Challenge
Discovery recruitment was fragmented and manual. Customers could opt in to discuss feedback, but there was no single source of truth for consented participants. PMs had to individually contact users and coordinate times, which delayed conversations and reduced response quality while feedback context was still fresh.
Approach
I engineered an automated end-to-end flow:
- Added follow-up opt-in across core surveys (NPS, feature requests, PMF, SUS).
- Routed all relevant survey responses into HubSpot, using low code tools like Zapier.
- Built a HubSpot workflow that automatically sent personalised outreach from PMs (round robin), including self-serve booking links.
- Removed manual scheduling by allowing customers to book directly into PM calendars.
- Embedded post-interview analysis by uploading recordings to Dovetail.
- Added a recurring "Customer Voice" segment in fortnightly Product Syncs to share clips and key insights with the wider organisation.
Impact
- Shifted discovery from ad hoc outreach to a consistent near-weekly interview cadence.
- Reduced PM admin overhead and increased speed from feedback to conversation.
- Enabled PMs to validate both submitted feedback and active product bets in the same session.
- Improved cross-functional empathy and alignment, especially with Engineering, through regular customer evidence in team rituals.
- Created durable onboarding leverage: incoming PMs inherited a live, automated discovery engine instead of building one from scratch.
What I'd Improve Next
- Automate interview recording ingestion into Dovetail.
- Auto-generate participant briefs (account context, product interactions, relevant history).
- Suggest interview prompts tied to company strategy and active product bets.