

Amazon is a great example of hyper-personalization. It has access to data points like Full name, Search Query, Average time spent on search, Past purchase history, Brand affinity, average spend amount, etc. Using this, they can create a profile and use that to craft a highly relevant email highlighting a blue Nike T-shirt (Blue = my previous search query + Nike = I have purchased Nike clothes in the past).” (source)

Compared to other E-Commerce brands, conversions from Amazon’s on-site recommendations are 60% higher.

This new knowledge of customers can be used to target through personalized incentives too. Indeed, Mammoth Resorts with IBM Watson delivered customized deals to potential vacationers based on their specific behaviors (e.g. promotional messaging delivered the day a customer’s restaurant pass is scanned, or a post-visit email with discounted rates on a return trip).

Gartner predicts that organizations that excel in personalization will outsell companies that don’t by 20%.

Attention has become the anchor for driving marketing effectiveness, and there’s no better way to grasp attention than through high quality and hyper-personalized content created with the help of an AI marketing assistant.

For more information:

Thanks for reading. If you enjoyed this article, feel free to hit that clap button 👏 to help others find it.