Study Data Science for Digital Marketing and Master Your Organisation’s Churn Cycle

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Harness the power of data science to better predict customer churn and retention

As a marketing leader, you know how important it is to have a team that possesses cutting-edge skills and analysis capabilities. Making sure you and your business stay at the marketing forefront requires an eye for upcoming trends, and a careful allocation of resources toward ongoing professional development.

There are many benefits that data science capabilities can bring to a strong marketing team and the larger organisation that it supports. One of these benefits is that data science can provide a new level of insight into an organisation’s churn cycle, bringing about fresh possibilities for customer retention. Read on to find out more about the advantages this could bring to your workplace.

Why the Churn Cycle Should Influence Training for Digital Marketers

The specific units and activities measured by the churn cycle vary based on the type of business or clients your marketing team supports. However, all churn cycles can be reduced to the following concept: the churn cycle is the pattern or journey through which customers begin – and then stop – interacting with your business.

Essentially, customer churn is the opposite of customer retention. Marketing professionals who have a strong grasp of the customer churn cycle will be able to gain better insights into the characteristics of a product or brand that initially attracts customers, and what hurdles along the way prevent conversions or further purchases. This makes the churn cycle a critical point of knowledge and analysis for any marketing team.

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Understanding the churn cycle will allow your marketing team to anticipate customer behaviour

Data Science for Digital Marketing Can Help You Develop a Churn Model

When marketers attend data science short courses, they gain the tools, skills, and knowledge they need to build an informative churn model.  A churn model is just one of the many predictive models that can be generated by the use of data science, and takes the standard churn rate measurement further by mapping not only how often customer churn occurs, but where and why.

On Southampton Data Science Academy’s course, marketers learn how data science fundamentals can be used to help predict churn, particularly through machine learning techniques. A machine learning approach to developing a churn model is a great way to enable quick, short-term responses to customer actions.

For example, such a model could be used to determine which customers should be included in a retention email campaign. By acquiring skills in data science, your marketing team can learn to use their digital marketing tools and campaigns at optimal points in the churn cycle.

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Data science techniques like machine learning can help your team develop a powerful churn model

Your Team Can Learn Churn Scoring After Data Science Short Courses

Developing a successful churn model can also give digital marketers the ability to use churn scoring methods to better identify customers that are at a high risk of churn, as well as those who are likely to be loyal on a long-term basis.

Online training for digital marketers in data science provides the tools needed to identify common characteristics among customers that are most closely tied to churn rates. By systematically analysing the presence or absence of these characteristics, marketers can then assign a churn score that quantifies a customer’s churn risk based on information that, without data science, would have otherwise been too subjective to easily measure.

This knowledge can aid in customer segmentation efforts, and can in turn provide richer, more nuanced insights into the behaviour and motivations of customers – the most valuable type of information for the savvy digital marketer.

Do you want to gain control of your business’s churn cycle?

Contact the Southampton Data Science Academy to learn more about our data science for digital marketing training!

Topics: online training for digital marketers, data science for digital marketing training, data science short courses

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