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In a Digital Marketing Analytics Course? The Advantages of Predictive Analytics

Predictive analytics help business professionals make better marketing decisions, which can result in increased revenue. With a growth rate of 23% per year, predictive analytics processes are being adopted by industries across the board. If you haven’t become acquainted with the benefits of predictive analytics, then you’ll want to start to familiarize yourself to implement these operations into your workflow when appropriate.

At Cumberland College, our Digital Marketing Analytics course prepares students to comfortably use Google Analytics, Google Search Console, Facebook Insights, and CRM reporting. With the skills to use each of these tools, plus practical application during class time, students learn how to effectively predict future trends based on data and analytics.

If you’re considering jumping into our Digital Marketing Analytics course, then below is everything you need to know about the advantages of predictive analytics.

Narrowing Down Your Audience for Segmentation

Targeting and segmenting your audience is a key component of successful marketing. Leveraging various behavioural and demographic markers, you can segment your leads and current customers to create new campaigns that are specifically tailored to your audience’s needs. 

Affinity analysis is a process you may use after your digital marketing analytics course to help segment your audience. This is a predictive process carried out by segmenting the audience based on their shared interests. Another option is response modelling, where you assess the data on how your audience responded to certain stimuli. Based on their response, you can predict the future behaviour of new and repeat customers. Getting an idea of what your audience wants, and how they are going to respond to your marketing, can progress your customers down the sales funnel.

digital marketing analytics course
After digital analytics courses, you’ll want to segment audiences based on data to predict trends

Predictive Lead Scoring for Digital Marketing Analytics Training

Lead scoring eliminates some of the run-around chases for customers who aren’t all that interested in your offers. Lead scoring is a form of predictive analytics that qualifies and prioritizes leads based on their interest, urgency, and authority to purchase. It consists of assigning scores, or numerical values, to measure where they are in the buyer’s journey. The higher the score, the more qualified they are for your offers and the more likely it is that they will result in a conversion.

Predictive analytics is determined by information that users may have provided you, previous purchases, how they interact with and respond to your stimuli, and more. With lead scoring, your team can give up on the low-scoring leads who are unlikely to ever pull the trigger on your offers, and spend more time nurturing high-scoring leads. 

digital analytics courses
Assessing and predicting data from users helps nurture the right leads

Decreasing Your Customer Churn Rate

When a customer stops doing business with you, they become part of the data that makes up your churn rate. Usually, businesses communicate the churn rate as a percentage of subscribers. With predictive analytics, you can use data markers from your current customer base to identify any red flags that may result in you losing a loyal customer. Once you identify some of these red flags and get feedback from lost customers, you can predict when other customers may start to feel the same way. Determining where your business is going wrong and how to solve the problem can help you proactively address your customers’ needs after digital marketing analytics training.

At Cumberland College, you’ll have many opportunities to physically create your own sets of goals, data points, campaigns, and reports, and track them as they perform. 

Do you want to enroll in a digital analytics course?

Contact Cumberland College for more information!

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