Best Propects Case Study Header

Best Prospects Scoring Model (B2B Sales Targeting)

Built a weekly top-K best prospects scoring system aligned to rep capacity (125 calls/week) using industry hierarchy, penetration signals, and proximity features—validated with time-based evaluation and productionized for repeatable scoring.

Which prospects should sales reps call this week?

  • Sales reps can only act on ~125 calls per week
  • Conversions are delayed from appearing in the system up to 75 days, on average
  • Base rates are low and vary by region/market/territory
  • Business needs consistent outputs
  • The top 125 need to have a precision/conversion rate of 3% or higher

What types of data and labels were used?

  • Prospects + customer + outcomes
  • NAICS (industry codes) at the 2, 4, 6 levels
  • Basic firmographic data (business demographic data)
  • Geographic data
  • The scoring of a prospect occurred within a 7-day window

Success Metrics

Precision@125

The business is targeting having a 3% conversion rate for sales reps.

Lift@125

How many times was the prospect conversion rate greater than the base conversion rate for the entire sample for the week.

PR-AUC

A metric used when the target is imbalanced, where it measures the area under the precision/recall curve.

Model Choice

XGBoost classifier was chosen based on the imbalanced target, better explainability to the business, and its performance exceeded that of other models.

Feature Engineering

Market penetration

What percentage of the market Cintas penetrated by global/region/market by naics level 2, 4, or 6 depending on whether the business count met the required threshold.

Current Customer Proximity to Prospects

The haversine distance to the nearest customer. Also, the counts of customers within a distance radius to a prospect.

Guardrails

  • Time-based splits/Rolling validation windows
  • No “future” features leaking post-score signals
  • Added a 75-day buffer for the lag between sales and the data entering the CRM system

Evaluation

Trained on data through 10/15/2023; evaluated via a rolling quarterly backtest across 2024, starting 1/15/2024, shifting the evaluation window forward every 75 days, and aggregating performance metrics across all windows for territories that had at least 185 prospects in the sample.