Candidate selection and matching focused on experience in your industry
Marketlead continuously grows the database with strong candidates, monitors the market, and structures data on every profile.
We track the top companies in your industry and find specialists who worked with a similar business model, product, check, and geo.
The database holds the top 5,000 professionals across 40+ roles.
How the "growing companies" signal works
We continuously collect market data and compute comparative company dynamics inside each niche. The model takes in:
- revenue and year-over-year growth
- organic and paid traffic growth, branded search volume
- acquisition channel activity and how fast it scales
- product releases, iteration frequency, expansion to new segments and geos
- hiring: which roles are reinforced, which functions are closed first
- successful direction launches, ad campaigns, SEO positions, mentions, funding rounds, M&A activity
These signals produce a ranked list of leading companies per niche and business model. We then source candidates from that list.
From company to person: the specialist profile
Every specialist in the database is described as a set of parameters:
- niche and industry
- business model
- product
- check size
- audience and JTBD: who buys and which recurring job is solved
- geo
- channels and tools
- AI stack
- measurable results: revenue growth, CAC, ROMI, CPL, retention, conversion, channel launches, new-geo expansion
How matching works
When you bring a task, we describe your company in the same coordinate system: niche, model, check, audience, geo, stage, team, goals for the next 3–6 months.
What decides isn't one parameter but the combination.
- for B2B SaaS with a 500 000 ₽+ check and a long sales cycle, priority goes to experience in a similar model and a similar decision-maker type — not "strong performance in general"
- for mass-market B2C on Telegram and VK, priority is speed of hypotheses, creatives, seedings, and quick-demand work
- for product tasks the heavier weights are retention, activation, product analytics, and AI tools
What you get is not "people with a matching role" but candidates you don't need to train from scratch.
How this differs from classic recruiting
Classic recruiting starts from a job description and keywords. The output is people who formally match the title but don't understand your economics, audience, and niche dynamics.
Our approach starts from a different question:
In what context has this person already produced results, and how close is that context to yours — in niche, business model, check, audience, geo, and the companies winning in this niche right now.
So the shortlist isn't a resume scan but a narrow list of people you can talk to specifically: what the check was, who the audience was, which channels, which metrics, where the experience transfers to your task and where it doesn't.