Collaborative Projects – Leveraging team work
Participating in the Data Analytics Bootcamp at Le Wagon I gained valuable insights into effective teamwork, learning how to collaborate, communicate and leverage each team member’s strengths to successfully develop and deliver data projects.
real state french market
Final project of Data Analytics Bootcamp, le Wagon, Batch1334. Team Work of 5. Score cities in France to invest. Develop a clustering and ranking system of French areas that combines the interest of two specific user profiles: leisure and investor
real state french market
Combining both tourism-related factors and investor-driven factors. Performance overview through sales, ROI, housing score, sales price m2, investment score and vacancy rate-
real state french market
Key takeaways & recommendations based on the scoring and clustering results for leisure & investor profiles.
house renting analysis
Team work project of 5. Case study AIRBNB.Optimize the listing offering for analyse to increase overall sales and customer satisfaction. KPI’s from room type, availabilty rate, average price, average review score and revenue.
house renting analysis
Room type deep analysys. Review scores are lower for slower response rates, suggest to reach out to hosts and push them to respond within a day to increase renter satisfaction. Availability Rate by Room Type.
house renting analysis
Pricing for booked vs non booked listings over time. Revenue overtime analysis.
SoloGenius – Empowering Data Analytics
Projects developed independently during the Data Analytics Bootcamp at Le Wagon, demonstrates the power of my individual skills in the world of data analytics. I gained hands-on experience in data collection, analysis, visualization and presentation.
chart formating
data visualization by adjusting colors, fonts, labels and styles .
charting with export
Save and exporting charts from data visualization tools in various formats such as images, PDFs or spreadsheets.
chart count
Analysis to quantify and assessing the frequency of specific chart types.
stock analysis
Systematic evaluation of financial data, market trends, and company performance.
summary analysis
Digital marketing analysis by: turnover, CTR, ROAS, clicks, cost
main results analysis
KPIS: turnover, cost, ROAS, nb_sessions and transactions. Trend over time.
campaign, orders & sales
Campaign analysys: channel, impressions, turnover. Order analysis: turnover, margin, % margin, customer segment. Sales analysis: categories, segment, margin and % margin.
campaign by channel
Analyzing the turnover of the SEA non-branded campaign involves assessing the revenue generated specifically from non-branded search engine advertising, providing insights into the effectiveness of these marketing efforts in driving sale.
campaign by time & channel
Analyse the turnover and cost of SEA non-branded campaign by Quarter, month and day
SALES ANALYSIS BY CATEGORY
Analyse the qty and % margin by categorie , cattegory_2 and product name.
SALES ANALYSIS BY CATEGORY
Analyse the turnover, qty and % margin over time. It cool be interesting to add a brekdown by category.
CROSS FILTERING CHARTS
Add optional metrics as nb_session, impressions, KPI analysis: turnover, ROAS over time.
NPS global score
Analysis by transporter type and segment. Current month satisfaction, average overall score, customer satisfaction over month by domain.
NPS by transporter
Current month transporter NPS NPS over month by transporter, delivery customer satisfaction over month by transporter, delivery reviews over month by transporter.
nps:order by customer
Data analysis and reporting to sort Net Promoter Scores (NPS) by individual customers. It helps identify which customers have the highest and lowest NPS, allowing businesses to focus their efforts on improving relationships with promoters and addressing concerns of detractors.
global analysis by month
Customer analysis by global note over month, customer satisfaction over month by domain.
global score
Customer analysis, current month satisfaction, NPS over month, customer satisfaction over month by domain.
score by segment
Customer score analysis by average NPS by segment, NPS over by segment, satisfaction over month by domain.