Hello, I’m Mette.
Data Analyst
Mette is a data analyst who loves to translate data into insights, that can be used to make datadriven decisions
Contact Mette
Mette is a data analyst who loves to translate data into insights, that can be used to make datadriven decisions
Contact Mette
I love helping businesses with data analysis. My passion is diving into data and extracting valuable insights. When I am not analyzing data or working on projects, I enjoy spending time with family and friends.
My area of focus is applying data analysis to improve business processes. I create value for companies by identifying key metrics and providing actionable recommendations. I enjoy learning, collaborating with stakeholders, and making data-driven decisions to drive success.
About MeIn this project I focus on predicting the number of viewers that will attend the VFF homegames. Various of variables are taken in consideration to build af reliable model. The case is based on publicly available data and the CRISP-DM theory.
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In this churn analysis project, we predict customer departures using transaction and interaction data. Insights inform targeted retention strategies, enhancing marketing and service. This enhances operations and deepens customer understanding.
View CaseIn this project I am focusing on evaluating local e-mail marketing services i order to determin if they meet the standards of the international companies. Articles are in Danish.
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In this project I focus on developing rules based on a transactions dataset showing th combinations of grcoseries purchased together. This can reveal trends on what items are frequently combined. These insights has business values and can optimize several departments, for example marketin and inventory.
View CaseThis projekt focuses on forecasting unemployment rates, utilizing advanced statistical models and machine learning techniques to predict labor market trends. By analyzing historical data and economic indicators, I provide accurate and reliable forecasts that can help businesses and policymakers understand and respond to changes in employment.
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Understanding customer behavior is key to optimizing marketing strategies and improving retention. This project applies unsupervised machine learning (K-Means clustering) to segment customers based on purchasing patterns, identifying distinct groups such as high-value buyers, frequent shoppers, and at-risk customers. By leveraging data-driven insights, businesses can personalize engagement, enhance customer loyalty, and maximize revenue.
View CaseYears of expirience in datadriven Customer Service and Hospitality Management. I am ready to translate data into insights and help you make the rights decisions.No more guessin, the data will tell you all you need to know
Linkedin Download My ResumeI highly recommend Mette as a valuable addition to any team or project. Mette consistently demonstrates a strong work ethic, exceptional attention to detail, and a willingness to go above and beyond to meet objectives. Her collaborative nature and excellent communication skills make her an exceptional team player. Mette has a proven track record of delivering high-quality results and is always eager to take on new challenges. Therefore I wholeheartedly recommend her and am confident that she will make a significant and positive impact wherever she chooses to apply her skills and expertise. Her professionalism, dedication, and remarkable abilities make her an invaluable asset to any team or organization.
Mette is reliable, time efficient and a competent customer service agent. With her empathy and her willingness to always do her absolute best in every situation, no matter if it's towards colleguages or customers, I would definitely recommend to work with Mette!
As the founder of Date for Good, I had the pleasure of working closely with Mette. Mette worked on data-driven business development, implemented new systems, and conducted research on topics that contributed to our strategic decisions. Additionally, she managed our social media channels, created engaging content, and handled user inquiries with great professionalism. With a proactive approach to problem-solving, Mette continuously identified development opportunities, worked systematically, and documented all her work. A concrete example of her effective contributions was the implementation of our ticketing system for managing user inquiries, which significantly streamlined our support processes. Furthermore, her churn analysis was crucial in understanding and predicting user behavior, as she identified key variables. I can warmly recommend Mette to any organization in need of a sharp and dedicated employee with a strong interest and talent for data and business development.
