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Glossary entry

Buying signal

A detected event that suggests a target account is in or near a buying window. Mama catalogs 47 signal types across 5 categories. A signal is the entry to a workflow, not the exit — it tells you which 12 accounts to work this week, not what to send them.

First written: March 12, 2026 · Last revised: May 18, 2026 · Category: detection Reading time: 7 min
01

Plain English

TLDR
A buying signal is something that just happened at an account which makes it more likely they're shopping for what you sell — like a funding round, a new exec hire, a stack change. Mama detects 47 signal types from public sources, scores them by strength + recency, and surfaces the accounts where multiple strong signals just fired.

The phrase "buying signal" comes from B2B sales, where it originally meant anything a buyer says or does on a sales call that indicates interest. Modern usage broadened it: a buying signal is now any public event at a target account that you can detect without them telling you, which suggests they're moving toward a purchase decision in your category.

The shift matters because it changes what outbound looks like. Old outbound: send a lot of emails, hope some land on the few accounts that are in-market right now. Signal-driven outbound: detect which accounts are in-market right now, then send a small number of relevant emails to them.

02

Why it matters

At any given time, only a tiny fraction (most analysts estimate 3–5%) of your TAM is actively in-market for what you sell. Without signals, you're spraying outbound across the full TAM and getting reply rates that reflect the dilution — usually 1–3%.

Signals let you flip the math. If you can identify which 3–5% are in-market this quarter, you can concentrate your outbound on them and get reply rates closer to 12–20% (see the worked numbers in the cold-email-opener playbook).

The catch — and it's a big one — is that a signal isn't an outbound email. The signal is permission to act; the action still has to be good. Most teams that buy intent data assume the signal IS the work and wonder why reply rates didn't change. Section 04 of the manifesto argues this in more detail.

03

The five categories Mama detects

47 specific signal types collapse into 5 categories. Each category fires at a different cadence and carries a different base confidence — see /sources for the upstream-data provenance for each.

FN
Funding events
Closed rounds, M&A, debt raises, IPO. Highest single-signal weight — a Series B usually triggers a 90-day buying window for adjacent tooling.
~140/wk detected
EX
Exec moves
VP+ joins, departures, lateral moves. Strongest reply-rate signal in the consultancy archive — new execs are auditing their stack in the first 30 days.
~80/wk detected
HI
Hiring spikes
Sudden volume change in open roles, role-type changes, geo expansion. Noisiest category — we threshold against the team's own 90-day baseline, not absolute count.
~210/wk detected
ST
Tech stack changes
Tool added, dropped, or swapped on a target's site, app, or job postings. Tightest buying window (~14 days) — stack-decision teams move fast once they've started.
~95/wk detected
VC
Voice mining
Quotes from execs on podcasts, panels, blogs, conference talks. Lowest false-positive rate — execs only say things publicly that they want quoted.
~40/wk detected
04

Real signal vs ambient noise

Not every detectable event is a buying signal. Most aren't. The distinction matters because conflating the two is how teams end up with thousands of "intent records" that don't convert — they're firing on noise.

Real buying signal
A specific event that changes the buyer's environment in a way that creates a buying need for something in your category. "Closed $45M Series B" → likely replacing sequencer + adding intent data inside 90 days.
Ambient noise
A continuous-state observation that doesn't indicate a change. "This company has 280 employees" — true, but says nothing about whether they're shopping for anything right now.

Three tests for whether something is a buying signal

  • Is it an event, not a state? "Just hired a VP" is an event. "Has a VP" is a state. Only events fire signals; states feed firmographic ICP fit.
  • Does it change the buying environment? A funding round creates capacity and pressure to spend. A new office in a new city creates a need for local tooling. A quote about "workflow latency" creates a category-shopping moment.
  • Can you point to the source? If you can't link the signal to a public artifact (press release, LinkedIn post, podcast episode), Mama tags it as inference, not signal. See /sources for the provenance rules.
05

Strength + recency

Two signals of the same type aren't equally useful. A $45M Series B with a Bloomberg interview is louder than a $4M angel round with a tweet. A signal that fired yesterday is more useful than one from 90 days ago. Mama scores both axes per signal.

Strength · how loud is the signal?

Each of the 47 signal types has its own loudness curve. For funding signals, loudness scales with round size, lead-investor profile, and press footprint. For exec moves, it scales with seniority and whether the move was internally promoted vs externally hired. Strength is per-signal-type — a "loud" hiring signal doesn't look like a "loud" funding signal.

Recency · how fresh is the signal?

Signals decay. A funding round from 14 months ago is not a buying signal — it's history. Mama applies a per-type half-life to every signal. Funding signals have a 14-day half-life; exec moves 30 days; stack changes 21 days; voice quotes 60 days (because exec statements stay relevant longer than transactional events).

Funding signal · 14-day half-life
Strength at days 0 → 60
100 50 0
Day 0
100
Day 7
71
Day 14
50
Day 30
23
Day 60
5

The ICP rubric weighs both axes together: signal recency at 25% weight, signal strength at 20% weight. See the ICP rubric entry for how the 4 dimensions combine.

06

How Mama uses it

Three places signals show up in the product:

  • In the brief — every account brief lists the top 3 signals firing on that account, with strength and recency stamped on each, and the source link.
  • In the score — signals feed two of the four dimensions of the ICP rubric (recency + strength). The combined score is what drives working-list sorting.
  • In the working list — Mama publishes a daily "score-jumped" list of accounts where the score rose by 10+ points in the last 24 hours, which is almost always driven by a fresh strong signal.

The signals also feed the cold email builder directly — when you pick a signal type, the builder slots the right consequence sentence into the 6-line frame automatically.

07

Common mistakes

Three patterns we've seen kill the value of signal-driven outbound. All three are listed in more detail on /anti-patterns.

Mistake 1
Treating signals as universally weighted. A funding round, a hiring spike, and a stack change are not equally meaningful for every buyer. The whole point of the per-type strength curves is to stop pretending one signal type fits all motions.
Mistake 2
Ignoring signal recency. A signal from 60 days ago is, for funding events at least, worth less than 10% of its peak weight. Working a stale signal looks to the buyer like you haven't been paying attention.
Mistake 3
Acting on a single signal in isolation. One signal is permission; three signals fusing on the same account in the same window is conviction. The depth dimension of the rubric (20% weight) exists to reward signal fusion.
Found something off? Glossary entries are reviewed in batches. If a definition is wrong, incomplete, or missing the angle that would help your team, email [email protected] and reference this entry — we'll revise and credit your input.
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