Using the Power of Data and Machine Learning to Reach New Audiences

As a marketer, you are in an industry that is continuously evolving. Nowadays, there are more social media platforms than ever before. This means that your brand has more opportunities to reach a new audience, as well as more brands to compare with.

On top of this, consumers understand tech more than ever and social media is impacting their behavior in a big way. They know that you are trying to reach out to them. However, the catch is that they will only tolerate marketing that is relevant to their needs or timely to their current position in a purchasing cycle. Sounds like a lot of work, doesn’t it? Well, a marketing campaign will only work if it is tailored to the right audience at the right time and on the right platform.

Given that there are numerous media channels and platforms to reach consumers. We have entered the stage where marketers are incapable of manually analyzing data, and tailoring the content to reach each of their different audiences. Not only has this become physically impossible to do without human error, but it is extremely time-consuming. And in such as fast-paced industry, every minute counts if you want to stay ahead of the competition.

So, what’s the answer?

How can you produce creative and engaging content to send to consumers without dedicating countless man hours on the grunt work? This is where you need a platform or a program that can conduct data analytics with added artificial intelligence and machine learning. Let’s break it down:

What is artificial intelligence?

Artificial intelligence (AI) refers to intelligence demonstrated by machines. It is a broader concept that depicts the idea of machines being able to carry out “smart” tasks. Netflix, Amazon, and Siri are just a few popular examples of AI being used today.

What is machine learning?

Machine learning is a current application of AI that provides systems with the ability to automatically learn and improve from experience without additional programming. It focuses on the development of algorithms that allow computer programs to access data and use it to learn for themselves.

If you want to drive engagement with new audiences across numerous platforms, AI and machine learning are the way to go. They tap into existing audience data, analyze it, and ensure a buildup of the latest market and brand insight – all in real time. Yet, the true beauty of AI and machine learning is in the performance. A program that uses AI and machine learning can automatically determine which marketing messages need to be directed to which audience. It can also determine which social or digital platform the marketing messages need to go through.

When applied to marketing, these transformative technologies detect patterns and trends in extremely large data sets, known as big data. This, in turn, allows you to identify consumer preferences, behavior, and current market conditions, all the while outreaching on a large scale.

What Do Big Data and Machine Learning Have in Store for the Future of Marketing?

They will greatly impact marketing. This is how:

  • Optimizing consumer needs and preferences

    In the early days of the internet, you did not need to worry about factors that could hurt your brand’s reputation or sales, such as negative online reviews. Now, with online accessibility, the consumer journey is different. To give you a clearer picture of this, consider the following: 55% of consumers do their research on social media platforms and over 60% of American adults are on social media 12 hours a week. Big data and machine learning can help to optimize consumer needs and preferences by figuring out when and how to target certain demographics. As algorithms evolve, we can expect more powerful insights into the consumer journey. 

A laptop monitor containing a code with an if function.
  • Automating customer service

    Automation is not new. Individuals can book a doctor’s appointment online, order their favorite meal via a mobile application, and much more. But now, thanks to machine learning, automating customer service is the next step in marketing.

    By predicting patterns in data, all of which are based on consumer inquiries and previous behaviors, machine learning may help to recommend services and sell services without prior training. Can you imagine the benefits of applying this technique to a sales-oriented business?

  • Improving lookalike marketing

    Lookalike audience are individuals who are likely to be interested in your brand because they display similar traits to those who are already interested. With machine learning algorithms, tracking conversions and re-designing marketing strategies is made possible. This will allow you to reach out to users who share similarities with your audience, ultimately automating audience targeting.

    In the long run, gathering insight from consumer data can be valuable for interest-based targeting and faster-lead targeting. If the technology is utilized appropriately, it can reduce resources, such as time and money, needed to target potential customers manually.

  • Enhancing predictive analytics

    Perhaps the most important benefit of using big data and machine learning is predictive analytics. Using predictive analytics to gain insight from data will allow you to determine consumer patterns and to make decisions based on them. Consider When you buy a product on Amazon, you receive a list of recommendations based on your latest purchase. This is predictive analytics – it uses machine learning algorithms to make these recommendations based on user behavior (such as buyer history on Amazon).

    If machine learning can predict user behavior, it may be able to predict how certain ads perform with associated consumer data. It may help make ads smarter and more profitable, thereby enhancing your brand’s reputation.

Unlocking New Opportunities by Building a Shared Knowledge Base

Machine learning analyzes trillions and trillions of search inquiries and activities across millions of websites. It helps to identify patterns when individuals are close to purchasing a product/service from different brands. It also targets new ads that will be more relevant and interesting to different audiences. By using the power of data and machine learning, you can gain better insights into consumer behavior. That is, you can better understand behavior shifts and purchase intent, allowing you to reach new audiences for your brand.