How to do better Customer-Centred Personalisation with AI

Personalization

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Personalization has always been a significant factor in marketing strategies. Very often, customer-tailored personalization is in our hands’ thanks to Artificial Intelligence.

If the customer’s attention plays a significant role in the marketing war, having hyper-personalized contents and suggestions is a great way to grasp it.

We live in a hyper-personalized world.

We crave to feel unique, and we love extreme personalization. We’re delighted when we receive a customized newsletter for our birthday. We open our Facebook page, and our feed fits our interests and our favourite groups perfectly. And guess what? You have to thank AI-based algorithms for it.

How comes that AI know us so well? How can it work on hyper-personalization, and how will it change marketing?

Let’s find out!

Why personalization is so important

Let’s face it. People love personalization, mainly since social media appeared in the picture, less or more a decade ago.

People became overwhelmed by any impersonal advertising, so it’ easy to feel agreeable when you make your customers feeling special.

In a customer-centric marketing strategy, we have to take in high consideration people preferences.

It’s a matter of fact. People love to feel important. They love it when their favourite shop sends them a birthday newsletter with a discount code. That’s why brands take care of them.

73% of consumers prefers to deal with a brand that uses their data to make the shopping experience more agreeable and personalized. The reason is that they thought that “data tracking makes it possible for retailers to present them with relevant and targeted content“.

Artificial Intelligence in marketing is making simple how a brand can deliver personalized content and customer experience.

Once, before the dawn of social media and AI, personalization was achieved by using a set of already existing data. However, this approach had several inconveniences.

Pieces of information were not complete and impossible to improve in real-time. Before AI-tools for target segmentation comes, you had to collect data and try to get out from trend and segments by hand. Your content creation process was static.

Your customer experience was motionless, as well. You didn’t have the chance of modifying them on the go. This led, of course, to entirely inaccurate updates your marketing strategy. Personalization is a tough task that requires time, energies and tons of data about our customer.
Is there a way to make it easier?

Let’s discover more about it, shall we?

Personalization And AI

Nowadays, things are quite dramatically changed.

Artificial Intelligence and Big Data came to the aid and personalization took a new, unbelievable path. To propose so perfectly customized advertising, brands need to know customers’ data. They usually gave them to the AI-based technology willingly, in a lot of ways – for example by subscribing to newsletter or websites. Or, even more often, people interact with AI daily.

A lot of people come home and ask Alexa to put on their favourite Spotify playlist and reorder the groceries on Amazon. After that, they may activate face recognition on their smartphones to scroll their Facebook feed until dinner time. Just before lunch, they decided to give a chance to that movie Netflix suggested – and, surprise, it’s exactly the one they wanted to see!

Alexa, Netflix, facial recognition, Amazon suggestions are all examples of uses of AI in daily life.

AI technology allows marketers to explore a whole new world of possibilities for personalizing messages. Simple personalization is currently out of fashion. We’re in the hyper-personalization era. This means that marketers are now using “behavioural and real-time data to create highly contextual communication that is relevant to the user”. The advantage of this approach is to create a tailored offer for each customer – of course, without having to do it manually.

We can do this in a lot of ways. For example, predictive personalization can use previous stored data and browsing history to predict which kind of content may be interesting for a customer. Predictions also help to tailor offers on every single prospect, knowing precisely what he or she wants or craves. It achieves an entirely personalized offer. For example, this is the kind of data that Netflix uses for its recommendations. Brands can use data for marketing personalization, providing different content or customer experience for each user.

different coloured shirts
Freepik

Examples And A Suggestion

A critical issue is to be careful when we handle our customer’s data.
For them, it’s important “to control how our data is being stored, modified, and exchanged between different parties.”
We have to be careful and draw a line to select only necessary pieces of information. The key is to be mindful and respectful about our customers and their timing, building a good relationship.

Asking the right kind of data brings, at least two significant advantages:

  • Less useless data to take care of privacy and maintenance. Remember! Every piece of data must be managed appropriately!
  • More trust from your prospects and customers. A customer is not so happy if we ask for too many details at first occasional approach. Give him value before annoying with the new personal data request.

Other companies are using Artificial Intelligence in their marketing strategy. They are taking advantage of AI to do better marketing personalization.

  • Artificial Intelligence to make better new products that fit the market. For example, Nutrigene company is using AI to drive personalized product development. The brand sends tailor-made liquid vitamins based on every customer’s lifestyle and DNA.
  • Artificial Intelligence to recommend content. Sesame Street, the popular TV show, released an AI-based vocabulary learning app. The app that can analyze the kid’s level and recommend personalized learning exercises, evolving the difficulty with the pace of his signs of progress.
  • Artificial Intelligence to help customer support. Levi’s has developed an AI-powered chatbot that helps customers find the perfect fit. It uses natural language processing and machine learning to find out exactly what each client is looking for in a pair of jeans by analyzing his lifestyle and preferences.

Personalization seems to be a big thing, and AI is helping a lot. Which application is your favourite?

Takeaways

  • Maybe in the future we will be accustomed to facial recognition and personal assistants that call us by our name.
  • Before the dawn of social media and AI, personalization used to be achieved by using a set of already existing data. Now, we can use algorithms to create a tailored offer for each customer.
  • We have to be respectful about our customers’ data, and we have to manage them carefully to build a trustworthy relationship.

Sources

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