Find accounts with stacked buying signals
A Claude prompt that scans an account list and isolates the accounts firing multiple buying signals at once — funding round plus hiring surge plus leadership change plus product launch. One signal is interesting. Three signals stacked in the same window is a buying intent pattern, not a coincidence. The output is the short list of accounts where the rep should reach out this week, ranked by signal density.
Once Lusha is connected in Claude, the connector runs in the background — no special syntax needed. Just paste the account list and run.
Images on this webpage are for illustrative purposes only. Any named individuals shown in live demo outputs are real, with last names abbreviated for privacy.
The prompt
<context>
I want to find the accounts in my list with the highest concentration of buying signals — multiple signal types firing in the same window. These are the accounts most likely in an active buying cycle right now.
</context>
<task>
1. Take this account list (one per line, domain or name):
[PASTE ACCOUNT LIST]
2. For each account, use Lusha's signals layer to retrieve activity in the last [WINDOW, e.g. 90 days]:
- Financial events (funding rounds, IPO, M&A, strategic investments)
- Leadership events (executive hires, promotions, departures)
- Hiring surges by department
- Product launches and partnerships
- Headcount growth (1m, 3m, 6m, 12m)
- Web traffic shifts
3. Count distinct signal types per account. A stacked-signal account has 3+ different signal types firing in the window.
4. Output a ranked table sorted by signal density (high to low):
Account | Signal types fired | Detailed signals | Stack score | Recommended priority
5. Assign a stack score:
- TIER 1 — 4+ distinct signal types in the window (drop-everything outreach)
- TIER 2 — 3 distinct signal types in the window (call this week)
- TIER 3 — 2 distinct signal types in the window (monitor and reach out next week)
- SINGLE — 1 signal type only (worth tracking, not stacking)
- QUIET — no signals in the window
</task>
<constraints>
- Stack density is the metric, not absolute signal count. An account with 20 product launches is one signal type. An account with one hiring surge plus one leadership change plus one acquisition is three signal types — a higher stack score.
- Surface the actual signals per row so the rep can read the pattern, not just trust the rank.
- Multiple instances of the same signal type (e.g., three hiring surges over three weeks) count as one signal type. Persistence within a type strengthens that one signal, but stack score measures cross-type breadth.
- Do not invent signal types or events. Surface only what Lusha returns.
</constraints>What you'll get back
Input: 5-account list (Snowflake, Datadog, Notion, Together AI, Verkada). Window — last 6 months. All signal types enabled.
Output: 2 TIER 1, 1 TIER 2, 1 TIER 3, 1 SINGLE-signal. Every account in the territory fired at least one signal — the stack-score lens is what separates the priority calls from the routine monitoring. Below is the real result from running the prompt against the live Lusha connector.
| Account | Signal types fired | Stack score | Priority |
|---|---|---|---|
| Snowflake | Leadership (3 executive hires + multiple departures), M&A (3 acquisitions), Strategic Investment (2 rounds), Product Launches (6+), Hiring Surges (Sales, Operations, Marketing, Engineering), Headcount Growth (+9% YoY), Web Traffic (+279% spike) | TIER 1 — 7 types | Drop everything |
| Verkada | Funding ($5.8B valuation round), Hiring Surge (Sales +37%, Engineering +25%), Product Launch (cloud platform integration) | TIER 1 — 4 types | Drop everything |
| Together AI | Funding ($1B round in negotiation, $7.5B valuation), Hiring Surge (Sales +23%), Product (NVIDIA-powered infrastructure) | TIER 2 — 3 types | Call this week |
| Notion | Hiring Surge (Sales +204%), Headcount Growth | TIER 3 — 2 types | Monitor + reach out next week |
| Datadog | Hiring Surge (Sales +27%), Product Launch (GPU Monitoring) | TIER 3 — 2 types | Monitor + reach out next week |
The Notion row is the most instructive case. Notion fired the single strongest signal in the territory — a +204% sales hiring surge against a 16.7-job baseline. But the stack score lens drops Notion to Tier 3 because only two distinct signal types fired. Stack score measures breadth of intent, not intensity of one signal. Both metrics matter. A Notion rep would still reach out — the absolute intensity of the hiring surge justifies it — but Snowflake and Verkada are the accounts where multiple buying signals are firing at once, which is the harder pattern to fake or coincidence.
Real data drawn from the signals layer across all 5 accounts in the last 6 months. Reuses signal data already verified earlier in the gallery — zero additional credits consumed.
Why use Lusha in Claude
A single signal can be coincidence. A funding round without other signals could just be a routine financing event with no near-term buying implication. A hiring surge alone could be a backfill. A product launch on its own could be a roadmap shipment with no operational change. Three signals firing on the same account in the same window is something else entirely.
Stack density is the metric that separates real buying windows from noise. When an account fires funding plus hiring plus leadership change plus product launch in 90 days, the company is rebuilding multiple operational systems at once. Budget is unlocked. Mandate is scoped. Stack is being reviewed. That convergence is rare and short — usually a 60-90 day window — and it’s when AI prospecting tools earn their keep.
Stack score weighs breadth, not intensity. A Notion-style +204% hiring surge is the most intense single signal in our example, but it’s still one signal type. Snowflake firing across seven signal types is qualitatively different — the company is moving on multiple fronts simultaneously, and any reasonable hypothesis about budget timing favors action this week, not next quarter. Both metrics matter for different decisions. Intensity tells the rep how strongly one mandate is firing. Stack tells the rep how many mandates are firing at once.
The QUIET accounts are part of the answer. An account list scan where 4 of 5 accounts fire multiple signals isn’t an exceptional week — it’s a portfolio working as designed. An account list where 4 of 5 accounts are quiet is a different problem, either with the list or with the timing. The prompt surfaces both ends so the rep can read the portfolio as well as the rows.
Data drawn from Lusha’s signals layer, built on 300M+ verified contacts and millions of company records under GDPR, CCPA, SOC 2, ISO 27701, ISO 31700, and TRUSTe.
FAQ
How is signal stacking different from signal intensity?
Intensity measures how strong one signal fires — a hiring surge at +204% is more intense than one at +29%. Stacking measures how many different signal types fire on the same account in the same window. An account can score very high on intensity while scoring low on stack, or vice versa. Both views matter. Stack score is the one to lead with when prioritizing the week’s outreach because three different signals firing together is harder to dismiss as coincidence than one big number.
What if an account fires three hiring surges in a row but no other signal types?
Three hiring surges in three consecutive weeks count as one signal type — surge in hiring. The persistence makes the hiring signal stronger, but the stack score still reads as one type firing. The page surfaces this in the constraint block deliberately. Persistence within a type is intensity. Diversity across types is stacking. They’re different metrics.
What signal types count toward the stack score?
Funding events (rounds, IPO, M&A, strategic investments), leadership events (hires, promotions, departures), hiring surges by department, product launches, partnerships, headcount growth, and web traffic shifts. Each is one type. The prompt counts distinct types fired in the window.
Does this work for ABM tier-1 accounts only, or for any account list?
The prompt works on any list size — 5 accounts, 50 accounts, 500 accounts. The math is the same: count signal types per account, rank by density. For large lists, batch by tier or owner so the output stays readable.
How is this different from the weekly signal digest?
The digest is a rhythm — same list, same window, run every Monday, surface what changed this week. This prompt is an analytical lens applied to a window — find the accounts where multiple signal types fired, regardless of which week each one landed. Use the digest for weekly territory monitoring. Use this prompt when the rep wants to find the highest-conviction accounts in a quarter or before campaign kickoff.
Can I combine the stack score with the verified buying group for those accounts?
Yes. Identify the TIER 1 accounts first, then pair with the buying group prompt to pull the verified decision-makers at each. The combined workflow — stacked signal accounts plus verified contacts inside each — is the highest-leverage prospecting pattern in the gallery. Pair this prompt with the buying-group prompt for end-to-end execution.
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