1. What is the average salary of a Database Marketing Manager?
The average annual salary of Database Marketing Manager is $118,717.
In case you are finding an easy salary calculator,
the average hourly pay of Database Marketing Manager is $57;
the average weekly pay of Database Marketing Manager is $2,283;
the average monthly pay of Database Marketing Manager is $9,893.
2. Where can a Database Marketing Manager earn the most?
A Database Marketing Manager's earning potential can vary widely depending on several factors, including location, industry, experience, education, and the specific employer.
According to the latest salary data by Salary.com, a Database Marketing Manager earns the most in San Jose, CA, where the annual salary of a Database Marketing Manager is $149,738.
3. What is the highest pay for Database Marketing Manager?
The highest pay for Database Marketing Manager is $138,746.
4. What is the lowest pay for Database Marketing Manager?
The lowest pay for Database Marketing Manager is $90,246.
5. What are the responsibilities of Database Marketing Manager?
Manages a staff of analysts responsible for the maintenance of the organization's marketing database. Develops strategy for targeted marketing campaigns and may be responsible for data extraction, list or lead generation, or evaluating effectiveness of marketing campaigns. Requires a bachelor's degree in area of specialty. Typically reports to a head of a unit/department. Manages subordinate staff in the day-to-day performance of their jobs. True first level manager. Ensures that project/department milestones/goals are met and adhering to approved budgets. Has full authority for personnel actions. Typically requires 5 years experience in the related area as an individual contributor. 1 - 3 years supervisory experience may be required. Extensive knowledge of the function and department processes.
6. What are the skills of Database Marketing Manager
Specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
1.)
Insight: Insight is the understanding cause and effect based on the identification of relationships and behaviors within a model, context, or scenario.
2.)
Python: Applying the concepts and algorithms of Python to design, develop and maintain software applications to comply with business requirements.
3.)
Data Analysis: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.