PROJECT 03Intermediate
Lead Generation and Lead Behaviour
Business scenario
Orion Telecom's acquisition team generates ~18 leads per day across six sources. Sales complains that many leads are poor quality; marketing says sales does not follow up fast enough.
Problem statement
Describe lead volume and quality by source, region and campaign; describe how leads progress and how fast they convert; propose a lead-filtering rule.
Learning objectives
- Measure lead volume and mix over time
- Analyse lead behaviour (status progression, time to convert)
- Design and evaluate a lead-filtering rule using lead_score
Instructions
Use leads. Conversion = status 'converted'. Time to convert = converted_at − created_at. A filtering rule should be judged on how many conversions it would lose versus how much sales effort it saves.
Tasks
- Monthly lead volume by source and campaign vs non-campaign periods.
- Status distribution and conversion rate by source and region.
- Distribution of days to convert (median, 90th percentile) by source.
- Conversion rate by lead_score band (e.g. deciles).
- Propose a minimum score threshold; quantify leads removed and conversions lost.
- Dashboard of the funnel and source quality.
Deliverables
- SQL
- Dashboard
- Recommendation memo (1 page)
Evaluation rubric
| Criterion | Weight | Excellent | Proficient | Developing | Insufficient |
|---|---|---|---|---|---|
| Data preparation & validation | 20% | Correct filters and grain; validation checks documented and totals reconciled. | Correct and complete with minor gaps in rigour or presentation. | Partly correct; important steps missing, unvalidated or unclear. | Missing, incorrect, or not supported by the data. |
| Funnel & behaviour analysis | 25% | Correct rates, time-to-convert distributions, sensible segmentation. | Correct and complete with minor gaps in rigour or presentation. | Partly correct; important steps missing, unvalidated or unclear. | Missing, incorrect, or not supported by the data. |
| Filtering rule | 15% | Rule evaluated with explicit trade-off numbers. | Correct and complete with minor gaps in rigour or presentation. | Partly correct; important steps missing, unvalidated or unclear. | Missing, incorrect, or not supported by the data. |
| Interpretation & recommendations | 25% | Clear, quantified conclusions tied to the business question, with limitations stated. | Correct and complete with minor gaps in rigour or presentation. | Partly correct; important steps missing, unvalidated or unclear. | Missing, incorrect, or not supported by the data. |
| Presentation | 15% | Concise, well-labelled outputs a manager can act on without explanation. | Correct and complete with minor gaps in rigour or presentation. | Partly correct; important steps missing, unvalidated or unclear. | Missing, incorrect, or not supported by the data. |