Gen-Zero Case Study | closed:in
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Energy / Sustainability Netherlands Cold Email

Turning a saturated market into 142 opportunities for Gen-Zero

Gen-Zero helps businesses cut their energy bill by buying energy collectively. closed:in built their entire Dutch prospecting engine, custom KVK-anchored data, signal-based segmentation and Instantly infrastructure, and turned a market everyone calls saturated into a predictable pipeline. The investment paid for itself in under two months.

0
Opportunities
27,455
Businesses contacted
1 : 193
Per opportunity
< 2 mo
Investment payback

Winning a market everyone else is already fighting over

Gen-Zero helps businesses cut one of their largest fixed costs by buying energy collectively. By pooling demand, it locks in fixed rates ahead of the market and secures pricing structurally below what a single business could negotiate alone. The service is free to the customer, and Gen-Zero is paid on commission by the supplier.

Before closed:in, acquisition was entirely manual: self-sent cold emails, cold calls, and lead lists pieced together by hand. The market itself was never the problem. Effectively every business needs an energy contract, so the addressable market is enormous. That size is exactly the trap. The obvious high-consumption niches are saturated and over-pitched, which turns outbound into a price war in the inbox. The brief to closed:in was simple, and hard: find a niche with high energy use and low competition, and do something nobody else is doing.

A custom data engine, run on Instantly

closed:in does not buy lists and blast them. For Gen-Zero, they engineered the entire Dutch prospecting layer from scratch, then ran it on Instantly's sending infrastructure.

01
KVK-anchored data engine
Anchored the hospitality segment on the official Dutch business registry (KVK), filtered on the SBI codes that legally define horeca, then triangulated coverage across OpenStreetMap, the Yellow Pages, restaurant directories and map data, down to one clean record per business.
02
Custom enrichment, in code
A free-first Python pipeline verified each company domain by actually connecting to it, harvested a real contact email, pulled owner names off about pages, and automatically removed businesses that had permanently closed.
03
Signal-based segmentation
Prospects were split into niches the message could speak to: energy-intensive cuisines and multi-location chains on the hospitality side, and on the grower side, high-gas-usage areas flagged with real CBS government data plus sites already mentioning solar panels and heat pumps.
04
Sending on Instantly
Plain-text, multi-step sequences ran on Instantly across 40 to 60 inboxes and 20-plus domains, with replies routed straight into the CRM. Bounce held under 1% and inboxes stayed at full warmup throughout.

With that first list, it just worked really well. 35 opportunities out of it. That is a lot, and that is just good. We can see it just works now.

Daniel, Gen-Zero

142 opportunities from 27,455 contacts

In about 13 weeks, the system produced 142 opportunities from 27,455 businesses contacted, a steady rate of one opportunity for roughly every 193 reached. With the conversion proven and the unit economics healthy, scaling was the obvious move: closed:in increased volume 50%, from 1,000 to 1,500 emails a day, and the conversion held. Across those opportunities, at Gen-Zero's deal economics, the program represents a six-figure potential in annual contract value, and the investment paid for itself within the first two months.

0
Opportunities generated
5.07%
Reply rate
1 : 193
Businesses per opportunity
< 2 mo
Investment recouped
Gen-Zero Instantly campaign dashboard: 72.5K emails sent, 142 opportunities, 5.07% reply rate

This campaign was featured by Instantly. Read the Instantly case study ↗

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