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In the ongoing mission to deepen and strengthen customer relationships, many marketers are stepping away from the basic forms of segmentation and personalisation. In fact, 97% of industry leaders have expressed that the future of marketing lies heavily within machine learning-based automation entities. The ever increasing ability of these tools is what is making the personalisation of our marketing content much more scalable, efficient and automated, as well as being more valuable to the customer on the receiving side.
For the marketers that are at the top of their personalisation game, and are already utilising machine learning and artificial intelligence, 63% have noted an increase in conversion rates, with 61% also recording an improved overall customer experience.
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Machine learning is a subset of AI and involves algorithms that can leverage data to make decisions for itself, continually learn without human input and adjust actions based on that learning. Basically, the more data it has available, the smarter it can become.
This gives marketers the ability to have a tool that can effectively analyse the type of content, keywords and phrases that are of most interest to your target consumer. Using this knowledge, they can then create content that is individually personalised for each customer. In time, the machine will learn what is the most effective content for triggering a specific action or outcome that fulfils a particular goal. This should help shorten the entire sales cycle as marketers are getting their target audience to take the desired action sooner.
The way that most marketers have delivered personalised experiences in the past was through the manual segmentation of customers into groups based on basic demographic information such as their age, gender, location etc. While this approach works, it is very limited.
The problem is that the rules are written by humans based on what they believe to be true for each segment. But each person is unique, and could be at different points in their journey with your brand, or have differing interests and content preferences to the others within the segment the marketer put them in. On top of that, their intent from visit to visit can also change. A few segments and rules cannot take all of this information into account.
However, now, your user profiles can go way beyond this and can include a deeper insight into your customers based on their online browsing habits, social posts, device preferences, hobbies and interests, and much more! With machine learning, true personalisation – also called individualisation – can be done at scale. These tools can process huge amounts of data in microseconds and make the most relevant, up-to-date decisions based on this data, which in turn, helps you present the most relevant experience to each and every visitor. This deeper understanding of your audience is what’s going to grab their attention and help you develop that long-term, meaningful relationship between brand and customer.
In this day and age our customers actually expect this individualised experience. As consumers it’s so frustrating when brands, who should know us well, completely miss the mark. For example, when you view an item of clothing on a specific website it’s pretty likely that re-marketing has been set up to have that item follow you around in other places on the internet in an attempt to get you to follow through with the purchase. They might even be offering you free delivery or a nice little discount code and, inevitably, you give in. You click on that ad with the full intention of purchasing, but what do you know… it’s out of stock in your size.
This sort of experience is not going to look good in the eyes of your consumer and frankly, with the technology available to marketers today, this should not be happening.
According to Gartner, by 2020, 90% of brands will be practicing at least one form of this real-time personalisation by machines – and it is these organisations that will be outselling their competitors that do not by 30%.
When a friend or a family member suggests a recommendation for something you might like, be it a book or a restaurant, the chances are, you’ll take them at their word and give it a go! That’s because you trust that these people know you and are aware of your likes and dislikes.