Running Signal Based Plays

• Source: Report research library
• Frameworks applied: Signal-based selling framework (five signal categories, priority bands with SLAs, signal-to-action playbooks), dynamic account tiering, weekly signal review, leading/lagging signal measurement

Suppression rules and per-rep alert-capacity caps turn SLA misses into a volume problem, which is the failure mode most signal skills miss.

Known weakness, published as found: Nearly every claim rests on a single vendor page; add independent sourcing for the SLA windows and the metric targets, or label the targets as vendor-set defaults in the scoreboard table itself. Gate the five-category signal inventory table as reference material so short runs do not read it.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly running-signal-based-plays in your agent's skills directory.
3. 3.Save the file inside that folder as SKILL.md.
4. 4.Ask the agent one of the trigger requests below.
5. 5.Check the output against what you already know before it leaves your desk.

• Build a signal-based play map with SLAs for job changes, funding rounds and earnings-call mentions
• Reps are ignoring our intent alerts - how do we cut the noise and enforce response times?
• Which accounts should we prioritize this week based on buying signals?

• Write the cold call opener and objection handling script for our new product
• Calculate our SAM for North American mid-market companies running Salesforce

---
name: running-signal-based-plays
description: >-
  Maps buying and account signals to named plays with response-time SLAs,
  routing rules, dynamic account tiering, and noise suppression, then measures
  signal response rate and signal-sourced pipeline. Use when the user says
  signal-based selling, buying signals, intent data, trigger-based outreach,
  job change alerts, funding round trigger, hiring signal, earnings call
  trigger, signal routing, play SLA, why are reps ignoring signals, intent
  signal noise, or asks how to prioritize accounts this week. Use this skill
  whenever the task is turning an observed account event into a timed,
  routed action, even if the user calls it a "trigger" or an "alert". Do NOT
  use for ICP definition and static list building (see
  building-icp-and-target-lists), for cadence and copy design (see
  designing-outbound-sequences), or for inbox and domain configuration (see
  protecting-email-deliverability).
metadata:
  version: "1.0"
---

# Running signal-based plays

Build a signal-to-play map with response SLAs, routing, dynamic tiering, and
suppression, then instrument it. One job: what fires, who acts, how fast, and
what gets ignored. Sequence copy, list construction, and sending infrastructure
are out of scope.

## Operating principle

Every rep action traces to an observable event at a target account, and every
outreach must answer "Why this account? Why now?" — reps work accounts showing
real-time evidence of a buying window rather than working a static list
top-to-bottom
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).

## Workflow

Copy this checklist into your reply and tick items as you complete them:

```
- [ ] 1. Inventory available signals by category and source
- [ ] 2. Score and rank signals; assign priority bands
- [ ] 3. Write the play for each high and medium signal
- [ ] 4. Set routing and SLA per play
- [ ] 5. Build the suppression list for low-value signals
- [ ] 6. Reset tiers dynamically for the quarter
- [ ] 7. Instrument leading and lagging indicators
- [ ] 8. Run the weekly signal review; validate SLA compliance and fix
```

**1. Inventory signals by category.** Force every signal into one of five
categories, because uncategorized signal feeds are what produce equal treatment
of unequal signals
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)):

| Category | What it indicates | Examples |
|---|---|---|
| Intent | Actively researching the category | Pricing/comparison page visits, content downloads, webinar registrations, third-party intent |
| Event | Shifting priorities or new budget | Earnings calls, product launches, M&A, regulatory filings, press releases |
| Behavioral | Named-individual engagement, not anonymous | Email opens, link clicks, demo-page revisits, CRM activity patterns |
| Financial | Budget and urgency | Funding rounds, IPO filings, earnings beats/misses, hiring surges |
| Personnel | Mandate to change, or churn risk | New VP Sales / CRO, key-role hires, promotions, departing champion |

(all rows: [Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework))

Weight personnel and event signals highest when ranking, because they are named
as the highest-correlation leading indicators of a buying window
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
Read event language literally: "digital transformation initiative" implies a
different opportunity than "cost optimization and headcount reduction"
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).

**2. Assign priority bands with SLAs.** This mapping is non-negotiable once
set, because an SLA that is renegotiated per signal is not an SLA
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)):

- **High — act within 24–48 hours.** New CxO/VP hire in the buyer persona (the
  new leader has a 90-day mandate; send a personalized welcome with a relevant
  insight); earnings call mentioning your value area (reference the exact call
  language); funding round Series B or later (tie to the stated growth plan);
  multiple intent signals at one account in one week (multithread 2–3
  stakeholders); champion moves to a new company (congratulate, offer to
  replicate the prior outcome).
- **Medium — act within 1–2 weeks.** Hiring surge in the buyer's department
  (share a use case or benchmark); product launch or expansion (connect value to
  the initiative); a single intent signal such as one content download
  (targeted nurture); conference attendance or speaking (reference their talk).
- **Low — monitor and nurture only.** Job postings in adjacent functions
  (watchlist, revisit in 30–60 days); industry award or press mention (social
  engagement); non-competitive tech-stack change (note for positioning).

Escalate priority when multiple signals cluster at one account — clustering
raises prioritization by itself
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).

**3. Write the play per signal.** Each play states trigger, response window,
research step, artifact, first touch, and follow-up pattern. Two reference
plays, to be matched in shape
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)):

- **New VP of Sales hired.** Trigger: job-change alert or account-intelligence
  flag. Window: 48 hours. Steps — research the new VP's background, previous
  companies, stated priorities, and posts; build a 60-second account brief
  covering current strategic initiatives, recent earnings-call language, and
  competitive landscape; send outreach referencing a specific challenge the VP
  is likely inheriting; send two follow-ups over 10 days, each anchored to a
  *different* insight about the new company.
- **Earnings call mentions "sales transformation" or "revenue operations."**
  Window: 1 week. Steps — pull the exact quote; map the stated initiative to
  specific capabilities; identify 2–3 likely stakeholders (CRO, VP RevOps, VP
  Sales); send insight-led outreach to each referencing the call language.

Play content is a judgment step: hold the trigger, window, artifact, and
follow-up count fixed, and let the rep choose the specific insight, because the
insight is what cannot be templated.

**4. Set routing rules.** For each play, name the single owner role, the
fallback owner, the destination surface (CRM task, email, Slack), and the
disposition options. Deliver signals into CRM, email, and Slack, and treat
native CRM integration as a requirement rather than a nicety, because adoption
collapses when the signal lives outside the rep's working surface
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
Route to exactly one owner with an explicit fallback; two owners on one signal
reliably means zero owners.

**5. Suppress low-value signal noise.** Signal availability has outpaced signal
quality, and the dominant failure mode is teams that "treat all signals
equally"
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
Apply these suppression rules, which are non-negotiable because unfiltered
feeds destroy SLA compliance on the signals that matter:

- Suppress any signal at an account outside the ICP or on the suppression list,
  regardless of strength; fit gates timing.
- Never alert on low-band signals; write them to a watchlist reviewed on the
  30–60 day cycle instead.
- Deduplicate: one alert per account per signal category per 7 days, with the
  strongest instance carried forward.
- Suppress anonymous behavioral signals; behavioral signals count only when
  they resolve to a named individual
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- Cap the weekly alert volume per rep at the number of plays they can execute
  inside SLA, and drop the lowest-scoring surplus rather than queueing it.

**6. Reset tiers dynamically each quarter.** Static tiering makes 50 accounts
Tier 1 because they match the ICP. Signal-based tiering makes 12 accounts Tier 1
*this quarter* because they match the ICP **and** show active buying signals,
while the other 38 drop to Tier 2 until signals fire
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
Preserve the underlying fit tier from list building; the signal tier is an
overlay that controls effort allocation this quarter, not a rewrite of the ICP.

**7. Instrument.** Track these, at these targets
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)):

| Horizon | Metric | Target |
|---|---|---|
| Weekly | Signal response rate — % of high-priority signals acted on within SLA | >80% |
| Weekly | Time-to-response, high priority | <48 hours |
| Weekly | Signal-sourced meetings | 30%+ of new meetings |
| Weekly | Multi-signal accounts | Trend upward |
| Quarterly | Win rate on signal-qualified deals | 2–3x cold outreach |
| Quarterly | Average deal velocity | 20–40% faster than baseline |
| Quarterly | Signal-sourced share of new pipeline | 30%+ within two quarters |

**8. Run the weekly signal review, then loop.** Replace the weekly pipeline
review with a signal review asking: which accounts fired high-priority signals
this week; which signals are clustering at one account; which accounts went
silent after prior activity; where are personnel changes occurring in buyer
personas
([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
Then validate the program:

```
- [ ] Signal response rate >80% on high-priority signals
- [ ] Zero high-priority signals older than 48 hours unactioned
- [ ] Every fired signal has exactly one owner and a disposition
- [ ] No low-band signal generated an alert
- [ ] Alert volume per rep <= executable capacity
- [ ] Every outreach logged names the signal it traces to
```

If response rate is below 80%, do not exhort reps. Cut alert volume by
tightening suppression or demoting a signal type, then re-measure next week and
repeat until the gate passes — chronic SLA misses are a volume problem before
they are a discipline problem.

## Output format

Use this exact structure, because routing configuration and the weekly review
are generated from it. Adapt the per-play prose.

```markdown
# Signal play map — <segment> <quarter>

| Signal | Category | Band | SLA | Owner role | Surface | Play |
| New VP Sales hired | Personnel | High | 48h | AE | Slack + CRM task | play-01 |

## play-01 — <name>
Trigger: ... | Window: ... | Research: ... | Artifact: 60-second account brief
First touch: ... | Follow-up: 2 touches / 10 days, distinct insight each

## Suppression rules
<rule -> reason>

## Dynamic tiering — this quarter
| Account | Fit tier | Signals firing | Signal tier |

## Scoreboard
| Metric | Target | Actual | Action if missed |
```

## Gotchas

- Fit gates timing, not the reverse. A strong signal at a non-ICP account is
  still a non-ICP account; working it is the most common way signal programs
  quietly become inbound-flavored spray
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- Manual monitoring does not scale to a named-account list: at roughly 15
  minutes per account per week, 100 accounts consumes about 25 hours, which is
  why unautomated signal programs decay to zero within a quarter
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- Two follow-ups on a personnel play must each carry a *different* insight
  about the new company; repeating the welcome message reads as automation and
  burns the 90-day window that made the signal valuable
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- A single content download is a medium signal, not a hot lead. Routing single
  low-intensity intent signals as urgent alerts is what trains reps to ignore
  the queue, which then costs you the high-priority signals
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- Quote the exact earnings-call language rather than paraphrasing the theme. The
  play's whole advantage is demonstrable specificity, and paraphrase is
  indistinguishable from a generic industry template
  ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
- Signal-triggered sends still count against the sender-side spam-rate ceiling:
  Postmaster Tools spam rate must stay below 0.10% and never reach 0.30% or
  higher ([Google](https://support.google.com/a/answer/81126)). A burst of
  urgent signal outreach to unverified contacts is a deliverability event.
- Do not use open rate as a behavioral signal of record. Google does not track
  open rates and cannot verify third-party open reporting, so an "opened twice"
  trigger is built on an unverifiable measurement
  ([Google](https://support.google.com/a/answer/81126)).
- Vendor-reported ROI figures for signal programs generally lack study-level
  backing, and the framework's own numbers are secondhand citations on a vendor
  page ([Salesmotion](https://salesmotion.io/blog/signal-based-selling-framework)).
  Forecast off your own measured signal-sourced pipeline, not off case studies.

What does the Running Signal Based Plays skill do?

Maps buying signals to plays with response SLAs and routing rules, suppresses signal noise, and instruments signal-sourced pipeline

Where does the Running Signal Based Plays skill come from?

Report research library. It was written by The Revenue AI Report against a 12 criterion quality rubric and graded in an independent scoring pass.

Why was the Running Signal Based Plays skill chosen for this library?

Suppression rules and per-rep alert-capacity caps turn SLA misses into a volume problem, which is the failure mode most signal skills miss.

When should the Running Signal Based Plays skill not be used?

Do not use it for: Write the cold call opener and objection handling script for our new product Or: Calculate our SAM for North American mid-market companies running Salesforce

How do I install the Running Signal Based Plays SKILL.md file?

Download the file, create a folder named exactly running-signal-based-plays inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.