Anonymous Registration Flow
Sole architect and builder
Stack
- Laravel
- MySQL
- Claude Code
Numbers
- ~85% drop in cost-per-respondent for the new study format
- 4 qualified pipeline leads generated from a single thought-leadership publication powered by this capability
- Zero disruption to the existing longitudinal panel business
Problem
Our flagship research platform, Shopalong, was built around longitudinal panels with full participant PII for purchase validation. That architecture didn’t support a new class of point-in-time studies clients were asking for — quick-turn, no-PII research on emerging topics like AI search behavior. The cost-per-respondent on traditional architecture made these studies economically unviable.
Approach
Re-architected the platform to support a parallel anonymous registration path with stripped-down data collection, batched provisioning, and a different downstream analytics pipeline — without disrupting the existing longitudinal flow that the production business runs on.
Outcome
Cost-per-respondent dropped roughly 85% for the new study format. The capability powered The AI Visibility Gap, our thought-leadership case study on how consumers actually use AI search tools, which generated four qualified pipeline leads from a single publication. The deeper point: this is data-fidelity infrastructure — it lets us collect the exact data we need without the overhead of data we don’t.