A Complete Guide to Machine Learning in Marketing

What is machine learning?

Machine learning falls under the umbrella of artificial intelligence. Essentially, machine learning describes systems and software applications that are designed to “learn” based on analyzing data sets.

Or, in other words, machine learning consists of technology that receives input, identifies patterns, and independently adapts to new data in order to form solutions and solve problems.

This is a high-level definition of machine learning. In practice, there is a vast array of machine learning technologies that exist, many of them designed for highly specialized purposes. Machine learning is a concept that can be applied to virtually every industry you can think of, from healthcare to retail to shipping logistics to marketing.

Machine learning in marketing tends to involve software programs and other technologies that allow marketers to quickly analyze and extract valuable insights from large data sets. Machine learning software can also help automate many different processes, streamlining certain marketing tasks and saving marketers precious time and energy.

Many repetitive, mundane tasks that marketers would typically have to do themselves—such as combing through analytics and reports, optimizing content, and segmenting audiences—can be achieved more quickly and efficiently with machine learning.

How has machine learning impacted the way businesses operate?

While machine learning is a relatively new technology, it is quickly evolving and changing the ways in which many businesses operate. This is in large part because so many businesses rely on large and often complex sets of data to make decisions and create short- and long-term strategies. Machine learning models can help businesses organize and manage their data and—perhaps even more importantly—interpret the raw data in order to produce valuable insights.

In this day and age, machine learning can also help your business remain competitive in a crowded industry. Being able to collect and leverage data related to your customers, your business, and your industry can provide you with a competitive edge.

By combining accurate data with sophisticated machine learning technology, you can stay relevant in an era where the strategies of industry leaders are often dictated by data and algorithms.

Machine learning has had a particularly large impact on the digital marketing industry, which is constantly adopting new technologies and innovative methods to more effectively reach customers and build campaigns.

When used properly, machine learning models can prove extremely valuable to marketers and business owners. By leveraging machine learning algorithms to increase marketing automation and optimize marketing campaigns, you can actually do less work while increasing your bottom line.

In the next section, we go into even more detail about how machine learning algorithms can be used to take your marketing efforts to the next level.

How can machine learning be used in marketing?

Machine learning has many potential applications when it comes to marketing. Whether you’re trying to boost customer engagement, optimize marketing campaigns, or provide better customer service, there are ways for machine learning to help you achieve your goals.

So how, exactly, can machine learning be used in marketing? Below, we touch on five key areas where machine learning can help your marketing efforts and improve your customer experience.

Customer segmentation

Customer segmentation describes the process of breaking your customers up into different groups based on common characteristics.

By grouping customers together based on specific buying characteristics, you can more precisely target these groups and personalize your marketing campaigns. For instance, you might segment customers based on factors such as age, income level, geographic location, education level, purchasing habits, and so on.

With machine learning software, you can automate the customer segmentation process, making it more accurate and efficient. This is crucial for a few reasons.

First of all, large companies with vast amounts of customer data will likely find it tedious, time-consuming, and difficult to manually sort through data sets and segment customers. In addition to being an ineffective use of time, manually creating customer segments tends to be much more error-prone than using machine learning software.

Additionally, machine learning algorithms can help you identify patterns and segments that you never noticed before. With the right machine learning model, you can engage in hyper-segmentation, which allows you to break down broad customer segments into even smaller, more specific segments.

This allows you to create highly relevant and personalized content for your audience, which in turn can contribute to better customer relationships and more effective marketing campaigns.

Analytics

As digital marketing software becomes more sophisticated, brands now have more data at their disposal than ever before.

In general, this is a good thing—with more data on hand, you can better understand your customers, your competition, and your industry at large. However, collecting large amounts of data can also lead to problems.

When dealing with huge amounts of data points, one of the main problems is that the data becomes difficult to manage and analyze. A large data set can prove to be overwhelming or unmanageable for any human being. Yet, a machine learning program can easily process and organize massive amounts of data in a short amount of time.

Whether you’re parsing through sales data or engaging in reputation management on the web, machine learning can help expedite tasks that may otherwise take hours or even days to complete. Additionally, machine learning models can identify complex patterns that would be hard for a human to recognize and even perform predictive analytics in order to predict probable outcomes.

Optimizing marketing campaigns

Using machine learning technologies, you can optimize marketing campaigns by making data-driven decisions. While in the past, marketers might launch a campaign with blind hope that it proves successful, this is no longer the case. Modern digital marketing methods leverage data so that you can reach the right customers at the right time, and get the most bang for your buck.

When working with a limited campaign budget, you want to get the highest return on investment (ROI) that you can. Machine learning models can help point you in the right direction by using existing data to show you which marketing channels might best be utilized to achieve your goals.

Machine learning software can even automate marketing campaigns for you, thereby saving you time and money. For instance, machine learning can help when running digital ad campaigns by automatically targeting relevant audiences and tailoring content to suit the goals of your particular campaign.

Customer service

If you’ve had a customer service interaction recently, you may have engaged with machine learning technology yourself. That’s because so many brands are now using machine learning models to create automated chatbots and facilitate positive customer service experiences.

Providing excellent customer service is important for virtually any business. This is because excellent customer service typically leads to high customer satisfaction, which in turn can lead to a high customer retention rate. Essentially, when you make your customers happy and quickly resolve their problems, this leads to happier customers who are more likely to make future purchases with your company.

Machine learning can help improve customer service by enabling you to create chatbots and digital assistants that can automatically address customer needs. You can train machine-learning chatbots to use natural language processing and handle a wide variety of customer issues, from shipping concerns to website navigation.

While chatbots may not be suited to handle every customer service task, they can be a helpful asset when customers want to ask a quick question or troubleshoot a common problem. Programming chatbots and virtual assistants can also free up more time for your customer service team, allowing them to provide higher quality service, quickly address customer issues, and avoid burnout.

Forecasting

When running a business, forecasting can often be one of the most complex and painstaking tasks you have to deal with. Whether you’re forecasting demand or calculating customer lifetime value (CLV), it can be difficult to come up with accurate figures when you’re dealing with large data sets and shifting market conditions.

Forecasting is especially important because erroneous figures can lead to real-world problems. For instance, demand forecasting has a direct impact on both pricing and supply.

Incorrectly forecasting demand can lead to you having a shortage, an excess of inventory, or prices that undercut your potential profits. Using machine learning tools, you can quickly identify patterns in data and more accurately forecast future events.

In addition to helping you forecast demand, machine learning models can help you forecast consumer purchases, customer lifetime value, customer retention rates, churn rates, and a number of other business metrics. With accurate business forecasts, you can better understand market conditions and strategically position yourself in your industry.

How can using machine learning in marketing benefit your business?

Through the use of machine learning solutions, you can benefit your business in more ways than one. Both basic and advanced machine learning models present opportunities for you to bolster your marketing campaigns, improve customer experience, save time and money, and make more data-driven decisions.

Curious about how machine learning can help your business? Below, we list four ways in which machine learning can help your company’s marketing efforts.

Lower costs

Given the fact that machine learning solutions are so sophisticated and capable of so much, you might assume they are expensive—however, this is not the case. In fact, these days, machine learning tools are often built into existing marketing software.

For instance, you can use Mailchimp’s Content Optimizer to build better email marketing campaigns with the help of artificial intelligence. Or you can use our dynamic content tool to automatically create more personalized marketing emails that resonate with your audience.

On top of being surprisingly affordable, machine learning tools can cut down on costs in other areas as well. You can save money by automating manual processes that may have otherwise taken hours and use accurate insights to make business decisions that lower costs for your organization.

Higher-quality data analysis

Perhaps one of the best features that machine learning has to offer is its ability to quickly and accurately analyze large sets of data. While it’s possible to conduct data analysis manually, this causes several problems.

First of all, manually conducting data analysis on a large scale can be extremely time-consuming. A job that a machine learning model can complete in seconds or minutes may take human beings hours or days.

Manual data analysis is also more prone to error than data analysis conducted by machine learning tools. Machine learning programs can quickly process large batches of information and highlight patterns that would often be unrecognizable to the human eye.

With high-quality data analysis, you can create highly specialized customer segments, accurately track campaign performance, and gain key insights that can help guide business decisions moving forward.

Automation of processes

You can save your team time, money, and energy by leveraging automation in your business and marketing processes. Automation can be a great tool to streamline time-consuming, repetitive tasks. Whether you’re targeting specific audiences or building out the customer journey, automation can help you more effectively engage with customers while saving you time.

Automation facilitated by machine learning can prove useful in several aspects of your business.

For instance, you can use automation to quickly respond to customer inquiries and improve customer service. Machine learning also allows you to automate different parts of your marketing campaigns. With Mailchimp, you can set up automation to send abandoned cart emails, set up retargeting campaigns, collect customer feedback, and much more.

Customer satisfaction

Customer satisfaction measures how well you satisfy customer expectations and keep consumers happy. Virtually every business owner strives to maximize customer satisfaction since satisfied customers tend to be more engaged, loyal, and likely to make purchases in the future.

By incorporating machine learning tools into your business and customer service processes, you can increase customer satisfaction and establish a loyal customer base for your brand. That’s because machine learning enables you to build chatbots that quickly address customer problems and concerns.

Additionally, by enabling automation and using data to optimize the customer journey, you can increase the number of positive interactions that consumers have with your brand.

Implement machine learning models in your business operations

Machine learning presents marketers and business owners with a number of opportunities to optimize digital marketing campaigns and improve business processes. Using machine learning, you can more effectively analyze data, improve the customer experience, and automate all sorts of tasks. Overall, this can help you better serve your customers while improving your bottom line.

Mailchimp’s all-in-one marketing platform incorporates machine learning and other innovative technologies to help your business run as smoothly as possible. From AI design features to smart recommendations, Mailchimp’s software can help you create better content and run data-driven marketing campaigns that generate results.