Case Study

From "pipeline by luck" to predictable growth: how this Munich-based AI SaaS Start-Up shortened sales cycles by 30% in 6 weeks.

Overview

Industry: B2B Software / SaaS for Ecommerce

Location: Munich, Germany

Company Size: 11–20 employees

Timeline: 6 weeks

This company is an AI-driven consumer intelligence and market validation company focused on helping consumer brands make better product and go-to-market decisions before committing major budget or time. The company builds realistic digital shopping environments where real consumers interact with products.

They already had:

Founder Led Sales
Highly manual research and outreach

What they lacked was a predictable, automated outbound system to replace luck-based pipeline generation.

The Challenge

Pipeline generation was entirely luck-based.

Founder Led Sales with highly manual research and outreach
Cold Calling & Events as main channels
Pipeline = LUCK
In Q1 & Q2 2025: 52 Discovery Calls total, CR = 17.3%, 198,599k€ booked revenue, Sales Cycle = 47.6 days
No systematic, automated outbound process

As a fast-growing AI SaaS startup, the company needed to move from luck-based pipeline to predictable, automated growth.

The Goal

Build a predictable outbound system that:

End-to-end automation of account research and personalized outreach
Makes pipeline predictable, not luck-based
Generates 4+ discovery calls per week
Shortens sales cycles
Increases conversion rates

The Solution

Automated Outbound System for AI SaaS

We built a fully automated outbound system that eliminates manual work and makes pipeline predictable:

Inside the System

How the Workflow Works (High-Level)

1. ICP Definition & TAM Building

Defined target accounts for consumer intelligence platform:

Consumer brands selling online
E-commerce, product, and marketing teams
Companies launching new SKUs or entering new categories
Marketplace sellers

2. Automated Account Research

Built end-to-end automated research:

Account-level data enrichment
Product and category intelligence
Marketplace performance signals
Competitive positioning analysis
Decision-maker identification

3. AI-Powered Personalized Outreach

Created automated personalized messaging:

Account-specific value propositions
Product validation and market testing angles
Behavioral intelligence messaging
6-touch sequences with personalization tokens
Multi-channel integration (email, LinkedIn)

4. Automated Workflow & Infrastructure

Built complete automation:

Automated list enrichment and scoring
Sequence triggering and follow-up
Reply detection and routing
CRM integration and activity tracking
Real-time dashboard and reporting

5. Sales Process Optimization

Optimized sales process:

Qualification criteria refinement
Meeting routing and follow-up automation
Pipeline tracking and management
Conversion rate optimization

The Result

Immediate Impact

End to end automation of account research and personalized outreach
Pipeline = PREDICTABLE
4+ discos per week
1st deal with 40k value (5 days sales cycle)

After Q3 2025

47 Discovery Calls in Q3 2025
CR = 27.7% (up from 17.3%)
199.240k€ booked revenue
Sales Cycle = 33.9 days (down from 47.6 days - 30% reduction)

Before vs. After

Before

Founder Led Sales, highly manual research and outreach
Cold Calling & Events as main channels
Pipeline = LUCK
Q1 & Q2: 52 Discovery Calls, CR = 17.3%, Sales Cycle = 47.6 days

After

End to end automation
Pipeline = PREDICTABLE
4+ discos per week
Q3: 47 Discovery Calls, CR = 27.7%, Sales Cycle = 33.9 days (30% reduction)
1st deal with 40k value (5 days sales cycle)

One-Line Transformation

Before: Pipeline by luck with manual research and outreach, 17.3% conversion rate, 47.6 day sales cycles.

After: Predictable, automated pipeline with 27.7% conversion rate and 30% shorter sales cycles (33.9 days).

Who This Is For

Teams who:

AI SaaS startups needing predictable pipeline
Founder-led sales teams wanting automation
Companies with luck-based pipeline generation
Teams needing to shorten sales cycles and increase conversion rates