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DataGardener

DataGardener

How a 4-Person Invoice Finance Broker Transformed Prospecting with DataGardener

Invoice Finance Broker
client overview

Client Overview

A small, four-person invoice finance broker in Wales was losing valuable time to manual prospect research across Companies House, Google, LinkedIn and various contact providers. Despite the effort, the team struggled to consistently identify businesses matching their lending appetite, often reaching opportunities after competitors already had.

This case study is relevant for:

Invoice finance brokers, asset-based lenders, and small commercial finance teams who spend too much time on manual prospecting – particularly small brokerages (2-10 people) looking to speed up lead generation.

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Discover how data-driven intelligence can transform financial services lead generation and reduce prospecting spend.

The Challenge

Before using DataGardener, the team spent a significant amount of time researching potential clients across Companies House, Google, LinkedIn and multiple contact providers.

Even after investing hours into research, they often struggled to identify businesses that genuinely matched their lending appetite. Contact information was inconsistent, CRM records lacked quality, and opportunities were often discovered after competitors had already made contact.

The team needed a faster and more reliable way to identify businesses that were likely to require invoice finance.

Why DataGardener?

The broker wanted to spend less time researching and more time speaking with the right businesses.

DataGardener enabled the team to:

  • Build highly targeted prospect lists in under 30 seconds.
  • Filter more than 1,000 companies based on their ideal client profile.
  • Improve outbound targeting.
  • Gain visibility into existing lending facilities.
  • Identify funding opportunities much earlier.

Instead of searching for businesses manually, the team could focus on meaningful conversations with companies that were already aligned with their lending criteria.

How They Used the Platform

Finding Refinance Opportunities Earlier

Using Secured Lending AI together with Debenture Search, the broker filtered:

  • Construction companies.
  • Businesses funded by a specific lender
  • Facilities approaching renewal within the next three to four months.

Before making the first call, the team already understood:

  • Who the current lender was.
  • The type of facility in place.
  • How long the funding had been running.
  • Whether the business was likely approaching a refinance window.

This created far warmer conversations and generated positive engagement with prospective clients.

Identifying Businesses Likely to Need Funding

The broker also searched for:

  • Construction companies.
  • No existing registered charge.
  • Signs of cashflow pressure.
  • Businesses matching their ideal client profile.

Within seconds, DataGardener produced a highly targeted list that would previously have taken hours to build manually.

Instead of researching hundreds of companies one by one, the broker immediately had a qualified list of businesses ready for outreach.

The Results

Following implementation, the team experienced:

  • Significant reduction in research time
  • Prospect lists generated in less than 30 seconds.
  • Better quality outbound conversations.
  • Earlier identification of refinance opportunities.
  • Higher conversion rates through targeted outreach.
  • Improved confidence before every sales call.
  • Approximately three times return on investment through more focused prospecting.

Business Impact

For a small four-person brokerage, time is one of the most valuable assets.

By replacing manual research with DataGardener’s Lending Intelligence, the team was able to dedicate more time to speaking with qualified prospects, strengthening relationships and winning new business.

Instead of wondering who to contact next, they started each day with a targeted pipeline of businesses that matched their lending appetite and showed genuine funding potential.

Products Used

  • Lending Intelligence.
  • Secured Lending AI.
  • Debenture Search.
  • Business Intelligence.
  • Financial Filters.
  • Contact Intelligence.

Client Feedback

“Before DataGardener, most of our day was spent researching companies across multiple sources before we could even make the first call. Now we can identify the right businesses in seconds, understand their existing funding position and spend our time having meaningful conversations instead of searching for information. The quality of our outreach has improved dramatically.”

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