How to tailor a conference’s tracks according to your customer needs and be SOLD OUT in no time! We used customer segmentation.
Problem: The organizers of the “Ladies in Business” Conference had difficulties in attracting participants to the event.
Goal: The ultimate goal was to build a conference program tailored to the needs of female entrepreneurs who aim at scaling their business. Our team took the challenge of transforming survey data into insights, extracting the pain-points and areas in which female entrepreneurs needed support.
Challenges
Machine Learning and Predictive Analytics:
Our initial idea was to identify different entrepreneur profiles and characterize them by their specific needs. The survey had mainly worked with categorical ordinal response. By using cluster analysis and feature engineering, we reached a dead-end and switched the strategy.
Workflow
Machine Learning and Predictive Analytics:
After having a common understanding of the problem and the data, we proceeded with an initial data analysis in the software Python. Data cleaning was performed in order to ensure the quality of the results.
We used different visualizations until reaching those which best highlighted the relevant information. We used an impactful wordcloud, heatmaps, linecharts, boxplots and barplots.
The analysis focused on segmenting the entrepreneurs by their experience in business and highlighting differences and similarities across groups.
Results
The end results were:
- a report, summarizing the relevant information - a story about resilience, perseverance and mentorship.
Together, our client and us, exchanged insights and designed a conference content which debuted with a full house.
