Last updated: August 31, 2026
Ben Argeband, Founder & CEO of Heartbeat.ai — definitions, workflow, and a fast way to tell which metric is actually broken.
What’s on this page:
Who this is for
This page is for recruiters and team leads who are dialing a lot but not getting the results they expect — high volume, low pickup, dead lines, or wildly different outcomes across recruiters on the same team. The goal isn’t a benchmark to chase; it’s a repeatable way to separate a list problem from a timing problem, then fix one thing at a time.
Quick answer
- Core answer
- Connect rate tells you whether dials reach a live line at all — human, voicemail, or IVR. Answer rate tells you whether a human actually picks up once you’re connected. They diagnose two different problems, and mixing them together is the most common reason recruiting teams can’t figure out what to fix.
- How to validate a fix
- Run a two-week baseline vs. improved comparison: hold everything steady for a week, change one lever, then compare using the same denominators both weeks.
- Best for
- Recruiters and leaders diagnosing why calls aren’t converting into conversations.
Compliance & safety
This method is for legitimate recruiting outreach only. Respect candidate privacy, opt-out requests, and applicable data and telemarketing laws. Nothing here is legal or medical advice.
At-a-glance: what each metric can (and can’t) tell you
| Metric | What it indicates | Primary levers | What it does NOT indicate |
|---|---|---|---|
| Connect rate | Whether your dial attempts reach a live line (human, voicemail, or IVR) | Number quality, verification, suppression, recency, dialing infrastructure | Whether a person is available or willing to talk |
| Answer rate | Whether a human answers once you’ve connected | Call windows, caller ID strategy, cadence, context via email, gatekeeper routing | Whether your list is accurate (a wrong number can still be “answered”) |
| Deliverability rate (email) | Whether follow-up emails land (so calls aren’t “random”) | Domain auth, list hygiene, bounce suppression, sending patterns | Whether the recipient read it or will reply |
The measure → diagnose → fix loop
- Measure: capture dials, connects, and human answers consistently across your phone tool and ATS/CRM.
- Diagnose: decide whether the bottleneck is line quality (connect rate) or human availability (answer rate).
- Fix: change one lever at a time for a week, then compare against the prior week.
Skipping the diagnose step is where most teams waste effort — they’ll refresh a whole list when the real issue was calling at the wrong time of day, or they’ll test five new call windows when half their numbers are disconnected.
Step-by-step method
1) Standardize what you log
Your phone tool needs to separate outcomes at minimum: connected-to-voicemail, connected-to-human, connected-to-IVR, invalid/disconnected, and no answer. If these get lumped together in reporting, the math will mislead you no matter how much data you collect.
2) Set up minimum viable instrumentation
Three event types need to be captured reliably:
- Dial attempt: every outbound attempt, including retries.
- Connected call: the carrier connects to a live line — human, voicemail, or IVR.
- Human answer: an actual person picks up (not voicemail, not IVR).
A practical setup that works in most stacks:
- Phone tool: create dispositions that separate connected-to-voicemail from connected-to-human, and keep invalid/disconnected separate from no answer.
- ATS/CRM: log each dial as an activity with disposition and duration. If syncing every dial isn’t realistic, sync daily rollups per recruiter and treat the phone tool as the source of truth.
- Data fields: tag numbers as line-tested and store a recency date (last verified), so you can compare performance by freshness rather than guessing.
3) Use a consistent disposition mapping
| Phone tool event/disposition | Counts toward | Notes for recruiters |
|---|---|---|
| Connected – Voicemail | Connected calls | Counts as connected; does not count as a human answer. |
| Connected – Human Answer | Connected calls + Human answers | Use only when a person actually answers. |
| Connected – IVR/Auto-attendant | Connected calls | Track separately if possible; it behaves differently than voicemail. |
| No Connect – Invalid/Disconnected | Total dials only | Flag for suppression or re-verification. |
| No Connect – Busy/No Answer | Total dials only | Not a data-quality signal by itself; often timing. |
4) Run a two-week baseline vs. improved comparison
You need enough volume to smooth out daily noise, but not months of data before acting. Two weeks, one change, consistent denominators.
- Week 1 (baseline): keep your current list and call windows. Report per 100 so denominators stay obvious — connects per 100 dials, answers per 100 connects, delivered per 100 sent for follow-up emails.
- Week 2 (one change): if connects were weak, refresh or verify numbers, suppress bad lines, and prioritize recent records. If answers were weak, adjust call windows, caller ID strategy, cadence, and add context via a follow-up email.
5) Match the lever to the metric
Levers that move connect rate (line quality):
- Prioritize line-tested numbers and track recency — a fresher, smaller list usually outperforms a stale, larger one.
- Suppress known bad outcomes quickly: disconnected, wrong person, do-not-contact requests.
- Segment by source and recency bucket; stop feeding low-quality sources into high-volume dialing until they’re cleaned.
- See phone validation for provider direct dials for a deeper walkthrough.
Levers that move answer rate (human availability):
- Test call windows by segment — specialty or care setting — and document what actually wins.
- Use a consistent caller ID strategy; erratic patterns can trigger spam labeling on carrier networks.
- Tighten cadence: fewer repeat dials in short windows, and mix in email so the next call isn’t cold.
Levers that move deliverability rate (email lands):
- Fix domain authentication (SPF/DKIM/DMARC) and keep sending patterns consistent.
- Remove bounces quickly rather than continuing to send to dead inboxes.
Diagnostic table
| What you see in reporting | Likely root cause | What to check today | Next fix to try |
|---|---|---|---|
| Low connects per 100 dials | Stale/wrong numbers, wrong line type, weak suppression | Share of invalid/disconnected; performance by recency bucket; source-by-source comparison | Verify/refresh; suppress bad outcomes; prioritize line-tested records |
| Connects are OK, low answers per 100 connects | Timing mismatch, caller ID distrust, gatekeeper routing | Answer rate by hour/day; first attempt vs. second attempt; voicemail-to-reply path | Shift call windows; adjust caller ID; tighten cadence; add email context |
| Email follow-ups don’t land (low delivered per 100 sent) | Deliverability issues | Delivered per 100 sent and bounces per 100 sent; check domain auth and bounce suppression | Fix auth + hygiene; remove bounces; slow down; rewrite templates |
| Week-to-week numbers swing wildly | Measurement inconsistency or small sample | Disposition usage consistency; denominator drift across reports | Standardize dispositions; run the two-week plan with one change only |
Weighted checklist
Use this to decide where to spend your next two hours. Score each item 0–2 (0 = not done, 1 = partial, 2 = solid), multiply by weight, and total it.
| Item | Weight | Score (0–2) | Notes |
|---|---|---|---|
| Phone tool dispositions separate connected-to-voicemail vs. connected-to-human | 5 | ||
| ATS/CRM logs dials and dispositions (or daily rollups) tied to recruiter + req | 5 | ||
| Numbers are tagged line-tested and include recency (last verified date) | 5 | ||
| Suppression list exists and is enforced (opt-outs, wrong person, do-not-contact) | 5 | ||
| Two-week baseline vs. improved plan is scheduled with one lever change in week two | 4 | ||
| Call windows are tested by segment and documented | 3 | ||
| Email deliverability is monitored (delivered per 100 sent; bounces removed) | 3 |
Outreach templates
These are meant to improve answer rate by adding context and reducing friction on the next attempt. Keep them short, log outcomes in your ATS, and suppress opt-outs immediately.
Template 1: First call voicemail (15–20 seconds)
Voicemail: “Hi Dr. [Last Name]—this is [Name]. I’m recruiting for a [role type] in [city/setting]. If you’re open to a quick 3-minute screen, call me at [number]. I’ll send a short email with details.”
Disposition to log: Connected – Voicemail
Template 2: Follow-up email after a connected voicemail
Subject: Quick note after my call
Body: “Dr. [Last Name]—I just tried you by phone. I’m recruiting for a [role] with [schedule/case mix/location]. If it’s worth a quick look, what’s the best number/time to reach you? If not you, who handles these conversations in your group?”
Disposition to log (for the call): Connected – Voicemail
Template 3: Gatekeeper-friendly opener (clinic line)
“Hi—can you help me route a recruiting call for Dr. [Last Name]? I’m trying to confirm the best direct number or time window for a brief call. I can email details if that’s easier.”
Disposition to log: Connected – IVR/Auto-attendant (or your closest equivalent)
Template 4: Data cleanup (wrong person)
“Thanks—sounds like I have the wrong contact. Who should I update this to, and should I remove this number for Dr. [Last Name]?”
Disposition to log: Connected – Human Answer (then tag as wrong person and suppress)
Common pitfalls
- Mixing denominators: reporting answers per 100 dials one week and answers per 100 connects the next hides the real bottleneck.
- Not separating voicemail from human answers: voicemail connects inflate connect rate and can mask an answer-rate problem.
- Over-dialing stale data: more volume doesn’t fix bad numbers — it burns recruiter time and can increase unwanted-contact complaints.
- Weak suppression: if opt-outs and wrong-person records aren’t suppressed fast, you waste dials and create compliance risk.
- Ignoring email deliverability: if follow-ups don’t land, your second call is still a cold call.
How to improve results
Run the same report weekly for two weeks, using the same denominators, and compare segments — not just totals.
1) Two-week reporting grid
| Segment | Connects per 100 dials | Answers per 100 connects | Delivered per 100 sent | Notes (what changed) |
|---|---|---|---|---|
| Week 1 (Baseline) | ||||
| Week 2 (One change) |
2) A shared measurement spec
Use this so your ATS report, phone tool report, and recruiter scorecard all match — the single biggest cause of “our numbers don’t agree” disputes is inconsistent denominators, not bad data.
| Metric | Numerator | Denominator | Report format | Primary source |
|---|---|---|---|---|
| Connect rate | Connected calls | Total dials | Connects per 100 dials | Phone tool |
| Answer rate | Human answers | Connected calls | Answers per 100 connects | Phone tool |
| Deliverability rate | Delivered emails | Sent emails | Delivered per 100 sent | Email system/ATS |
| Bounce rate | Bounced emails | Sent emails | Bounces per 100 sent | Email system/ATS |
| Reply rate | Replies | Delivered emails | Replies per 100 delivered | Email system/ATS |
Two splits that make the numbers actionable:
- Recency: group by last verified date using your standard buckets.
- Line type: mobile vs. office vs. unknown, or “direct dial confirmed” vs. “not confirmed.”
Canonical formulas, for audit purposes: Connect rate = connected calls ÷ total dials. Answer rate = human answers ÷ connected calls. Deliverability rate = delivered emails ÷ sent emails. Bounce rate = bounced emails ÷ sent emails. Reply rate = replies ÷ delivered emails.
3) Improve connect rate with verification and suppression
- Prioritize recently verified, line-tested numbers for high-volume dialing.
- Suppress disconnected, wrong-person, and do-not-contact outcomes immediately.
- If you’re building lists manually, start with how to build a physician call list and add verification before dialing.
4) Improve answer rate with timing and context
- Test two call windows per segment for one week, keeping everything else constant.
- Send a short context email after attempt one so attempt two isn’t random.
- Reduce rapid repeat dials; use a cadence that respects clinic flow and candidate experience.
Legal and ethical use
Recruiting outreach needs to stay permission-aware and respectful. Maintain suppression lists, honor opt-out requests quickly, and avoid automated outreach patterns that create unwanted contact. For U.S. teams, understand baseline rules around calling and texting under the TCPA and related FCC guidance.
- FCC overview of the Telephone Consumer Protection Act (TCPA)
- FCC guidance on stopping unwanted robocalls and texts
Evidence and trust notes
These metrics only stay useful if your definitions and denominators stay consistent week over week. This page focuses on operational measurement — what you can change next week — rather than generic industry benchmarks. For how Heartbeat.ai approaches data quality, verification, and methodology, see our trust methodology.
FAQs
When should I focus on connect rate vs. answer rate?
Focus on connect rate when you’re seeing lots of invalid/disconnected outcomes or you suspect stale numbers. Focus on answer rate when you’re connecting but mostly hitting voicemail or gatekeepers — then timing, caller ID, and context are usually the levers.
What should my team report each week?
At minimum: connects per 100 dials, answers per 100 connects, and delivered per 100 sent for follow-up emails. Keep the same denominators every week and segment by recency and source.
Does voicemail count as connected?
Yes. If the carrier connects to a live line and you reach voicemail, it counts as a connected call. It does not count as a human answer.
Where should these metrics live: ATS or phone tool?
The phone tool is the source of truth for dials, connects, and answers. The ATS/CRM is where you tie activity to pipeline outcomes. Sync dispositions into the ATS when possible, but don’t let denominators drift between systems.
Next steps
- If connect rate is the bottleneck, start with phone validation for provider direct dials and implement recency plus line-tested tagging.
- If you need a clean workflow to build and maintain lists, use how to build a physician call list and add suppression from day one.
- To operationalize this in your workflow, start free search & preview data and run the two-week baseline vs. improved plan with consistent reporting.
About the Author
Ben Argeband is the Founder and CEO of Swordfish.ai and Heartbeat.ai. With deep expertise in data and SaaS, he has built two successful platforms trusted by over 50,000 sales and recruitment professionals. Ben’s mission is to help teams find direct contact information for hard-to-reach professionals and decision-makers, providing the shortest route to their next win. Connect with Ben on LinkedIn.
