There is no denying the fact that technology has developed at a rapid pace over the past few years, and this is something that shows no signs of slowing down. At the moment, machine learning is playing a huge role. With that being said, below we are going to take a look at some of the different ways that machine learning is impacting how we go about targeting new potential customers. 

  1. Reinforcement learning for marketing decisions that are sequential – Some of the most difficult and complicated decisions we make are not single predictions. Rather, they are a number of different decisions that we make over a long period of time. Balancing long-term gains with short-term tradeoffs is a challenge for even the most intelligent of humans. This is where machine learning can come in. Use this alongside Google Analytics for the best results. Read up on how to add users in Google Analytics if your team are not on board yet.
  2. Superior reporting – Another way in which machine learning ables you to target new customers more effectively is because it provides enhanced reporting capabilities through automated data visualisation. After all, images speak louder than words. Not only is AI faster but it is more efficient when it comes to the transformation of data into visual insight.
  3. Branded object recognition – When it comes to AI and machine learning, there is no denying that computer vision is a field that is rapidly advancing at the moment. It lends itself to a broad scope of applications. Marketing teams will be able to utilise machine learning-powered computer vision so that products can be recognised and so that user insight can be extracted from unlabeled videos and images. This means that businesses will have the capacity to determine when their logos have appeared in content that has been user-generated. You can then calculate quickly and easily the media that has been earned by using video analysis. 
  4. Speech-To-Text (STT) and Text-To-Speech (TTS) to power searches that are voice-based – Voice-only and voice-enabled platforms have introduced a new paradigm and new possibilities when it comes to user engagement for our hardware and software interfaces. When you consider the fact that voice-based digital assistants are on the rise, such as Google Assistant and Amazon Echo, you understand that shopping is becoming more and more touch-free. This enhances the convenience associated with online shopping, which is what the Internet is all about. In order to future-proof your marketing, you are going to need to have a conversational AI strategy. 
  5. Customer experience automation and dialog systems for chatbots – Aside from the areas of improvement that have already been mentioned, another domain that machine learning has had a massive impact on is with regards to chatbots and bots. This area represents one of the most ubiquitous applications of machine learning. However, the vast majority of the marketing bots today use minimal machine learning and natural language processing. Instead, they are completely scripted. This can, in fact, causes frustration for the consumer because they know they are dealing with a bot instead of a consumer and then scripted responses can often offer nothing of any value. However, we are now going to see more sophisticated dialog systems being used, and this is definitely something that you should be able to look into.