Marketing has immensely changed over the last few decades to better target consumers through a digital market. According to research, 84% of marketing organizations are implementing or expanding AI and machine learning in 2018. It has greatly expanded our knowledge by being able to track real-time analytics of the many contributions to revenue growth. Machine learning is revolutionizing marketing by knowing what is driving more Marketing Qualified Leads (MQL) and Sales Qualified Leads (SQL). This intel better optimizing marketing campaigns and improving the company’s profitability.
While traditional methods may have been strained due to the digitalization of data, the benefit of machine learning will better value consumers along with overall business needs. Machine learning uses a type of algorithm to indicate patterns within the data to improve customer experience and learn which ones will become high-value in the future. For example, the e-commerce business for food and beverages has expanded into a large business that no one would have expected it to be years ago. PepsiCo’s Shyam Venuugopal (VP of Global Media and Consumer Data Strategy) said it best, “We are operating in an environment that is constantly changing.”
Customer journeys are constantly growing in complexity and spanning across multiple platforms and devices. With this, marketers have had to rethink their marketing strategies for reaching their target audiences. We live in a time period where there are infinite options for creating content and becoming more ambitious to capture what customers need and/or want. Machine learning is an asset to better anticipate and act on the problems. It’s taking content, marketing automation, lead scoring, personalization and sales predictions to a whole new level of precision and speed.
How does Machine Learning Help?
Overall, machine learning can help marketers in a several ways. One of the biggest challenges in marketing is how to personalize messages to individual prospects so that it resonates with them to feel a connection. These actions result in: increased customer loyalty, engagement and spending.
Without machine learning, it would be extremely difficult to compile and process the amount of data that comes from all platforms that is required to predict marketing offers and incentives for individual consumers. Some areas machine learning applications can help marketers are:
- Customer Segmentation – Successful customer segmentation is a major tool in every marketer’s toolbox. Machine learning customer segmentation models are effective at extracting homogeneous groups of customers similar behaviors and/ or preferences.
- Customer Churn Prediction – Discovering patterns in the data generated by customers who churned previously, churn prediction machine learning can accurately predict which customers are a high risk of churning. This allows marketers to engage in proactive churn prevention, which increases revenue.
- Customer Lifetime Value Forecasting – CRM machine learning systems are a productive way to predict the customer lifetime value (LTV) of existing customers, new and veteran. LTV is a valuable tool for dividing customers and measuring the worth of a business and forecast growth.
As stated by Louis Columbus, “58% of enterprises are tackling the most challenging marketing problems with AI and machine learning first, prioritizing personalized customer care, new product development.” These marketing areas have the highest benefit but are also the most complex. With the ability to perceive and understand the most successful marketing approach, machine learning relieves marketers of the heavy lifting associated with the massive amounts of data.
With machine learning in place at businesses, large and small, marketers will become accustomed to not only doing their work differently, but also doing different work. Marketing must be shifted to more strategic insight-based because of the amount of data processed on a daily basis. But, isn’t that the fun of marketing now? Being able to constantly experiment with different approaches for content and platforms. Machine learning along with AI have opened the doors for marketers to create a fun and interactive approach for consumers, both new and existing.