I will build a lead scoring model to increase conversions
AI, Data Science, Cloud Deployments
Vetted by Fiverr Pro
Chris Collins was selected by the Fiverr Pro team for their expertise.
Vetted for
Data Science & ML
About this Gig
Vetted Pro
Your sales team's time is your most expensive asset. Spending it on leads that won't convert is how revenue plans die. A lead scoring model ranks incoming leads so reps call the ones that will actually close.
I'm a data scientist with 10+ years of experience across logistics, e-commerce, and marketplaces. I build scoring models that plug into the tools your sales team already uses no learning curve for reps.
What you get:
- A model trained on your historical lead customer data
- Probability scores and a ranked list of current leads
- Feature importance showing what actually predicts conversion (often not what sales thinks)
- Clean code and documentation
- Optional direct integration with HubSpot, Salesforce, or Pipedrive
Typical use cases: B2B SaaS, agencies, marketplaces, insurance, real estate, anywhere a sales team is sorting inbound.
Before ordering, message me with your CRM and roughly how many historical leads you have. 1,000+ closed/not-closed outcomes is the realistic minimum for a usable model.
Programming language:
Python
•
MLflow
•
Amazon SageMaker
Tools:
TensorFlow
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MLflow
•
Amazon SageMaker
My Portfolio
Other Data Science & ML Services I Offer
FAQ
How many past leads do I need?
1,000 with known outcomes (won/lost) is the realistic floor. Fewer works but with lower confidence.
Which CRMs can you integrate with?
HubSpot, Salesforce, Pipedrive natively. Others via API (message me first).
Will my reps have to change their workflow?
No. Scores appear as a field in your CRM. Reps work the way they already do.
What if my product is new and I have no history?
Lead scoring needs history. I'll tell you honestly if you're too early and suggest an alternative.
Can the model be retrained as new data arrives?
Yes — the Premium package includes a retraining pipeline.
