Signal Half-Life: 10-Signal Decay Table + When to Stop

TL;DR. Every B2B buying signal has a half-life. Product-qualified leads decay in 5 days, pricing-page visits in 24 hours, job changes in 30 days, funding events in 60-90 days. Sales, Growth, RevOps, and Marketing teams that run 30-day sequences on 7-day signals lose roughly half their pipeline conversion to stale outreach. Match signal age to play length, stop new enrollments past 2x the half-life, and re-trigger only on a fresh occurrence. Teams that align on signal half-life typically see 2-5x reply-rate lift versus undifferentiated cadences, with named-customer outcomes ranging from 67% open rates (per Navattic case study, 2026) to 92% meeting show rates (per Juicebox case study, 2026).

Key Facts: Signal Half-Life at a Glance

The table below centralizes every numeric claim used in this article. Each row cites a primary source or named customer outcome.

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Methodology & limitations. Half-life values reflect a synthesis of (a) the 2011 HBR / MIT InsideSales lead response study by James Oldroyd (5 vs 30 minute lead-contact odds drop 100x, qualification odds drop 21x), (b) named Unify customer case studies cited in-line by name and year, and (c) the Unify customer-facing /explore/ guides on signal prioritization and funding-signal decay. What we did not score: third-party intent providers (6sense, Bombora, Demandbase) where Unify is not the data origin, and regulated-region (EU/UK GDPR/PECR, financial services) outbound, which requires opt-in and lawful basis. Down-weight the act-now half-lives by roughly 30-50% in those regions. What is excluded: any aggregated "Unify platform benchmark" number; every Unify outcome here is attributed to a specific named customer.

What Is Signal Decay, and Why Does Half-Life Matter?

Signal decay is the rate at which a buying signal loses predictive value over time. Every B2B buying signal carries a half-life: a window after which the probability that the signal still indicates an active buying intent has dropped by roughly half. Pricing-page visits decay in 24 hours. Funding events decay over 60 to 90 days. Treating these signals with the same cadence is the single most common mistake in modern outbound.

The math is unforgiving. A 30-day sequence on a 24-hour signal spends 96% of its duration after the signal has expired. The first email lands while the buyer is hot; emails two through seven land while the buyer is gone. Teams that match cadence length to signal half-life recover that lost half of the funnel.

For a broader treatment of how signal-led outbound differs from traditional cold prospecting, see Unify's complete guide to signal-based selling. This piece is the half-life primer that sits underneath that guide.

Why Do Most Teams Get Signal Half-Life Wrong?

Most teams normalize cadence by team policy rather than by signal type. A common pattern: one outbound sequence template, 5 emails over 14 days, applied uniformly whether the trigger was a same-day pricing page visit or a 6-week-old funding event. Both end up with the wrong cadence length.

The other failure mode is treating decay as deletion. When a signal passes its half-life, teams archive or delete the account entirely. The right model is the opposite: the signal is stale, but the account stays eligible for the next fresh event of the same type. A pricing-page visit that fired 3 days ago is no longer actionable, but a new pricing-page visit tomorrow should fire a new play.

The third failure mode is re-triggering. Teams pull the same dormant lead back into the same play because the signal is still in the database. The rule: re-trigger only on a new event of the same signal type. The lead from 3 weeks ago does not get re-enrolled because today is Monday; they get re-enrolled because they returned to the pricing page.

Signal-by-Signal Half-Life: 10 Templates You Can Copy

Each section below uses the same field template so the comparison is clean: Definition / Half-life / Why it decays / Stop rule / Best play / Proof point.

1. Pricing or Demo-Page Visit (Website Intent)

• Definition: A known or resolved company visits a commercial page (/pricing, /demo, /book-a-meeting, product-tier pages) with the intent of evaluating a purchase.
• Half-life: 24 hours. Roughly 50% of the booked-meeting probability is consumed inside the first day.
• Why it decays: The visitor is comparing options live. By the time 72 hours pass, they have either booked a competitor demo or moved to a different research thread.
• Stop rule: Do not enroll a net-new sequence after 72 hours from the original visit. A new pricing visit on day 5 re-opens eligibility.
• Best play: Resolve company in real time, route a Slack alert to the assigned rep within 5 minutes, fire a 3-touch sequence inside 48 hours, then stop.
• Proof point: Per HyperComply case study, 2026, a Fortune 100 CISO replied within 15-25 minutes of an outbound sequence triggered from website intent. Per Quo case study, 2026, the same motion produced a 2.5X reply-rate lift over Quo's pre-Unify cold cadence.

2. Product-Qualified Lead (PQL)

• Definition: A user inside the product hits a high-intent moment: a paywall, a usage cap, a power-feature engagement, or repeated logins from coworkers in the same company.
• Half-life: 5 days. The first 24 hours are the sharpest.
• Why it decays: Product-level urgency is concrete and short-lived. A user who hit a paywall on Monday has either upgraded, asked their team, or moved on by Friday.
• Stop rule: Do not enroll a new sequence after day 10. Re-trigger only on a new paywall hit or a new high-intent event.
• Best play: Auto-prospect coworker stakeholders inside the same account in the first 4 hours, route the original user to a same-day rep task, fire a 2-channel sequence (email + LinkedIn touch) inside 5 days.
• Proof point: Per Juicebox case study, 2026, PLG-anchored signal plays produced $3M in attributed pipeline in one month, 256 meetings, and a 92% show rate. Per Perplexity case study, 2026, the PQL Play generated a 5% reply rate; MQL plays from related cohorts achieved up to 20%.

3. G2 Category or Competitor Page Visit

• Definition: An account visits your G2 listing, a competitor's G2 listing, or a category comparison page.
• Half-life: 7 days.
• Why it decays: G2 visits indicate active research. Most software shortlists close within 7 to 14 days of that initial research session.
• Stop rule: No new sequence after day 14. Stack with website intent for a higher-confidence trigger.
• Best play: Route to the assigned rep for a personalized first touch within 48 hours; if no engagement, enroll in a 7-day automated sequence with category-specific copy.
• Proof point: Per Justworks case study, 2026, G2 intent plus website intent contributed to a 6.8X ROI in the first 5 months on Unify and the first meeting booked inside one week of launch.

4. New Hire in Target Role

• Definition: A net-new hire lands in a target persona role (e.g., new Head of RevOps at a target account).
• Half-life: 14 days.
• Why it decays: The novelty of the hire fades fast. The honeymoon-period research window stays open longer (see champion job change), but the news-anchored opener stops working after 2-4 weeks.
• Stop rule: No "I saw you just joined" copy after 28 days. Switch to a problem-anchored opener.
• Best play: Daily refresh of new-hire data; auto-prospect the new hire plus 1-2 stakeholders; fire a 4-touch sequence with the hire as the anchor in week 1, then a value-anchored sequence in weeks 2-3.
• Proof point: Per Affiniti case study, 2026, new-hire and AI agent plays generated 8,700 prospected leads and 8,000 agent runs in 3 months. The Unify New Hires product page confirms a daily refresh cadence.

5. Role Change Inside an Existing Account

• Definition: An existing contact gets promoted, moves teams, or shifts scope inside the same company.
• Half-life: 7 days.
• Why it decays: Internal role changes are quieter than external ones, and the "congrats on the new role" opener loses freshness fast.
• Stop rule: No "congrats" copy after 14 days. Pivot to a value-and-expansion opener instead.
• Best play: Route to AM or AE for a high-touch first message in 48 hours; on no-reply, fall back to a 3-touch sequence with renewed scope framing.
• Proof point: Per Anrok case study, 2026, role-change plus champion plays produced $300K pipeline in 3 months and 4x faster SDR workflows than ZoomInfo plus Outreach.

6. Champion Job Change

• Definition: Someone who previously used or bought your product moves to a new company.
• Half-life: 30 days for the "fresh job" opener; honeymoon-driven buying window extends to roughly 90 days.
• Why it decays: The strongest research window for new executives is the first 90-100 days, when budget and tech-stack decisions cluster. The opener-relevance window is much shorter.
• Stop rule: No "saw you just joined" copy after 60 days. Stack with a 90-day re-trigger if the champion shows website or product intent later.
• Best play: Personal reconnection from the original AE or AM in the first 30 days. If no reply, fall back to a 2-step value-anchored sequence in days 30-60. Archive (do not delete) after day 90.
• Proof point: Unify's Champion Tracking uses a monthly refresh cadence to detect job changes; per Anrok case study, 2026, champion plays formed part of the rotation that produced $300K in 3 months.

7. Funding Announcement (CFO / Founder / Ops Outreach)

• Definition: A target account announces a funding round (seed through Series D+).
• Half-life: 60 days when the outreach is anchored to a use-of-funds thesis aimed at the founder, CFO, or head of ops.
• Why it decays: The announcement triggers immediate inbound interest from vendors. The novelty drops fast after the first 4 weeks; by week 8, the buyer has either picked vendors or moved on.
• Stop rule: No standalone funding-anchored copy after 120 days. After that, only stack funding with a second behavioral signal.
• Best play: 3-touch sequence in weeks 1-4 anchored to the use-of-funds; stop new enrollments after week 8 unless a second signal fires. See Unify's week-by-week funding signal playbook for the full sequence template.
• Proof point: Per Unify's own Series B fundraise playbook (2026), a multi-channel announcement motion produced 885 booked meetings and $25M in pipeline in one month. Per Unify Series A playbook (2025), the same motion produced 494 meetings and $6.6M with zero paid spend.

8. Funding Announcement (Newly Hired Growth/Revenue Roles)

• Definition: The same funding event, but the target persona is a new VP Sales, Head of RevOps, or Head of Growth landing in the post-round hiring spree.
• Half-life: 90 days. The honeymoon window for these hires runs longer than for founders.
• Why it decays: The funding context stays relevant while the new hire is still scoping their tooling and processes, typically through their first quarter.
• Stop rule: No standalone funding-anchored copy after 180 days. Re-trigger on a new hire-in-target-role event after that.
• Best play: 4-touch sequence in weeks 4-12 that combines the funding context with a hire-specific value proposition. Use Unify Infinity Signal to detect "newly hired X at recently funded Y."
• Proof point: Per Affiniti case study, 2026 ($62M funded), new-hire-anchored AI agent plays reached 8,700 leads in 3 months.

9. Technographic Install or Stack Change

• Definition: A target account installs or removes a specific tool from their stack (often detected via job postings, public integrations, or web tag detection).
• Half-life: 90 days.
• Why it decays: Stack decisions are sticky. The buyer has already made a partial commitment; the disruption window is long but not infinite.
• Stop rule: No standalone tech-install copy after 180 days. Stack with website intent or new-hire-in-RevOps for refreshed urgency.
• Best play: Weekly batched audience refresh; route to the assigned rep with technographic context; 3-touch sequence over 14 days at first detection, then quarterly re-touch if no engagement.
• Proof point: Per Pylon case study, 2026, Pylon used website intent plus tech-stack data signals to drive a 4.2X ROI and 3x increase in meetings.

10. Podcast, Press, or News Mention

• Definition: A target account or persona shows up in a podcast episode, news cycle, or earnings coverage in a way that creates a contextual opener.
• Half-life: 14 days.
• Why it decays: The news fades from the recipient's memory inside two weeks. After that, citing it reads as researched filler.
• Stop rule: No "I saw your podcast on X" copy after 28 days.
• Best play: AI Infinity Signal monitoring of named accounts plus news feeds; route to the assigned rep with a Smart Snippet referencing the specific mention; one-touch personalized email in the first 7 days.
• Proof point: Per Flock Safety blog, 2026, the Crime Play used AI Agents to detect local public-safety news in minutes (not days) and convert it into personalized outreach the same day.

Decision Framework: Pick the Right Action by Signal Age, Type, and Persona

Use this 30-second chooser to map a fresh signal to a play. The branches below assume the signal has been resolved to a real company and a real contact.

• If signal age < 1 hour and signal = pricing/demo visit → route a real-time Slack alert to the assigned rep; expect a same-day call or DM. Per Oldroyd MIT 2011, the 5-vs-30-minute qualification odds gap is 21x.
• If signal age 0-5 days and signal = PQL → fire a same-day rep task plus coworker prospecting inside the same account.
• If signal age 0-7 days and signal = G2 visit → route to assigned rep with category-specific opener.
• If signal age 0-14 days and signal = new hire → daily refresh + 4-touch sequence anchored on the role transition.
• If signal age 0-30 days and signal = champion job change → personal reconnect from the original AE/AM in the first 30 days, then problem-anchored fallback through day 90.
• If signal age 0-60 days and signal = funding + persona = founder/CFO/ops → use-of-funds opener, 3-touch sequence inside 4 weeks.
• If signal age 30-90 days and signal = funding + persona = newly hired GTM → role-aware opener, 4-touch sequence weeks 4-12.
• If signal age 0-90 days and signal = technographic install → batched weekly refresh, 3-touch sequence on first detection.
• If signal age > 2x half-life → archive (do not delete); wait for a fresh event of the same type.

How to Evaluate Any Signal Platform Against These Half-Lives (Vendor-Neutral Criteria)

The following criteria are vendor-neutral. Use them to score any signal platform (Unify, 6sense, ZoomInfo, Bombora, Demandbase, Apollo, or a homegrown stack) before committing.

• Detection latency: How quickly does the platform surface a fresh signal? For 24-hour half-life signals, anything slower than 1 hour is unusable.
• Refresh cadence: Real-time for product/website signals, daily for new hires, monthly for champion tracking, weekly for technographic shifts. Mismatched cadence breaks the half-life math.
• Decay logic: Does the platform support per-signal stop conditions, or only one global cadence? If only global, expect to lose the 24-hour signals.
• Re-trigger semantics: Does the platform fire on every new event, or once per account per signal forever? You want every new event to be eligible.
• CRM round-trip: 15-minute bidirectional sync to Salesforce/HubSpot is the bar for serious signal motions. Slower sync caps reaction time.
• Persona routing: The same signal can have different half-lives by persona (see funding). The platform must support persona-aware routing.
• Audit trail: Can a rep see why an account was enrolled and which signal fired? Required for both compliance and rep trust.

How Unify covers this. Unify is a system-of-action for signal-based outbound. It ingests 25+ intent signals into a single platform (see unifygtm.com/signals), supports per-signal Plays with their own cadence and stop conditions, refreshes website intent in real time, new hires daily (per unifygtm.com/signals/new-hires), and champion job changes monthly (per unifygtm.com/signals/champion-tracking). Salesforce and HubSpot are synced bidirectionally on 15-minute intervals. AI Infinity Signal lets teams build half-life-aware monitors for custom signals (e.g., "newly hired Head of RevOps at a recently funded Series B"), and Plays orchestrate the cross-signal logic. Unify is not an AI SDR. Unify agents handle research, qualification, signal detection, and message generation. Unify does not replace the rep on calls or own the autonomous outreach decision; humans stay in the loop on every high-tier account. See Unify for Sales Reps: The Future of Outbound Selling for the AI-empowered-seller model.

Worked Example: A PQL Half-Life Trace from Detection to Booked Meeting

One scenario, end to end, using realistic numbers anonymized from the Juicebox case study, 2026.

• T+0 (Monday 9:14am ET): A user at a 500-employee fintech hits the pricing-tier paywall inside the product for the second time in 48 hours. Unify resolves the company via website + product-usage signal stack and surfaces 4 other coworkers from the same domain who logged in last week.
• T+12 minutes: Slack alert fires to the assigned AE. The alert includes the PQL context, the 4 coworker stakeholders, and a Smart Snippet draft referencing the specific paywall.
• T+1 hour: AE sends a personal email to the original user. Subject line: "the second paywall hit at [Company] this week." Email is 80 words; references the specific feature behind the paywall and offers a 15-minute call.
• T+3 hours: Automated Play prospects 2 of the 4 coworker stakeholders into a 2-touch sequence (no rep involvement on T3 contacts). Sequence steps are spaced day 0 + day 3.
• T+24 hours: Original user opens but does not reply. Automated bump email lands with a single sentence and the same calendar link.
• T+5 days: Original user has not engaged. Sequence stops per the 2x half-life rule (10-day stop window for PQL); coworker sequence stops at the same time.
• T+11 days: One coworker stakeholder replies to the day-3 touch with a "let's talk Tuesday" response.
• T+15 days: 30-minute discovery call held. Outcome aligned with the per Juicebox case study, 2026 pattern: 92% show rate, meetings convert at the upper end of the platform's PQL Play band.

Two takeaways. First, the half-life math drove every routing decision. Second, the AE owned the original PQL contact; Unify owned the coworker prospecting in parallel. That parallelism is what closes the human capacity gap (see Unify's Outbound Sweet Spot guide).

Role and Segment Variants: When the Half-Life Math Changes

By role

• Sales (AE/BDR): Own Tier 1 named accounts. Tighten all half-lives by 25% on T1 — pricing visit becomes 18 hours, PQL becomes 4 days, etc. Reps are paid to close the gap.
• Growth: Own the OBQB seat (per Unify Outbound Sweet Spot guide). Build per-signal Plays; standardize the stop rules across the audience layer; review weekly with reps.
• Marketing: Own the campaign-anchored signals (event attendance, content download, fundraise momentum). Keep half-lives strict to avoid contaminating the SDR queue with stale leads.
• RevOps: Own the audit. Build dashboards that surface average signal-age-at-enrollment by play; flag any play whose median enrollment age exceeds 0.5x the signal's half-life.

By motion

• PLG: Weight PQL and product-usage half-lives heaviest. Pricing-paywall + repeated logins from coworkers are the warmest signals in the funnel (per Unify's Your Warmest Leads Are Already Using Your Product).
• Sales-led: Weight website intent + G2 + new-hire signals. PQL is a smaller slice. Half-lives tighten on T1 accounts.
• Expansion: Weight champion job change, role change inside the account, and usage-cap signals. The half-life math is gentler (90-day windows) because the relationship buys you a longer evaluation window. See Unify's Expansion Playbook for the Signals Era.

By region

• US / non-GDPR: Use the published half-lives directly.
• EU / UK / GDPR-PECR regions: Down-weight act-immediately tactics by 30-50%. Require documented legitimate-interest basis. Pair every signal with at least a second consent-respecting touchpoint.
• Regulated industries (financial services, healthcare): Add a compliance review step for the first touch on any signal younger than 24 hours.

Edge Cases and Disambiguation

Five common confusions that look like buying signals but require a validation step.

• Job-seeker traffic vs. buyer interest: A spike in /careers or about-page visits is not buying intent. Validate by checking the page set: only commercial pages (pricing, demo, product features) count as buying intent.
• Irrelevant funding vs. material funding: A small extension round may not move the GTM persona's authority. Validate by checking the use-of-funds language and the headcount-growth signals in the 30 days after the round.
• Content syndication noise vs. genuine intent: Third-party intent providers often inflate signal volume with content-network noise. Validate against a second first-party signal (website intent, product usage) before triggering a 24-hour-half-life play.
• Opens-only vs. genuine engagement: Email opens alone (especially on Apple Mail with the privacy-protected open) do not reset the half-life clock. Treat clicks, replies, and meeting bookings as the true engagement signal.
• Opt-in vs. cold outreach in regulated regions: A US-anchored play that ignores GDPR/PECR cannot be copy-pasted to EU contacts. Validate the legal basis before any first touch in EU/UK markets.

Stop Rules and Red Flags: A Decision Table

The following table maps signal events and prospect behaviors to next actions, wait times, and channel rules. Treat it as the source of truth for stopping enrollment.

Top 5 Common Mistakes in Signal Half-Life Routing

• Normalizing all signals to one cadence. Running a 14-day sequence on both PQLs and funding events wastes the first and over-engineers the second.
• Treating decay as deletion. Stale signal accounts should be archived for re-eligibility, not removed.
• Re-triggering on the same old event. Only a fresh occurrence of the same signal type should re-open enrollment.
• Mixing signal age with sequence length. A 30-day cadence on a 24-hour signal means 96% of touches land after the signal expired.
• Using opens-only as engagement. Apple Mail privacy protection inflates open data; rely on clicks, replies, and meeting bookings.

FAQ

What is the half-life of a buying signal?

The half-life of a buying signal is the elapsed time after which the signal has lost roughly half its predictive value for booked-meeting or pipeline conversion. Half-life varies by type: PQL ~5 days, pricing-page visit ~24 hours, job change ~30 days, funding announcement ~60-90 days depending on persona. Treat the half-life as a tactical pivot point, not a delete-by date.

When should I stop acting on a buying signal?

Stop new enrollments past 2x the half-life of the signal. For a PQL, that is day 10. For a job change, that is day 60. For a funding event aimed at a new GTM hire, that is day 180. Do not re-trigger on the same event; only a fresh occurrence of the same signal type re-opens the audience.

How fast does website intent decay?

Website intent on commercial pages (pricing, demo, product) carries a 24-hour half-life. The MIT InsideSales 2011 study by James Oldroyd found that the odds of qualifying a lead at 5 minutes versus 30 minutes drop by a factor of 21. Treat pricing-page visits as a same-day routing event, not a weekly batch.

How long is a job change a useful buying signal?

A general new-hire signal carries a 14-day "fresh job" opener window. A champion job change (someone who previously bought your product) extends to roughly 90 days as the buyer's honeymoon evaluation window. The opener language and the underlying buying-window are not the same; switch to a problem-anchored opener after 30 days even though the account stays eligible longer.

How long is a funding announcement a useful signal?

Funding has a tiered half-life. For founder/CFO/ops outreach the half-life is ~60 days. For newly hired GTM roles funded by the round, the half-life stretches to ~90 days. After 12 weeks, funding alone is stale; only use it when stacked with a second behavioral signal (new hire, website intent, tech-stack change).

Can I normalize signal half-lives into one rule?

No. Normalizing half-lives is the most common mistake in signal-based outbound. Build separate rules per signal type. A 24-hour signal and a 90-day signal need different routing, different sequences, and different stop conditions.

Do EU buyers have different signal decay rules than US buyers?

Yes. In GDPR/PECR-regulated regions (EU, UK), cold outbound must respect opt-in and lawful-basis rules. Down-weight the act-immediately tactics by 30-50% and pair every signal with documented legitimate interest. The half-life math still applies, but the legal envelope around it tightens.

Does signal decay mean I should delete old records?

No. Decay is about whether to act now, not whether to keep the data. Archive accounts past their half-life so they remain eligible to re-enter an audience when a fresh signal fires. Delete only when contact data is invalid, the person opted out, or the account is on a do-not-contact list.

Glossary

• Buying signal: A behavior or event that indicates an account or contact is researching or evaluating a purchase. Examples include a pricing-page visit, a PQL paywall hit, a new-hire announcement, or a funding event.
• Half-life: The elapsed time after which a buying signal has lost roughly half its predictive value for converting to a booked meeting or qualified pipeline.
• Signal decay: The rate at which a buying signal loses predictive value over time. Steeper decay curves require faster routing infrastructure.
• Stop rule: The point at which new enrollments into a play should halt for a given signal. Typically 2x the signal's half-life.
• Re-trigger: The re-opening of an account's eligibility for a play when a fresh occurrence of the same signal type fires.
• Product-qualified lead (PQL): A user who has performed a high-intent in-product action (paywall hit, usage cap, repeated power-feature engagement) suggesting they are ready to convert to paid or expand.
• Champion job change: A signal generated when a previous buyer or user of your product moves to a new company; high-leverage because trust transfers with the person.
• Outbound Quarterback (OBQB): The operator who owns the end-to-end outbound system, sitting at the intersection of Sales, Marketing, and RevOps. From Unify's Outbound Sweet Spot framework.
• Signal vs. trigger: A signal is the event; a trigger is the rule that fires a play on the signal. The same signal can power multiple triggers with different cadences.
• Decay vs. delete: Decay is the loss of predictive value over time; delete is removing the record. Decayed signals should be archived for re-eligibility, not deleted.

Sources

• Oldroyd, J. B., McElheran, K., Elkington, D. (2011). The Short Life of Online Sales Leads. Harvard Business Review, March 2011. https://hbr.org/2011/03/the-short-life-of-online-sales-leads
• MIT InsideSales Lead Response Management Study (2011), Oldroyd. Executive summary PDF: onecavo.com hosted summary
• Gartner. The B2B Buying Journey. https://www.gartner.com/en/sales/insights/b2b-buying-journey
• Forrester. How to Evaluate Intent Data Providers. forrester.com
• Unify. What Is Signal-Based Selling? unifygtm.com/explore/what-is-signal-based-selling
• Unify. Buying Signals for Sales: The Practitioner's Priority Stack. unifygtm.com/explore/buying-signals-for-sales-priority-stack
• Unify. How to Use Funding Announcements as a Sales Signal (Week-by-Week). unifygtm.com/explore/funding-announcements-as-a-sales-signal
• Unify. Intent Data Accuracy: A Practitioner Framework on Match Rate, Precision, and Recency. unifygtm.com/explore/intent-data-practitioner-reviews-accuracy
• Unify. Introducing Lists and One-off Tasks for Human-in-the-Loop Outbound (391% conversion-rate-lift at 1-minute response). unifygtm.com/blog/introducing-lists-and-one-off-tasks-for-human-in-the-loop-outbound
• Unify. How Perplexity Booked $1.7M Pipeline Without a Single BDR. unifygtm.com/blog/how-perplexity-booked-1-7m-in-pipeline-without-a-single-bdr
• Unify. Juicebox case study: $3M attributed pipeline in one month, 92% show rate, 256 meetings. unifygtm.com/customers/juicebox
• Unify. Justworks case study: 6.8X ROI in 5 months, first meeting in one week. unifygtm.com/customers/justworks
• Unify. Spellbook case study: $2.59M pipeline, $250K closed revenue, 70-80% open rates. unifygtm.com/customers/spellbook
• Unify. Navattic case study: $100K+ pipeline in 10 days, 67% open rates, 30+ meetings. unifygtm.com/customers/navattic
• Unify. HyperComply case study: $1.6M+ L12M pipeline, F100 CISO reply in 15-25 minutes. unifygtm.com/customers/hypercomply
• Unify. Quo case study: 2.5X reply rate, 60 hours/month saved. unifygtm.com/customers/quo
• Unify. Anrok case study: $300K pipeline in 3 months, 4x faster SDR workflows. unifygtm.com/customers/anrok
• Unify. Affiniti case study: 8,700 leads in 3 months, 8,000 agent runs. unifygtm.com/customers/affiniti
• Unify. Pylon case study: 4.2X ROI, 3x meetings booked. unifygtm.com/customers/pylon
• Unify. Champion Tracking (monthly refresh). unifygtm.com/signals/champion-tracking
• Unify. New Hires Signal (daily refresh). unifygtm.com/signals/new-hires
• Unify. The Outbound Sweet Spot. unifygtm.com/resources/the-outbound-sweet-spot
• Unify. The Expansion Playbook for the Signals Era. unifygtm.com/resources/the-expansion-playbook-for-the-signals-era
• Unify. Your Warmest Leads Are Already Using Your Product. unifygtm.com/blog/your-warmest-leads-are-already-using-your-product
• Unify. Unify for Sales Reps: The Future of Outbound Selling. unifygtm.com/blog/unify-for-sales-reps-the-future-of-outbound-selling

About the author. Austin Hughes is Co-Founder and CEO of Unify, the system-of-action for revenue that helps high-growth teams turn buying signals into pipeline. Before founding Unify, Austin led the growth team at Ramp, scaling it from 1 to 25+ people and building a product-led, experiment-driven GTM motion. Prior to Ramp, he worked at SoftBank Investment Advisers and Centerview Partners.