Reaching product teams at the exact moment feedback goes ignored
The platform that routes user feedback for product teams stopped guessing which PMs to reach — and started finding them at the exact moment they needed it most.
Industry
Product Monitoring
Location
US / Remote
Target ICP
Product managers & startup PMs
Use case
LinkedIn outbound
More demos booked per month
Reply rate on signal-based outreach
Less time spent on lead research per batch
Buying signals monitored across LinkedIn
The Challenge
Sending to product managers. Landing with the wrong ones, at the wrong time.
Lotus solved a real problem: user feedback that goes nowhere, bugs that never reach engineering, insights that disappear before anyone reads them. Product managers live with this daily.
The problem was finding them at the moment they were ready to fix it.
Igor would batch LinkedIn research every Monday — identify PMs, write connection requests, and follow up manually. Reply rate sat around 5%. The calls that happened were exploratory; nobody was in pain that week.
A PM who just posted about their feedback process going nowhere is a completely different conversation from one who made peace with the same problem six months ago. Without signal intelligence, Lotus reached both with the same message. And both were ignoring it.
Four signals that started real conversations
Feedback crisis post
PMs posting about feedback being ignored, lost, or never reaching engineering. They named the exact problem Lotus solves — they just haven't found the fix yet.
30-day windowNew PM or Head of Product
Companies that just brought in a new product leader are actively reassessing tooling. The first 60 days is when everything gets reevaluated — including feedback systems.
65-day windowTool migration signal
Teams switching project management tools are already in change mode — more open to adding a feedback layer they're currently missing.
Launch frustration post
PMs sharing post-mortems or lessons from a rough release often highlight the exact gaps Lotus fills. High intent, minimal sales resistance.
65-day windowReply rate: before vs. after Sendio
Reply rate (%)
From signal to demo in three steps
Signal detection
Sendio monitored LinkedIn daily for the four signals that predicted when a PM or product team was most open to fixing their feedback workflow.
ICP scoring
Every detected lead was scored against Lotus's ICP — product managers and startup PMs with active, unstructured feedback systems. Only leads that matched both signal and profile made it to the queue.
Signal-anchored messages
Each message referenced what happened in their world that week. A PM who just shared a post about feedback chaos got a completely different opener than one who had just been promoted. The relevance was built in.
“I used to send to hundreds of product managers and hope the right ones were having the wrong week. With Sendio, I only reach the ones who just had the wrong week. The difference in how they respond is immediate.”
