Machine Learning Trends for 2018
When it comes to the tech industry, there’s nothing more exciting than the development of AI and machine learning. Year upon year, emerging technologies are helping to redefine the customer experience and enabling marketers to better connect with their customers. In 2018, machine learning looks set to grow into one of the most predominant forces in the tech world. Below we look at the top machine learning trends for the year ahead.
1. Image Recognition and Social Media
Anyone whose been paying attention to the world of digital marketing will have noticed that visual media such as images and videos have become some of the most effective tools in modern marketing. Thousands of marketing agencies are constantly trying to analyze the most effective images for driving customer engagement.
Over the course of next year, it looks like AI image recognition tools will begin to automate this process and break down massive libraries of virtual images. AI programs will be much more efficient than even the most expert analysts and will start to breakdown the way people respond to images on social media. Marketers would have much more data at their disposal as well as being spoon fed insights by machine learning tools. Though such technology is still in its infancy there remains massive potential.
2. Chatbots
Right now chatbots are evolving at a considerable rate. We’re going beyond rudimentary question and answer sequences into the world of natural language processing. Through NLP, chatbots can analyze and identify the meaning of words. This means that you can ask a chatbot questions and it will provide relevant and useful responses rather than the cookie cutter ones of yesteryear. In the past, asking a question would get you a reply limited to certain phrases or keywords.
3. Building Personalized Customer Journeys
As we move into 2018, more marketers are opting to cultivate personalized customer journeys. Platforms like Blueshift are making real headway in terms of making the customer experience unique. Whilst the platform used to use predictive scores for customer journeys to a point-in-time, now users are placed into a specific customer journey as soon as their score exceeds a set limit.
The AI places the customer according to their responses to site marketing, where journeys are triggered by a specific event or user behavior. This means users will be exposed to custom funnels and attribution models as the platform determines which part of the journey had the biggest impact. In other words machine learning will help to define what customer journey a user is looking for.
4. Conversational Interfaces
One of the most promising manifestations of machine learning is that of conversational interfaces. These depart from chat bots in that they are specialist customer service bots design to automate the customer service process. In 2018 we can expect to see more businesses attempt to build conversational bots that embody their voice and company values. What’s more, these bots can have the capacity to have thousands of conversations at once.
The customer service implications of such bots are far reaching both in terms of efficiency and customer service. As Golden Krishna suggests “the best interface is no interface” and many people are considering conversational interfaces to be the realization of that mode of thought. Conversational bots will take us further away from the narrow and regimented customer experiences that many experience today.
Machine Learning in 2018: The Tip of the Iceberg?
In many ways machine learning is standing on the edge of a revolution. Though digital marketing has grown exponentially in the last few years we’re yet to see machine learning reach it’s full potential. Ultimately we can only sit back and ponder over how widespread the effects will be. What is clear is that machine learning will make our ability to process and manage information much greater than ever before.
In the context of the customer experience, this translates to tailor made experiences compiled by perceptive machines and support run by well-informed conversational interfaces. The true potential of these developments is impossible to know, and we can only revel with excitement to find out just how deep the rabbit hole goes. In future, businesses who invest in smart machines are going to redefine technology’s place not just in our marketing, but our world as well.