Connect rate vs answer rate: how to diagnose broken recruiting calls fast
Ben Argeband, Founder & CEO of Heartbeat.ai — Definitions + actions + quick troubleshooting.
What’s on this page:
Who this is for
Recruiters and leaders diagnosing why calls aren’t working: high dial volume, low pickup, too many dead lines, or inconsistent results across recruiters. This is a workflow page—measure cleanly, diagnose the bottleneck, then change one lever at a time.
Quick Answer
- Core Answer
- Connect rate tells you whether dials reach a live line (including voicemail/IVR); answer rate tells you whether a human picks up. Use both to pick the right fix.
- Key Statistic
- Heartbeat observed typicals: connect rate ~10% typical (Heartbeat internal). Validate changes with a two-week baseline vs improved plan.
- Best For
- Recruiters and leaders diagnosing why calls aren’t working.
Compliance & Safety
This method is for legitimate recruiting outreach only. Always respect candidate privacy, opt-out requests, and local data laws. Heartbeat does not provide medical advice or legal counsel.
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 |
Framework: The “Stop Guessing” Metric Loop: Measure → Diagnose → Fix
- Measure: capture dials, connects, and human answers consistently (phone tool + ATS/CRM).
- Diagnose: decide if the bottleneck is line quality (connect) or human availability (answer).
- Fix: change one lever at a time for one week, then compare.
Step-by-step method
Step 1) Standardize what you log (so the math is stable)
Your phone tool should separate these outcomes at minimum: connected-to-voicemail, connected-to-human, connected-to-IVR, invalid/disconnected, and no answer. If those are mixed together, your reporting will lie to you.
Step 2) Set up “how to measure in ATS/phone tool” (minimum viable instrumentation)
You need three event types captured reliably:
- Dial attempt: every outbound attempt (including retries).
- Connected call: carrier connects to a live line (human, voicemail, or IVR).
- Human answer: a person answers (not voicemail, not IVR).
Practical setup that works in most stacks:
- Phone tool: create dispositions that separate connected-to-voicemail from connected-to-human. Keep invalid/disconnected separate from no answer.
- ATS/CRM: log each dial as an activity and store the disposition + duration. If you can’t sync every dial, sync daily rollups per recruiter and keep the phone tool as the source of truth.
- Data fields: tag numbers as line tested and store recency (last verified date). That lets you compare performance by freshness.
Step 3) Use a disposition mapping table (so “connected” is consistent)
| 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. |
Step 4) Run the two-week baseline vs improved plan (fast, controlled)
The trade-off is… you need enough volume to smooth out daily noise, but you don’t need months of data to take action.
- 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 (email follow-ups)
- Week 2 (Improved): change one lever based on Week 1:
- If connects are weak: refresh/verify numbers, suppress bad lines, prioritize recent records.
- If answers are weak: adjust call windows, caller ID strategy, cadence, and add context via email.
Step 5) Levers per metric (what actually moves each one)
Levers that move connect rate (line quality):
- Prioritize line tested numbers and track recency (freshness beats “big list”).
- 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 cleaned.
- Operational resource: phone validation for provider direct dials.
Levers that move answer rate (human availability):
- Test call windows by segment (specialty/setting) and document what wins.
- Use consistent caller ID strategy; avoid patterns that trigger spam labeling.
- Tighten cadence: fewer repeat dials in short windows; mix channels so the next call has context.
Levers that move deliverability rate (email lands):
- Fix domain authentication (SPF/DKIM/DMARC) and keep sending patterns consistent.
- Remove bounces quickly; don’t keep sending 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 2 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 2 | 4 | ||
| Call windows are tested by segment and documented | 3 | ||
| Email deliverability is monitored (delivered per 100 sent; bounces removed) | 3 |
Outreach Templates:
These templates are designed to improve answers by adding context and reducing friction. 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 answer problems.
- 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 cold.
How to improve results
Measure this by… running the same report weekly for two weeks, using the same denominators, and comparing segments—not just totals.
1) Use the two-week reporting grid (copy/paste into your ops doc)
| Segment | Connects per 100 dials | Answers per 100 connects | Delivered per 100 sent | Notes (what changed) |
|---|---|---|---|---|
| Week 1 (Baseline) | ||||
| Week 2 (One change) |
2) MEASUREMENT_FORMULA measurement spec (uniqueness hook)
MEASUREMENT_FORMULA: use this measurement spec so your ATS report, phone tool report, and recruiter scorecard all match.
| Metric | Numerator | Denominator | Report format | Primary source |
|---|---|---|---|---|
| Connect rate (reporting spec) | Connected calls | Total dials | Connects per 100 dials | Phone tool |
| Answer rate (reporting spec) | Human answers | Connected calls | Answers per 100 connects | Phone tool |
| Deliverability rate (reporting spec) | Delivered emails | Sent emails | Delivered per 100 sent | Email system/ATS |
| Bounce rate (reporting spec) | Bounced emails | Sent emails | Bounces per 100 sent | Email system/ATS |
| Reply rate (reporting spec) | Replies | Delivered emails | Replies per 100 delivered | Email system/ATS |
Two splits that make the numbers actionable:
- Recency: group by last verified date (your standard buckets).
- Line type: mobile vs office vs unknown (or “direct dial confirmed” vs “not confirmed”).
Canonical formulas (for audit only): 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 + suppression
- Prioritize recently verified, line tested numbers for high-volume dialing.
- Suppress disconnected/wrong-person/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 + context
- Test two call windows per segment for one week; keep 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 has to be 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 and guidance around calling/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 (stop requests and unwanted contact)
Evidence and trust notes
These metrics are only useful if your definitions and denominators stay consistent. We focus on operational measurement (what you can change next week) rather than generic benchmarks. For how Heartbeat.ai approaches data quality, verification, and methodology, see our trust methodology.
Compliance references used in this article:
- https://www.fcc.gov/general/telephone-consumer-protection-act-1991-tcpa
- https://www.fcc.gov/consumers/guides/stop-unwanted-robocalls-and-texts
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/answers. The ATS/CRM is where you tie activity to pipeline outcomes. Sync dispositions into the ATS when possible, but don’t change denominators between systems.
Next steps
- If connect rate is the bottleneck, start with phone validation for provider direct dials and implement recency + 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.
