How Mindflow achieved a 35% reply rate using intent-based outbound
35%
reply rate on intent-driven campaigns
21%
of replies convert into MQLs
€25k
average contract value (~18-month cycle)
Overview
Mindflow is an AI automation platform helping enterprise teams orchestrate workflows across thousands of APIs. Their customers include large organizations such as Auchan, and their sales process targets cybersecurity leaders like CISOs and SecOps teams.
But generating qualified pipeline for enterprise cybersecurity software is difficult, and traditional outbound methods simply weren't enough.
The challenge
Before using Gojiberry, Mindflow relied on traditional outbound built on ICP lists: building prospect lists, sending cold outreach campaigns, and manually personalizing messages. But this created a fundamental problem — most prospects had no buying intent.
As Nathan Amram, Growth Automation Manager at Mindflow, puts it: "Cold outbound felt too cold. We were reaching out to people without knowing if they were actually interested." To improve results, the team experimented with technical workarounds — tracking followers of competitors, monitoring engagement on cybersecurity influencers, and searching socials manually for niche keywords.
But these signals were difficult to monitor and impossible to scale. Mindflow needed a way to systematically detect buying signals.
The solution
Mindflow integrated Gojiberry's intent data directly into their internal automation agents. Instead of relying on manual prospecting, the company built an automated intent-driven pipeline that runs daily and automatically identifies new prospects showing relevant signals.
Signals tracked
• Engagement on competitor posts
• Reactions to cybersecurity influencers
• Posts mentioning niche keywords — SOAR, security automation, workflow automation, agentic AI
• Explicit pain signals such as discussions around "alert fatigue"
These signals indicate that a prospect may already be exploring automation solutions.
The workflow
Mindflow connected the Gojiberry API to its internal growth automation system. The pipeline operates in three steps.
1 — Detect intent signals
Every day, Mindflow's internal agent pulls fresh leads directly from the Gojiberry API. These leads already contain intent signals indicating potential interest.
2 — Filter by ICP
The automation system filters leads by company type, job titles (CISO, SecOps, DataOps), geography, and company size. Only high-quality matches enter the pipeline.
3 — Generate personalized outreach
A second agent scrapes profiles, generates personalized outreach sequences, and launches campaigns — each sequence automatically adapted based on the intent signal detected.
Nathan describes the system as "a fully automated engine that feeds our outbound with fresh, intent-driven leads every day."
"Intent signals change outbound completely. You're no longer guessing who might be interested."
Nathan Amram, Growth Automation Manager at Mindflow
Results
Using Gojiberry signals, Mindflow dramatically improved the performance of their outbound campaigns: a 31–35% reply rate, with 21% of replies converting into MQLs. Even with deliverability limitations restricting sending volume, the system consistently generates qualified conversations.
The business impact is significant. Mindflow sells enterprise software with a ~€25,000 average contract value and a ~18-month sales cycle — which means a single deal generated from intent signals can pay for Gojiberry for years.
Why it works
For Mindflow, the difference is simple. Instead of contacting random ICP lists, they reach out to prospects already discussing relevant topics:
• Security teams discussing automation challenges
• Engineers complaining about alert fatigue
• Professionals engaging with competitor content
This lets the team start conversations at the moment interest already exists. As Nathan summarizes: "Intent signals change outbound completely. You're no longer guessing who might be interested."
Reliability was essential too. Nathan highlights two key strengths of Gojiberry — a robust API and clear documentation. Once the integration was completed, the system required very little manual intervention: "The API and documentation are excellent. Once everything was connected, it just worked."
What's next
Mindflow plans to continue expanding their intent-driven acquisition model, with future initiatives including tracking additional cybersecurity signals, improving signal scoring, and scaling their automated growth agents.
Their long-term vision is to build a fully autonomous pipeline generation system powered by AI.
The takeaway: enterprise sales teams often struggle with outbound efficiency, and Mindflow solved this by combining AI automation agents with Gojiberry's intent data — a system that continuously identifies high-potential prospects and feeds their outbound engine with qualified leads.
As Nathan concludes: "Intent-based lead generation is the future of outbound."
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