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How StoneHaven Secured $36M+ in Commercial Pipeline for a Precision-Agriculture SaaS Platform

Commercial pipeline secured
$36M+
Qualified enterprise cooperatives and distributors
165+
Average contract value
3.1× ($350K → $1.09M)
Top-5 national cooperatives adopted
2 of 5

The headline numbers

All inside a 90-day window.

Company context

The client is a precision-agriculture SaaS platform founded in 2016, serving more than 8,000 grower accounts across 3.2M+ monitored acres. The product was strong and the brand was trusted by the growers who already used it.

The problem was not the product. It was how new enterprise customers found their way in. Adoption leaned on pilots, grants, and regional distributor introductions, which made growth real but slow and hard to forecast.

The challenge

A great platform was trapped inside a manual, unrepeatable sales motion.

Every large grower or cooperative took weeks of hand research before anyone could even start a conversation. Outreach went out from the company's main domain, which put deliverability and the brand's reputation at risk every time volume increased. There was no repeatable way into national cooperatives and agri-corporations, the accounts that actually move contract value.

The cost was predictability. The team could not say with confidence how many enterprise opportunities next quarter would hold, because the pipeline depended on intros they did not control.

The process

StoneHaven built an enterprise outbound engine in five layers. Each one removed a specific bottleneck that had been capping growth.

1. Infrastructure and deliverability. StoneHaven stood up 120 dedicated sending domains and 360 mailboxes, fully authenticated with SPF, DKIM, and DMARC, then ran a staggered warmup before any volume went out. This moved sending off the main domain and protected the brand. Bounce rate held at 0.8% across the entire program.

2. TAM mapping and enrichment. StoneHaven mapped 18,000 ICP accounts and enriched 64,000 decision-makers, including ag-business executives, cooperative leaders, and large-farm operators. Each record carried the firmographics that matter in agriculture: acreage, crop type, region, and fund or expansion signals.

3. Personalization at scale. Using dynamic fields from a data enrichment tool, such as crop focus, recent expansion, and regional benchmarks, every email read like 1:1 outreach with zero manual research per prospect. This is what let the program stay personal at enterprise volume.

4. Sequencing and sending. Multi-step sequencer campaigns ran A/B-tested copy through timed follow-ups, with a dedicated pilot-to-contract conversion workflow so interest turned into signed agreements instead of stalling in evaluation.

5. Reporting and optimization. Weekly reviews kept the system honest. When enterprise adoption lagged early, StoneHaven re-engineered the pilot evaluation metrics around grower ROI. That single angle change unlocked the enterprise replies that had not been landing.

The results

The engine produced enterprise pipeline that the client could forecast and repeat.

  • StoneHaven secured $36M+ in commercial pipeline in 90 days.
  • 165+ qualified enterprise cooperatives and distributors entered the pipeline.
  • Average contract value grew 3.1×, from $350K to $1.09M.
  • 2 of the top 5 national cooperatives adopted the platform.

The 90-day funnel behind those outcomes:

Funnel stageResult
Emails sent across sequences~380,000
Reply rate5.6%
Bounce rate0.8%
Positive replies~4,300
Meetings booked2,150
Qualified enterprise opportunities165+

Beyond the numbers

The real shift was control. The client moved from chasing pilots one at a time to running a system that fills the calendar with the right accounts every week.

The tripling of average contract value tells the strategic story. The engine was not just generating more conversations, it was reaching larger cooperatives and agri-corporations that pilots and distributor intros had never reliably surfaced.

"We stopped chasing pilots one by one. StoneHaven gave us a system that fills the calendar with the right co-ops and growers every week."— VP of Revenue at the AgTech platform

Methodology and data note

The figures here come from real client program data over a 90-day period, anonymized for confidentiality. Pipeline, contract value, and funnel metrics reflect actual results from roughly 380,000 emails sent across the sequences described above. The client is kept anonymous at their request; the firmographic details (founding year, account count, monitored acreage) are accurate and unchanged.

FAQ

How long did this take?

The full program ran in 90 days, including infrastructure setup, warmup, TAM mapping, and live sequencing. The $36M+ pipeline and 165+ qualified accounts were secured inside that window.

Why 120 domains and 360 mailboxes instead of sending from the main domain?

Sending high volume from a company's primary domain risks deliverability and the brand's reputation. Dedicated, fully authenticated domains with staggered warmup keep the main domain safe and held bounce rate at 0.8% across ~380,000 emails.

Does this work for AgTech specifically?

Yes. The targeting was built around agriculture firmographics: acreage, crop type, region, and expansion signals, with personalization fields like crop focus and regional benchmarks. The same system structure applies to any enterprise B2B motion, but this build was tuned for cooperatives, distributors, and large-farm operators.

What moved average contract value from $350K to $1.09M?

Reaching larger accounts. The engine consistently put the platform in front of national cooperatives and agri-corporations, including 2 of the top 5 national cooperatives, rather than relying on the smaller pilots and distributor intros that had capped deal size before.

What does a setup like this involve?

A dedicated sending infrastructure, an enriched ICP database (here, 18,000 accounts and 64,000 decision-makers), personalization tooling, multi-step sequencing with a conversion workflow, and weekly optimization. Scope scales with TAM size and sending volume.

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