Artificial intelligence is used in many business systems that are part of a larger organisation, or for everyday apps that are meant to be fun and help, or support. Systems that use artificial intelligence are becoming more advanced and exciting. They have become a more widely used communication channel than social media. Thanks to them, many processes are more straightforward, faster and more effective, such as building and maintaining relationships in the target groups and their traits. This helps bots capture information quickly and optimise service costs. In the past, we restricted ourselves to traditional resources such as call centres and telemarketers, but now sales are bots. We’re introducing artificial intelligence in the form of increasingly efficient tools that communicate across websites, social media, and mobile applications. The direction of development seems clear, and soon a must-have of any successful company.
A marketing automation platform enables the automation of marketing activities by monitoring users and their behaviour on the website. Based on the collected data, comprehensive behavioural profiles are created, including the segmentation of contacts based on received data. These make it possible to develop purchasing preferences or interests of individual people and segments. These materials are then used to send personalised content in emails, to generate effective marketing campaigns, or to show personalised content on the website.
What influence does artificial intelligence have on marketing automation?
Artificial intelligence or machine learning is already being used by many of the world’s most famous companies. Surely you have unconsciously come across these many times. All recommended products that you see when visiting a website are the result of the implementation of machine learning technology.
The currently used marketing automation technology is based on the execution of commands that operate from defined algorithms. This simple mechanism adjusts the actions performed according to what is programmed manually at the beginning. Machine learning, i.e. artificial intelligence, is characterised by a completely different strategy. Similar to humans, their potential comes from experience, more precisely from information collected and analysed from the outside. Facebook, Spotify, Google Maps, or Uber are just a few of the many brands that have used this solution in their daily lives.
Artificial intelligence in marketing automation is used today, among other things, to create an advanced rating system: lead scoring, workflows, automation rules, and segmentation and well-defined campaign activity. The problem lies in a large amount of data that needs to be analysed.
In short, artificial intelligence and machine learning technology that analyses data about customers creates perfectly selected recommendations and suggests the best communication channel with the customer.
Example:
Intelligent Artificial Intelligence segmentation is based on behaviours, transactions, and other data being analysed. These data come from identified and anonymous people on the website and will monitor all the time. Based on recognisable behaviours, the system will automatically define segments. This allows you to design the site to respond to the needs of visitors automatically. This does not seem to be new to MAS. However, artificial intelligence is essential as this technology continues to evolve, allowing it to respond in real time or to personalise advanced segmentation through the most advanced algorithms and structures.
Conclusion:
At first glance, artificial intelligence seems to be used by marketing automation solutions, but let’s not forget that the algorithms of marketing automation systems are defined in advance by humans, and a completely different strategy characterises artificial intelligence. Similar to humans, the potential of artificial intelligence comes from experience, more precisely from information collected from outside and independently analysed.
In the future, we will publish articles with examples of implementation and types of artificial intelligence. If you have a question about the article or a suggestion for new topics, please contact us.
Author: Sarah-Johanna Hamera – MAC
