Ale CabreraAle Cabrera
SHIPPED · IP INTELLIGENCE · NOV 2025 TO JUNE 2026 · 6 MONTHS
IP Intelligence Data: Internal Initiative
Proposed and launched a more precise layer of IP intelligence data, using a private to public beta process to validate market fit and production readiness before full GA.
- 5handpicked beta testers with full data access and biweekly validation cycles
- 24 hfrom discovery to access, fully self-serve and automated
- ↑data accuracy, validated through structured biweekly beta testing
About 6 months to GA
- Late 2025Kickoff: proposed private beta with existing, unperfected data
- Early 2026Onboard: 5 handpicked beta testers, biweekly validation cycle begins
- Early–Spring 2026Iterate: engineering resolves accuracy and categorization issues
- Spring 2026Ship v1: public beta launched, paired with new customer website
- NextFull GA: general release following the public beta period
Beta program stages
- Private beta
5 handpicked testers - Validation cycle
biweekly, ~1 month - Public beta
launch with website - Full GA
general release
Three risks, and what happened
| Risk | How it was handled | Result |
|---|---|---|
| Value. No specific customer request was driving this. Was it actually a market priority? | Ran customer interviews to confirm use case and business value before committing further investment. | Organic discovery by existing customers, no dedicated marketing push. |
| Feasibility. Existing IP data gave a location, but not precise enough placement. No clear playbook for packaging it. | Private beta with the data as-is rather than waiting to perfect it. 5 handpicked testers, biweekly validation cycles. | Accuracy and categorization issues resolved as testers surfaced them. Public beta launched. |
| Compliance. Higher-precision location data raised the question of PII-adjacency. | Personally investigated the compliance implications. | IP addresses are PII-adjacent but not classified as PII, clearing the path to proceed. |
My role. Defined the private beta to public beta launch process end-to-end. Led discovery and customer interviews, explored packaging concepts, designed the beta program. Used my data science background to validate data quality issues directly with engineering.
With Sales. The public website functioned as their proof point in enterprise conversations, turning product discoverability into a direct sales asset.
Product leader with a data scientist past · Zapier, Clearbit, HubSpot
Product doc: ale-cabrera.com/portfolio/ip-intelligence-internal