Find which signals are actually converting to pipeline

<context>
I want to know which signals are actually converting to pipeline — not which signals we think matter, but which ones appear in deals that became opportunities vs deals that didn't. I want to use this to sharpen our prospecting triggers and stop chasing signals that don't convert.

My data:
- Won opportunities (converted to pipeline): [PASTE COMPANY, SIGNAL PRESENT AT OUTREACH, SOURCE — one per line]
- Lost or stalled outbound attempts (same period): [PASTE COMPANY, SIGNAL USED, OUTCOME — one per line]
- Signals we currently use for outreach: [LIST YOUR CURRENT TRIGGERS]
- Timeframe: [LAST QUARTER / LAST 6 MONTHS]
</context>

<task>
1. For each company in both lists, use Lusha to verify what signals were actually present at the time of outreach:
   - Confirm the signal that was used was real and current at outreach time
   - Check whether any additional signals were present that weren't used
   - Note the recency of the signal at time of first touch

2. Compare signal presence across won vs lost/stalled:
   - Which signals appear disproportionately in won opportunities vs stalled ones?
   - Which signals appear equally in both — suggesting they're not differentiating?
   - Which signals appear only in stalled/lost — suggesting they correlate with low intent?
   - Does signal recency matter? (touches within 30 days of signal vs 60-90 days)

3. Identify signal combinations that outperform single signals:
   - Do any two signals together predict conversion better than either alone?
   - Is there a signal sequence that appears in won deals but not lost ones?

4. Return a signal conversion analysis:
   - Signal performance table: each signal with its conversion rate
   - Top 2-3 highest-converting signals — with the recency window that performs best
   - Bottom 2-3 signals with low or no conversion lift — recommend deprioritizing
   - One signal combination worth testing as a new trigger

5. Flag any signal currently in use that converts at below 10% — that signal is consuming outreach capacity without producing pipeline.
</task>

<constraints>
- Base signal verification on Lusha data, not rep notes or CRM tags.
- Conversion rate = companies that became opportunities / total outreach using that signal. State the denominator.
- If sample size for any signal is under 10 attempts, flag as too small to conclude.
- The signal to deprioritize must be named specifically, not just "focus on better signals."
</constraints>

The situation: A RevOps lead at a B2B SaaS company runs the analysis across last quarter’s outbound — 47 outreach attempts, 14 converted to opportunity. Four signals currently in use: new CRO hire, Series B funding, headcount growth >20%, and job posting spike in the sales function.

Output: Two signals are doing real work. One is neutral. One is consuming capacity with near-zero conversion. One combination outperforms all single signals.

Signal conversion analysis — Q2

47 outbound attempts · 14 converted to opportunity · 33 stalled or lost

Timeframe: Q2. Signal verification via Lusha.

Signal performance table

Top-converting signals

1. New CRO hire — within 30 days of signal 67% conversion rate (8 of 12). The recency window matters significantly: the same signal at 31–90 days converts at 38%. Touches within 30 days of a new CRO joining are nearly twice as likely to convert as touches after 30 days.

Optimal approach: Run the cold call prep prompt or the prospect list from signal prompt immediately when a new CRO signal fires — don’t queue it.

2. Series B funding — within 60 days 45% conversion rate (5 of 11). Strong standalone signal. No significant recency degradation observed within the 60-day window — touches at day 5 and day 55 converted at similar rates.

Signal combination — outperforms both standalone signals

New CRO hire + Series B (both within 90 days) Only 4 companies in the dataset had both signals. All 4 converted to opportunity — 100% in a small sample. Worth building as an explicit Tier 0 trigger: when both signals fire at the same company within a 90-day window, treat it as an immediate priority regardless of other queue position.

Sample size: 4 — directional, not conclusive. Run for another quarter before making it a permanent rule.

Signal to deprioritize

Job posting spike in sales function — 0% conversion (0 of 7)

7 outreach attempts using job posting data as the primary trigger. Zero converted. Lusha verification shows the job posting signal was real in all 7 cases — the issue isn’t data accuracy, it’s that a hiring spike alone doesn’t predict intent to purchase. Companies post roles for many reasons that have nothing to do with vendor evaluation.

Recommendation: Remove job posting spike as a standalone trigger. It may have value as a secondary signal (combined with a new exec hire or funding), but it produces no pipeline as a primary reason to reach out.

Additional signal detected but not being used

Lusha found headcount growth >30% in the sales function at 6 companies that converted — in 4 of those, the headcount growth was the most prominent signal, not the one the rep used for outreach. Currently classified under generic “headcount growth >20%” but the 30%+ threshold appears to be the meaningful cut. Worth splitting the signal category and testing.

Signal verification via Lusha connector, May 19. Outbound data from pasted CRM export.