Utilizing Machine Studying to Enhance Your Digital Advertising
Machine learning is about to transform the marketing sector. In many ways it has already started. According to Gartner, 30% of companies will use machine learning as part of their sales process by 2020.
Additionally, these companies use machine learning to differentiate themselves from the competition by tackling some of the toughest marketing challenges, such as: B. Personalization, Immediate Customer Support, and Big Data.
In other words, machine learning isn't just for computer scientists. Marketers should sit up and pay attention. Below, I've outlined five ways you can use machine learning to accelerate your digital marketing efforts.
What Is Machine learning?
Before we dive into marketing, let's take a second to figure out what artificial intelligence and machine learning are.
Artificial intelligence is simply any form of intelligence demonstrated by a machine instead of the natural intelligence of humans and animals. When most people think of artificial intelligence, they specifically think of computers that emulate some measure of human intelligence, such as a chess computer that I mentioned in the introduction.
Machine learning is a branch of artificial intelligence that enables systems to automatically find new and better solutions by learning from mistakes and experiences. The more data and experience a machine learning algorithm has, the better it will be in the future.
Machine learning systems can largely be divided into two subgroups: guided and unguided. Guided machine learning systems are primarily provided with data sets and solutions by humans. They learn what patterns to look for first and then better identify those patterns in the future.
Unsorted systems gain access to unsorted and diverse data sets and can decipher patterns independently and without human guidance. Undirected systems create an algorithm and then look for ways to improve it in the future.
Using Machine Learning to Improve Your Marketing
We know marketing teams don't want a lack of data. Marketers struggle to understand and then use all of the data that is available to them. Machine learning comes into play in this analysis.
The main reason for adding machine learning to your marketing stack is because large amounts of data make sense much faster and more effectively than humans.
In machine learning, data can be used to identify patterns and make predictions almost instantly. Marketers can then use these insights to streamline a large portion of their workflow, from running further tests and improving their website's user interface to personalizing the customer experience and automating customer loyalty.
The long and short of it is that machine learning can be used to improve just about any part of your digital marketing endeavors. Five of the most important options are explained below.
Analyze data sets
Regardless of how you use machine learning in your marketing efforts, the process likely starts with analyzing data sets.
For example, machine learning can be used to analyze and find user activity patterns on your website. Rather than digging through the data in your Google Analytics profile yourself, a machine learning algorithm can do the job in seconds, predict future user behavior and identify patterns that you can use to optimize your website.
Sure, humans are perfectly capable of analyzing data on their own, but you can't do it half as fast or accurately as AI-powered solutions.
Marketers can also use machine learning to better understand their customer base.
Take customer segmentation, for example. Splitting your audience into different groups can make your marketing efforts far more effective, but it is time consuming. On the other hand, a machine learning algorithm could automatically segment your customer base based on actions and behavior patterns that you cannot identify.
Create and optimize content
I don't need to reiterate the importance of content to your digital marketing endeavors. However, you may need to understand how machine learning can improve what you write and publish, and why using machine learning is critical in your content marketing strategy.
For starters, machine learning can help your articles rank higher in search engine results. It's one thing to be a great writer. It's another way to write in a way that Google likes so that you get rewarded in the SERPs. You need to make sure that you are using all of the relevant keywords, discussing every relevant topic, and covering all of your basics in general.
It is quite difficult to do this without smart content creation tools like Frase.io, which uses machine learning to compare your content to the top scores from Google and make sure you hit all the relevant points.
Second, machine learning algorithms can write content for you. Phrasee is an AI-powered copywriting tool that uses machine learning to create email subject lines and push notifications that the algorithm believes will generate the highest ROI.
You can even use AI to curate content for your customers. Curata provides machine learning content curation software that enables marketers to find and publish the most relevant and engaging content for their audience.
Personalization is important to consumers. Research from Accenture shows that 91% of consumers prefer brands that remember who they are and therefore make relevant offers and recommendations. In addition, more than half of consumers are only too happy to switch to a competitor if they don't get a personalized experience.
Here's the good news: machine learning enables you to deliver the most personal customer experience possible. You can use a machine learning algorithm that tracks user behavior at a detailed level, learns which products they like, and as a result creates a personalized homepage and recommendation list.
For example, Amazon uses AI algorithms that take into account users' purchase history, the items in their shopping cart, and their viewing habits to offer the product recommendations that are most likely to convert.
The same algorithm could also generate personalized offers for each customer and email them to consumers when they are most likely to buy.
Improve Marketing automation
Better personalization is one way machine learning can transform your brand's customer loyalty. However, this is not the only option. AI and machine learning can also be used to better automate your marketing efforts, thereby significantly improving customer loyalty.
Suppose you automatically send an email to customers when they sign up for your newsletter or when they leave their shopping cart. While most brands send a generic email, machine learning companies can customize content and offers based on the consumer's browsing history. If they look at your brand's selection of dog toys before signing up for your newsletter, a relevant chew toy listing would increase the chances of them getting back to your brand.
For SaaS brands, AI-powered marketing automation tools can analyze much larger and diverse sets of data to improve segment leads. This allows sales reps to prioritize the leads that are much more likely to convert.
Marketing automation is incredibly powerful. According to Invesp, marketing automation results in an increase in sales productivity of over 14% and a reduction in marketing effort by over 12%.
It's entirely possible to do this without machine learning, but AI makes your automation efforts much more personal and powerful.
Chatbots are a powerful customer service tool. Eight out of ten consumers who have looked at them report a positive experience. If you run an online business, these are far from important.
With chatbots, you don't have to have a human on hand to respond to consumers. Instead, machine learning chatbots can automatically answer customer queries with an alarmingly high level of accuracy. This is because your chatbot learns from your website content and conversations with consumers in order to keep improving the answers.
Since the chatbot is constantly learning and improving itself, it offers an even better customer experience with more conversations. You might want your chatbot to pass an incredibly complicated query to a human first, but soon the bot will become so effective that no human intervention is required. After all, you have a chatbot smart enough to sell the consumer, not just answer their questions.
Consumers are also unlikely to be able to tell that they are talking to a robot. Some chatbots, like IntelliTicks, use a different branch of AI, Natural Language Processing (NLP), to have human-level conversations with customers.
In addition, data collected by AI-assisted chatbots can be analyzed by another machine learning algorithm to provide insights that marketers can use to optimize their future endeavors.
What is the future of machine learning?
It's fast in the world of machine learning. Expect advances in marketing AI to come quickly.
For example, improved unattended machine learning algorithms are currently being developed. These algorithms don't require human input to begin with, making them much easier and faster for marketers to implement.
Personalization is also becoming more powerful. Machine learning algorithms will be better able to recognize what consumers want for you, but the way in which they can be integrated into online stores will also improve. In a nutshell, marketers will be able to customize every part of their sites for individual users, much like the way social media schedules are personalized for each user.
Finally, expect great advances in mobile machine learning. AI-powered digital assistants are becoming a more important part of our lives and marketers need to develop strategies to cope with it. Mobile applications can also incorporate machine learning capabilities in the same way websites do now.
However, don't let yourself get overwhelmed. Before you worry about the future, work your way through the suggestions I made above. You are then ready for whatever happens in the future.
It's clear: machine learning can transform your digital marketing efforts.
However, don't plunge into the world of machine learning. Introducing solutions without first understanding how the technology works and what role it plays in your company can usually do more harm than good.
Machine learning is powerful, but it's not a silver bullet. However, take one solution at a time and you will be fine.
Continue your education by reading my articles on the role of AI in SEO and AI-powered digital assistants.
Which machine learning strategy will you implement first?