What needed to be understood.
A simple service count would not show how customers move from one booked service to another. The analysis needed a network structure with sources, targets, connection strength, and business interpretation.
How the analysis was built.
- Modeled initial services as source nodes and successful add-ons as target nodes.
- Built a Power BI network visualization, source-target matrix, and activity ranking.
- Measured central and peripheral services.
- Translated service relationships into bundle, incentive, and staff-training recommendations.
What the evidence showed.
- Facial was the strongest gateway service with 75 successful transitions.
- Massage was the second major connector with 54 transitions.
- Waxing and Haircut were peripheral services with substantially lower cross-sell flow.
- The network depended heavily on a small number of anchor services.
What should happen next.
- Use Facial and Massage as anchors in signature packages and loyalty programs.
- Attach Waxing and Haircut to high-traffic services through targeted add-on offers.
- Train staff on historically successful pairings and monitor the network quarterly.
What this project does—and does not—prove.
The dataset records successful service transitions but does not include service margins, customer-level repeat behavior, or experimental evidence that a proposed bundle will cause incremental sales.