The consultancy where the best people were spending 40% of their time on the worst work 

James runs a specialist tech recruitment consultancy based in Birmingham. Eight consultants. The firm places software engineers, product managers, and technical leads at UK and European companies. Good client relationships. A strong reputation for quality placements. 

But James had a number that kept bothering him: 40 per cent. That was his best estimate of how much consultant time went into lead research-identifying target companies, mapping decision-makers, pulling contact data, building and cleaning outreach lists. Work that was necessary. Work that was genuinely time-consuming. And work that absolutely did not need a £45,000-a-year recruitment consultant to do it. 

The maths was uncomfortable. Eight consultants, 40 per cent of their time on research, at an average billing rate of roughly £120 per hour for placed candidates. That was a significant amount of potential revenue activity that never happened because the people best positioned to generate it were stuck doing data entry. The consultancy had effectively created an internal bottleneck around prospecting and outreach, a problem many firms now solve through B2B lead generation outsourcing and structured research support.

Why the in-house research approach kept failing 

James had tried to solve this before. Eighteen months earlier, he’d hired a junior researcher. The results had been mixed at best. The quality was inconsistent-some lists were excellent; others were poorly segmented and full of outdated contacts. Communication was difficult. The researcher worked remotely, but there was no daily accountability structure, so James only found out about quality issues when a consultant tried to use the list and came back with complaints. 

He’d also experimented with freelance researchers from an online platform. Same problems, lower commitment. One delivered a 500-contact list that turned out to be largely duplicated from a previous batch. Another went quiet for a week mid-project with no explanation. 

What James needed was different from both. Not a junior hire with no accountability. Not a freelancer with no stake in the quality. He needed a dedicated resource, a structured daily output target, and a process that confirmed the quality before it reached the consultants. This is where modern lead generation outsourcing models differ from traditional freelance research support. The focus shifts from ad-hoc list building to consistent, process-driven lead delivery.

A dedicated research coordinator, a daily output target, and AI tools that changed the maths 

A dedicated research coordinator was deployed and trained on LinkedIn Sales Navigator, Apollo.io, and ChatGPT for data enrichment and list building. Combining structured workflows with AI lead generation tools significantly reduced manual research time while improving lead quality and segmentation accuracy. The daily output target was defined upfront and written into the brief: 50 qualified leads enriched with decision-maker contact data, segmented by role, company size, and industry. 

Here’s what the daily workflow looked like: 

The daily log was non-negotiable. Every morning, the coordinator submitted a structured update confirming the previous day’s output, the segmentation applied, any data quality issues flagged, and the day’s planned targets. Consultants could review the list quality themselves, but in practice, they rarely needed to, because the daily log made issues visible before they reached anyone. 

Six weeks in-what changed across the consultancy 

The 12 new client conversations generated in six weeks were the number that shifted how James thought about the model. ‘We’d been leaving the pipeline on the table for months. Not because the consultants weren’t good at business development, but because they didn’t have the time to do it properly. Freeing up 40 per cent of their week changed what was possible.’ 

Within 90 days of deployment, the consultancy had made two new placements directly attributable to relationships initiated from the research database. The revenue from those placements alone was significantly greater than the total cost of the research coordinator over the same period. 

Questions consultancies ask about outsourcing lead research 

How can a remote research coordinator increase lead generation for a consultancy? 

By doing the high-volume, process-driven work that consultants are currently doing themselves, and doing it faster and at higher volume because it’s their entire job, not a fraction of it. A dedicated research coordinator focused solely on identifying targets, enriching contact data, and segmenting lists can produce 50 to 80 qualified leads a day. A consultant splitting their time between research and client work typically produces a fraction of that, and the quality is less consistent because the focus isn’t there. 

What tools does a remote research and data coordinator use? 

LinkedIn Sales Navigator for decision-maker identification and account mapping. Apollo.io for contact data enrichment, email verification, and list building. ChatGPT for data cleaning, categorisation, and summarising company research. Google Sheets for list management and segmentation. A project management tool for daily output tracking. The combination of Sales Navigator and Apollo.io is particularly powerful. Sales Navigator finds the right people, Apollo enriches the data, and ChatGPT handles the formatting and cleaning. 

How do you set output targets for an outsourced research team? 

Start with what the consultants actually need, not an arbitrary number. If a typical outreach campaign needs 200 qualified contacts per week, set the weekly target at 200 and break it into daily targets. Specify the segmentation criteria upfront: role seniority, company size, industry, and geography. Define what ‘qualified’ means for your specific market. Build the target into the daily task log so achievement is confirmed each morning rather than reviewed at the end of the week when it’s too late to course-correct. 

What is the ROI of outsourcing B2B lead research? 

The ROI calculation has two components. First, the value of consultant time recovered-if each consultant gets 40 per cent of their week back, and that time converts even partially into revenue-generating activity, the return is typically several multiples of the resource cost within the first quarter. Second, the direct pipeline impact of increased outreach volume-more contacts, more conversations, more placements. For a recruitment consultancy, a single additional placement from the expanded pipeline can represent £8,000 to £20,000 in fees. 

How does AI improve B2B lead research and prospecting? 

AI removes the manual bottlenecks that slow research down. Apollo.io’s enrichment AI fills in missing contact data from verified sources rather than requiring manual lookup. ChatGPT handles list cleaning, duplicate identification, and segmentation tagging in minutes rather than hours. LinkedIn’s AI features surface decision-maker connections and account insights that would take significant manual research to build. The result is a coordinator who produces 50 qualified, enriched, and segmented contacts a day rather than the 10 to 15 a manual researcher produces over the same hours. 

Want to stop your best people from spending 40% of their time on research? 

As competition for new business increases, more consultancies are adopting lead generation outsourcing to scale prospecting activity without increasing consultant workload or internal hiring costs.
ZeusInfinity Workforce can have a dedicated, AI-trained research coordinator deployed in under two weeks, producing enriched leads every day, confirmed in a daily log, and freeing your consultants to do what they’re actually paid for.