MoreWhat a signal is
A signal is an observable event that says an account may be ready to buy now. It turns a static target list into a timed one.
MoreThe data categories you can capture

Every signal resolves to one of a handful of data types. These are what you capture; the four modes below are how you find them. The examples here are illustrative, not a fixed or exhaustive list; your signal library expands to what your firm can act on.

FirmographicTechnographicDemographic / contactBehavioral and intentTrigger events
MoreFour ways to find them

This is the case for a custom engine over a bought tool or brute force. The methods of market research map almost one-to-one onto how intelligence gets sourced, and the breadth is the point. An off-the-shelf tool reads one mode. Your most expensive people, working by hand, cover two or three at enormous cost. A custom engine reads all four, calibrated to your market.

Mode 1
Mine what is available
The public and third-party record: firmographics, technographics, filings, earnings transcripts, press, web-visitor data. This is where off-the-shelf intent tools live, and they live in a thin slice of it. Everyone buys the same slice, so everyone sees the same thing.
Mode 2
Observe what they do
Behavior nobody asked them to report: hiring patterns, job postings, conference attendance, technology adoption, a change in how they work. Reading what an account does, not what it says.
Mode 3
Hear what they tell you directly
First-party declared signal from your own world: a client engagement wrapping, a champion changing roles, content engagement, a referral source going quiet, a dormant relationship worth reviving. This comes from your book and your CRM.
Mode 4
Catch what they have not said yet
Inferred intent before an account is in market: earnings-call language signaling a mandate, a leadership change implying a new agenda, a hiring surge that precedes an RFP by sixty to ninety days. The hardest mode, and the highest value.
Many kinds of signals, watched at once and scored against your fit, is not something you buy off a shelf or brute-force with a partner's hours. It is engineered, and it compounds.
MoreThird party data + First party data = customized intelligence and competitive advantage

The common error is to assume first-party data only grows existing accounts and third-party data only finds new ones. It does not sort that cleanly. Both feed both.

First-party · your world
A client engagement wrapping, a past client moving to a new firm, a champion changing roles, a referral source going quiet, a dormant relationship worth reviving.
Third-party · the market
A new practice or transformation mandate, an executive leadership change, a PE acquisition or recapitalization, a major competitive loss, a hiring surge in a function.

The integration of your first and third-party signals feeds one intelligence platform that improves both the pursuit of net-new accounts and the expansion of existing ones. Same engine, two sides of the book.

MoreSignal libraries are built per practice

Generic signals are commoditized. Every competitor can track a funding round. Few can read a shift in technology strategy at a named account before the RFP. The library is calibrated to the practice it serves, which is the breadth that proves the custom build.

Financial Services practice
A regulatory change, an M&A or recapitalization, a new CDO or CRO, a core-platform migration, earnings language signaling a transformation mandate.
Operations and Supply Chain practice
A plant or network expansion, an ERP migration, a tariff or sourcing shock, a new COO, a recall or service disruption.
Human Capital practice
A reduction or reorganization, a rapid hiring surge, a culture or retention crisis surfacing in reviews, a new CHRO, a post-merger integration.
MoreThe limits of traditional lead scoring

Traditional lead scoring, also called manual or rule-based scoring, is a static point system. Marketing and sales assign fixed point values to predefined actions and characteristics, for example ten points for an email open or twenty for a relevant title. When the accumulated score crosses a threshold, typically sixty to eighty points, the lead becomes an MQL and is handed to sales. The defining trait is that the weights are set by the team's assumptions rather than learned from outcomes, with no real-time adaptation.

What it is not: it scores individual inbound leads for a marketing-to-sales handoff. It does not surface accounts, does not act on real-time buying signals, and does not tell a rep which contact to reach inside an account or why. That is the gap Redline Growth fills.

On the maturity ladder, traditional scoring sits at Stage 2.
Stage 1
Manual research
Stage 2 · here
Operationalized: firmographic filters, account lists, rule-based scoring
Stage 3
Integrated: account-level intent
Stage 4
Compounding: contact-level signal

The benchmark lift is measured from Stage 2 to signal-qualified. A Stage 2 prospect can claim close to the full benchmark, a Stage 1 prospect has slightly more headroom but we cap at the cited ceiling, and Stage 3 and 4 prospects have progressively less.