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6 Ideals of a Customer Analytics Job Seeker
6 Ideals of a Customer Analytics Job Seeker

6 Ideals of a Customer Analytics Job Seeker

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Key takeaways

  • Organisations investing in personalised marketing are likely to significantly outperform those that do not.
  • Domain knowledge is crucial for addressing specific customer analytics challenges effectively.
  • Strong analytical skills, including statistical understanding and machine learning familiarity, are essential for customer analytics roles.
  • Proficiency in tools like R, SQL, and Tableau is vital for effective data analysis and presentation.
  • The demand for customer analytics professionals is expected to rise as companies become more data-driven.
5 min
Organizations that have fully invested in all types of personalization will outsell companies that have not by 20% according to Gartner by 2018 (Customer Analytics for Marketing, 26 May 2015). This means companies will dramatically increase investments for driving personalization. This is only possible by becoming a data-driven and analytical enterprise. It will also mean increased demand for Customer Analytics professionals. Here are 6 ideals of what such organizations are looking for when hiring Customer Analytics professionals:

1) Domain knowledge

Say the problem is “increasing customer base”, customer analytics can help identify the most probable customers. However, if the company has a problem of customers leaving in 3 months, the overall objective of increasing customer base will fail. So domain knowledge is needed to make Customer Analytics projects successful.

2) Analytical knowledge    

Deep data analysis can be carried using statistics and machine learning. Hence a basic statistical knowledge about distributions, hypothesis testing, central limit theorem and assumptions applied, knowledge of probability topics is a must. In addition, programming knowledge of machine learning algorithms like random forest, ensemble methods are needed.

3) Tool knowledge

You have to be familiar with a statistical programming language like R. In addition, database querying language like SQL is also important. Visualization tools like Tableau are needed to present information is a visually appealing manner. These are the basic set of tools you will need.

4) Learner

I have noticed most clients need lots of help with problem detailing, understanding how their data can be used to solve their problems. Therefore, it is important to have an open mind and explore new grounds. This is manifested in people who never stop learning and find new approaches to suggest to clients.

5) Problem solver

The basis of this domain is solving business problems using data. Hence, a keen observation and ability to reflect help connect the dots. Developing a systematic and objective approach will help in finding solutions to several types of business problems.

6) Story Teller

Business people need to understand insights coming out of data and make strategic decisions. Therefore, it is important to express ideas in a quality way. What better way to share ideas and insights than story telling? People can immediately grasp a complex idea when it is narrated in a story form and also take decisions based on them. This is an art but can make one very effective in the field if mastered.   Don’t worry if you don’t have all these qualities. Through perseverance, it is possible to train and develop these qualities. What are you waiting for?
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