Netflix Churn Analysis Dashboard -- 2

@glanegonsalves

Hey there, I can help analyze your Netflix user dataset to identify the strongest behavioural drivers of customer churn using R and Power BI. The analysis can cover watch-time behaviour patterns, session duration, genre preferences, subscription tiers, seasonal trends, and other engagement indicators through exploratory analysis, statistical modelling, and churn prediction techniques. I can also build a clean interactive Power BI dashboard with dynamic filters and structured DAX measures so stakeholders can easily explore churn patterns without coding knowledge. Deliverables can include visual insights, model evaluation metrics (accuracy, precision, recall), reproducible scripts, and a concise recommendation memo highlighting both quick retention wins and long-term engagement strategies backed by the data.

@DevDataAnalyst

Churn analysis on streaming behaviour data is exactly the kind of problem I enjoy — there's almost always a pattern hiding in watch-time drop-offs that a well-structured Python pipeline can surface cleanly. I'll run the full exploratory analysis in Python, covering daily watch totals, week-on-week shifts, and seasonal patterns, then correlate those against session duration, genre preferences, and subscription tier to identify the strongest churn signals. Visuals will be clear and annotated so a non-technical stakeholder can follow the logic without reading the code. On the modelling side I'll build a baseline classifier — logistic regression or gradient boosting depending on what the data supports — and report accuracy, precision, and recall honestly. No inflated numbers, just a reproducible benchmark you can improve on. The Power BI dashboard will sit on top of the cleaned output with DAX measures behind every card, sliceable by genre, subscription type, date range, and churn status. Append new data in the same schema and everything refreshes with one click — no manual intervention needed. I'll also deliver a short recommendation memo calling out quick retention wins and longer-term ideas the data actually supports, not generic advice. Everything will be packaged so a stakeholder without coding knowledge can navigate and refresh the report independently.

@nrajuu07

I'm a data analyst experienced in customer behavior analysis and churn prediction. I'll explore your Netflix user dataset across three dimensions — daily watch-time totals, week-to-week patterns, and seasonal trends — correlating them with session duration, content genres, subscription tier, and other meaningful signals to surface the strongest churn predictors. Deliverables include a concise exploratory analysis with clear visualizations, an interactive Power BI dashboard filterable by genre, subscription type, date range, and churn status with automated DAX measures updating as new data arrives, and a practical recommendation memo highlighting quick-win retention ideas backed by data. Optional churn prediction model included with accuracy, precision, and recall metrics. All packaged for one-click stakeholder navigation without coding knowledge required. Ready to start immediately.

@devanshkhandekar

Hi,I am a seasoned Applied ML Engineer(6+ yoe) & I can help analyse your Netflix user dataset to identify the strongest behavioural drivers of churn & convert the findings into an interactive Power BI dashboard with refreshable visuals,DAX measures,& a practical retention memo. Proposed Approach: -Data & Feature Engineering:Analyze watch-time trends,genre preferences,& engagement drops to build predictive churn features (inactive days,reduced session length) -Automated Dashboarding:Develop a scalable,refreshable Power BI dashboard featuring dynamic slicers for dates,subscription tiers,& churn status. -Predictive Modeling:Train a baseline churn classification model (XGBoost/Random Forest/Logistic Regression),delivering standard metrics (Precision,Recall) & SHAP-based feature importance. Relevant Experience: -Customer Analytics & Segmentation:Transformed raw behavioral data to identify high-value cohorts,track engagement patterns,& flag high-risk churn groups. -BI & Operational Reporting:Engineered stakeholder-ready dashboards focused on period-over-period KPIs,cohort summaries,& actionable visual insights. -Machine Learning Pipelines:Built end-to-end classification workflows,successfully translating complex feature importance data into plain-English business recommendations. -Technical Communication:Authored clear methodologies,limitations,& actionable insights tailored for both academic reports & non-technical business teams.

@Srashtasoft

Hi there, I have read your project requirements. You need a comprehensive churn analysis on your Netflix user dataset to identify the strongest behavioural drivers of subscriber churn, supported by exploratory data analysis, predictive modelling, interactive Power BI dashboards, automated reporting, and actionable retention recommendations. We can analyse watch-time behaviour patterns, session duration trends, content preferences, subscription tiers, and engagement metrics to uncover churn indicators. The project will include data cleaning validation, statistical analysis, churn prediction modelling, compelling visualisations, Power BI dashboard development with dynamic DAX measures, and a stakeholder-friendly solution that automatically refreshes when new data is added. A few questions before we proceed: ============================= Approximately how many records and features are included in the dataset? Is churn already labelled in the data, or will definitions of churn need to be derived from user activity patterns? Do you have a preferred churn modelling approach (Logistic Regression, Random Forest, XGBoost, etc.), or should we determine the best-performing model? Will the final Power BI dashboard be deployed locally, on Power BI Service, or within your organisation's workspace? Best Regards, Srashtasoft Team

@subaigfalcon

Hi, I’d be happy to help with your Netflix churn analysis project. As a Power BI and data analytics specialist, I can help you find the main reasons why Netflix users are leaving and turn the data into clear insights. I will analyze watch time trends, viewing behavior, genres, subscription plans, and other important factors that may affect churn. Based on the findings, I’ll build an interactive Power BI dashboard with clean DAX measures and easy to use filters. I can also create a churn prediction model, share its performance metrics, and provide practical recommendations to help improve customer retention. The dashboard will be fully refreshable, so new data can be added without rebuilding the report. My goal is to deliver a solution that is simple to use and easy for stakeholders to understand. Upon being awarded, I will start the project immediately at a very competitive price, ensuring prompt completion. I look forward to discussing the timeline and next steps. Thank you.

@noreenraheel

Hi, I understand that your goal is to identify the key drivers of Netflix customer churn and translate those insights into actionable retention strategies through analysis, visualization, and an interactive Power BI dashboard. As a Data Analyst with experience in Python, SQL, Power BI, DAX, and predictive analytics, I can perform a comprehensive exploratory analysis of watch-time behavior, session duration, content preferences, subscription tiers, and other relevant factors to uncover the strongest predictors of churn. Deliverables will include: ✔ Exploratory Data Analysis with clear insights and visualizations ✔ Churn prediction model with accuracy, precision, and recall metrics ✔ Interactive Power BI dashboard with dynamic filters for genre, subscription type, date range, and churn status ✔ Well-documented DAX measures and data model ✔ Automated refresh-ready setup that supports new data appended in the same schema ✔ Executive recommendation report with short-term and long-term retention strategies I have worked on data cleaning, EDA, dashboard development, and machine learning projects, ensuring that stakeholders can easily refresh and use reports without technical knowledge. I would be happy to discuss the dataset, timeline, and expected outcomes. Best Regards, Noreen Sajjad Data Analyst | Power BI | Python | SQL

@gunjan1711

- I have hands-on experience analyzing customer and sales datasets using Python, SQL, Power BI, and statistical techniques to uncover actionable business insights. - I can perform exploratory analysis on watch-time behavior, session duration, content preferences, subscription tiers, and engagement trends to identify the strongest drivers of churn. - My approach includes data validation, feature analysis, correlation studies, churn segmentation, and clear visual storytelling to help stakeholders understand customer behavior. - I have experience building interactive Power BI dashboards with DAX measures, KPI cards, slicers, trend analysis, and automated refresh workflows. - In a recent project, I developed a PHP API, integrated database data into Power BI, and created automated real-time dashboards for business reporting. - I can build a baseline churn prediction model and provide key performance metrics such as accuracy, precision, and recall along with clear interpretation of the results. - The dashboard will allow users to filter by genre, subscription type, date range, and churn status while remaining easy to refresh and maintain. - I will also provide a concise recommendation memo highlighting retention opportunities and practical actions supported by the analysis. Reference work is available in my profile.

@ADOkg

I am an experienced data analyst with a strong focus on churn prediction and business intelligence. I have successfully built automated, interactive dashboards and predictive models that translate raw behavioral signals into actionable retention strategies. My Approach: Behavioral Analysis: Using Python (Pandas/Scikit-Learn), I will conduct a multi-dimensional analysis of watch-time patterns—including daily, weekly, and seasonal shifts—to correlate session duration and genre affinity with churn. Predictive Modeling: I will develop a baseline classification model to identify high-risk subscribers, evaluating performance through accuracy, precision, and recall to ensure the signals are reliable. Retention Memo: I will synthesize these findings into a practical strategy document, offering "quick wins" (e.g., targeted engagement triggers) and long-term retention initiatives backed by your data. Why Choose Me: I specialize in building end-to-end data products—from the initial Python/SQL cleaning and feature engineering to the final, intuitive dashboard. My work is designed for business stakeholders who need to make high-impact decisions based on clear, visual insights. I am ready to start immediately. Could you please share the dataset schema or a sample extract so I can begin evaluating the behavioral predictors?

@blackmanex

I specialize in turning customer and behavioral data into clear, decision-ready insights using Python and Power BI. Your focus on churn analysis is exactly the kind of problem I enjoy working on, especially where watch-time patterns, engagement trends, and subscription behavior need to be connected into a clear story. I will explore churn drivers across daily usage, weekly shifts, and seasonal patterns, and link them to session duration, content preferences, and subscription tiers. The output will include a clean exploratory analysis, visual insights, and an interactive Power BI dashboard with dynamic filters and DAX measures so your team can independently explore churn behavior. I also ensure all dashboards are fully refreshable and structured for non-technical stakeholders, with a short recommendation report highlighting actionable retention strategies. I am ready to start immediately and can deliver a clear first version quickly for feedback before final refinement.

@rakhshanz3

With nearly two decades working in the IT industry and a background in AI and Machine Learning, I am uniquely skilled to tackle your Netflix Churn Analysis project. My background as a lecturer has given me a unique perspective on problem-solving, teaching me how to efficiently process complex datasets to extract valuable insights. I have used both Python and SQL for large-scale data handling and analysis, guaranteeing that I can provide you with the most exhaustive understanding of your data. In my previous role as CTO, I built comprehensive data-driven analytics platforms similar to the one you require for your project. These platforms housed powerful statistical algorithms that anticipated upcoming trends and provided actionable insights. This is exactly what I’ll bring to your table - a concise exploratory analysis with clear explanatory visuals that highlight the strongest predictors of churn. Utilizing Power BI, I‘ll build an interactive dashboard to help drive meaningful discussions around genres, subscription tiers, dates, and term retention. Moreover, your acceptance criteria matches perfectly with my technical skills. I can ensure all the figures in the dashboard will update automatically when new data is appended for seamless reporting. You will have a stable churn prediction model with reasonable baseline performance - I’ll include accuracy, precision, and recall metrics.

@shashankb73

Hi, I can deliver this. Netflix churn analysis with SQL exploration, Power BI dashboard, and actionable recommendations—this is analytical work I understand. What I understand: You have cleaned Netflix user data. I'll explore behavioral patterns (watch-time trends, genre preferences, subscription tier correlation with churn) using SQL. Build visuals showing the strongest churn drivers. Create an interactive Power BI dashboard sliceable by genre, subscription type, date range, and churn status. Write a memo highlighting quick wins and retention strategies backed by the data. Deliverables: SQL exploratory analysis surfacing key churn patterns Clear explanatory visuals showing behavioral drivers Power BI dashboard with DAX measures, auto-refresh on new data Short recommendation memo—quick wins + longer-term retention ideas Setup guide for non-technical stakeholder to refresh single-click What you get: Dashboard updates automatically when data is appended All metrics and slicers work smoothly Actionable insights, not just data dumps Everything packaged for stakeholder use (no coding required) One critical clarification: The acceptance criteria mentions churn prediction model. Do you need me to build a predictive model, or is the exploratory analysis + dashboard enough? That changes the scope significantly.

@ArthurSant0s1

Olá! Tenho interesse em participar deste projeto e acredito que posso entregar um trabalho de qualidade alinhado às suas expectativas. Atuo com edição de vídeos, realizando cortes estratégicos, sincronização de áudio, legendas, transições, efeitos visuais, correção de cores e ajustes necessários para tornar o conteúdo mais profissional e envolvente. Sou uma pessoa comprometida com prazos, comunicação e atenção aos detalhes. Antes de iniciar, procuro compreender exatamente os objetivos do cliente para garantir que o resultado final esteja de acordo com o que foi solicitado. Estou à disposição para discutir mais detalhes sobre o projeto e encontrar a melhor solução para suas necessidades. Agradeço pela oportunidade e aguardo o seu retorno.

@callistusjerold

Hello, I am a Senior Business Intelligence and Data Analytics professional with 8+ years of experience delivering analytics solutions using SQL, Python, Tableau/Power BI, Databricks, and Alteryx. For your Netflix churn analysis project, I can: • Perform detailed exploratory analysis of watch-time behavior, engagement patterns, content preferences, and subscription tiers to identify the strongest churn drivers. • Build clear visualizations and statistical insights explaining daily, weekly, and seasonal viewing trends. • Develop an interactive Power BI dashboard with dynamic filtering by genre, subscription type, churn status, and date range. • Create robust DAX measures and KPIs that automatically refresh when new data is appended using the same schema. • Build a baseline churn prediction model and provide performance metrics including accuracy, precision, and recall. • Deliver a concise recommendation report highlighting actionable retention strategies and business opportunities supported by data. My background includes designing enterprise BI solutions, optimizing large-scale datasets, creating executive dashboards, and translating complex analytical findings into business-focused recommendations. I can provide clean documentation and a stakeholder-friendly solution that can be refreshed and used without technical expertise. I would be happy to discuss timelines, dataset size, and expected deliverables before getting started. Thank you for your consideration.

@Jayabh10

Hello, I am p. Jayabharath a Biotechnology graduate with skills in Data Analysis, Bioinformatics, Python, Excel, Power BI, and Web Development. I have experience working with data processing, analysis, visualization, and research-related projects. I am detail-oriented, committed to delivering quality work, and able to meet project deadlines efficiently. I am confident that I can complete this project accurately and provide reliable results. I look forward to discussing your requirements and contributing to your project. Thank you for your consideration.

@someshwaran8

I'm already working with the Netflix data in my institution so I'm the eligible person for the project

@NithinKumar2021

I specialize in Python-based EDA and have built multiple churn-prediction pipelines from scratch. I'll use pandas + seaborn to surface the strongest behavioural predictors across watch-time patterns, session duration, content genre, and subscription tier — then translate those insights into a clean Power BI dashboard with proper DAX measures for genre/date/churn slicing. Deliverables: annotated EDA notebook, .pbix dashboard file, and a concise recommendation memo. Ready to start today.

@seenutamils

I have carefully reviewed your project requirements and I am confident that I can help you complete this project efficiently. I have knowledge in software development and problem solving, and I am committed to delivering quality work on time. I am a quick learner, communicate clearly, and pay close attention to project requirements. I am ready to start immediately and will provide regular updates throughout the project. Looking forward to working with you. Thank you.

@pradeep21o8

Hello, I am a Data Analyst and Python Developer with experience in Python, SQL, Machine Learning, Data Visualization, and Power BI. I can help identify the key drivers behind Netflix customer churn by analyzing watch-time behavior, session duration, content preferences, subscription tiers, and seasonal engagement patterns. My approach will focus on extracting actionable insights rather than just generating reports. For this project, I will deliver: • Exploratory Data Analysis (EDA) to uncover churn patterns • Statistical analysis and feature engineering • Identification of the strongest behavioral predictors of churn • Clear and professional visualizations • Interactive Power BI dashboard with filters for genre, subscription type, date range, and churn status • Churn prediction model (if required) with accuracy, precision, and recall metrics • Business recommendations and retention strategies backed by data I write clean, well-documented code and ensure that dashboards remain easy to refresh and maintain when new data is added. I am available to start immediately and would be happy to discuss your dataset and objectives in more detail. Looking forward to working with you. Best Regards, Pradeep Kumar Python | SQL | Power BI | Machine Learning | Data Analytics