Data Analysis
Aim
Result
Project Duration
Often, companies have data that contain a lot of hidden information. Asking the right questions and analyzing the data will give you relevant insights. The goal is to answer the right questions that will help the company to make the right decisions.
Results are presented in an interactive report with recommendations and follow-up steps. Based on this report, clear and well-founded decisions can be made, costs can be saved and processes optimized.
Project duration can vary between 2 weeks and 3 months. In order to carry out the project as quickly as possible, it is important that the relevant data is available, complete and clean. This might require collaboration with the data engineering team.
Case
An online retailer was interested in knowing how customers responded to their marketing campaigns and the factors that are associated with customer response.
What was the response?
About 30,083 (approximately 50%) of the targeted customers had a positive response to the campaign. In this case, we were interested on the factors that influence positive consumer responses to the campaigns
Factors associated with response
The figure below shows the association levels between different attributes that were measured during the campaign. The scores range from -1.0 to +1.0 where 0 denotes a weak association and 1 denotes a very strong association.
Customer attributes like Has kid at home?, Amount on Wines ($), Amount on Gold Products ($), No Deals Purchases, No Catalog Purchases, No in-Store Purchases, Has teen home?, and Amount on Fruits ($) had a positive association with response. On the other hand, Income, Amount on Sweet Products ($), Amount on Fish Products ($), and the No Web Visits per Month were negatively associated with consumer response.
When the sales funnel is optimized according to the (summary) analysis below, turnover can potentially increase by 30%.
Social media was the most effective promotion channel with a conversion rate of 0.1% of all traffic. This indicates that users who first engaged with a promotion on social-media were more likely to purchase the product.
A predictive model was fitted to evaluate the top 5 most important factors influencing a customers choice to purchase a product. The following figure shows the top 5 features.
The analysis shows that Income, Year of Birth, Education (PhD), Marital Status = Together, and Marital Status = Single were the top 5 features that influence customer purchasing decisions.
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