LeadsUp Banking Lead Scoring Dashboard

My Role

• 01Led the project direction and kept the team aligned around one product workflow.
• 02Provided UI guidance so every page followed the same interface direction.
• 03Trained the machine learning model for lead scoring.
• 04Built a REST API for the deployed machine learning model and integrated the prediction service into the backend logic.

Features

• 01Auto-ranking leads: automatically sorts prospects by highest subscription probability for term deposits.
• 02Transparent lead scoring: each prospect has a score/probability so sales can prioritize calls data-driven, not randomly.
• 03Concise sales dashboard: KPI overview of total leads, contacted, pending follow-ups, conversion rate, and high-priority prospects.
• 04Quick filter & segmentation: sort by status (contacted/pending), priority, and key attributes (age/job/campaign history).
• 05Actionable lead detail view: displays key prospect information to help sales tailor their approach when reaching out.
• 06Follow-up workflow: contact status updates + activity logging so every prospect's progress is tracked and never missed.

Impact

• Helps sales save time by focusing on the most promising prospects based on model predictions, rather than calling randomly.
• Increases campaign conversion rates by directing follow-up priority to prospects with the highest probability.
• Provides an easy-to-use MVP for daily sales workflow: ranking > contact > update status > monitor results.

Stack

Notes