AI and Machine Learning

Digital Marketing - Study Notes:

Value of machine learning

Machine learning and AI are similar, but they are not the same thing. Machine learning is a branch of AI. Machine learning mimics human thinking whereas AI mimics human interactions and experiences.

Machine learning enables computers to grow and change when exposed to new data, without explicitly being programmed for this new data. In effect, it uses data to identify patterns, generate data-driven recommendations, and automate decisions, with minimal human intervention. Put simply, it learns and adapts as it takes in more data.

An example of this is the driverless car. The car uses machine learning to make predictive decisions based on key inputs that it detects from the environment around it. These key inputs come from a combination of sensor data, video data, audio data, and GPS data, etc. The machine learning functionality then aggregates this data to determine the best action to take for the car – such as turning a corner, for example.

Machine learning in digital marketing

Marketing strategists create hypotheses, test them, evaluate them, and analyze them. This work is labor-intensive and time-consuming, and sometimes the results are incorrect because the information gathered has already evolved. Machines, however, can analyze large datasets quickly and efficiently without human error.

Here are some areas where machine learning can be applied to digital marketing:

• Marketing campaign management: Machine learning enables you to analyze and use data to automate tasks, such as email marketing campaigns to drive customer transactions. It can also determine which content gets the most clickthroughs or engagement. This can help you create similar, or more tailored, content in a timely fashion.
• Campaign bidding: Machine learning can help you make more accurate predictions across your ad accounts. For example, it can show you how different bid amounts might impact conversions or conversion value. It can quickly stop showing low-performing ads and push high-performing ads, to ensure a budgetis being spent efficiently towards the goals you input.
• New customer acquisition: Machine learning can help you create persona-specific marketing strategies. You can also use data to create ‘lookalike’ personas. These are people who haven’t bought from you yet but have similar characteristics to your customers, which means they are more likely to convert than audiences with fewer similarities to your existing customers. With lookalike personas or the expanded targeting option in Google Ads, you can target potential new customers based on solid data points. Machine learning can also give you insights into the Buyer’s Journey, which can then be used to support customer retention efforts.

You may also be familiar with other non-marketing functions where machine learning is applied, such as automated services, online recommendations, and even fraud detection. As people come to expect more personalized, relevant, and assistive experiences, machine learning has become an invaluable tool, both in everyday life, and in digital marketing.

Further advances in machine learning that will assist you in driving performance from your digital strategies will be available in the near future. Bear in mind however, that not all machine learning or AI-powered tools are as effective as you might think. Be sure to test their functionality, and then decide if it’s worthwhile including them in your tech stack, or not.

Advantages of machine learning in digital marketing

What are the advantages of machine learning for digital marketing strategists?

Machine learning enables marketers to:

• Store a significant amount of data.
• Use inputs from unlimited sources.
• Process, analyze, and predict outcomes easily.
• Learn from past behaviors.

Machine learning enables marketers to significantly improve their decision-making. With the ever-increasing sophistication of machine learning algorithms for marketing, you can deliver hyper-personalized offers, content, products, and services to drive results.

Some machine learning tools are easy to use, some are built into existing platforms, and others are used as standalone tools. Depending on what you’re trying to achieve, take the time to investigate the kinds of machine-learning-powered tools that are most suited to your digital marketing strategy.