Statistics
Call tracking and phone lead statistics, traced to source
Real platform data on 1.1 million tracked leads and 70 million+ calls — which channel produces the best calls, how call duration predicts a genuine lead, and what dynamic number insertion can and can't verify.
This is one of the better-sourced pages in this hub: CallRail and Invoca, two call-tracking platforms, analysing their own real usage data across a combined 1.1 million leads and 70 million-plus calls. A vendor whose product exists to measure call outcomes has both the data and the direct incentive to measure this specific question accurately.
The scope here is deliberately narrow: which channel actually produced the call, how long the call ran and whether it was answered, and what a business can and can't verify about where a call came from.
Response speed — how fast a business follows up once contacted — is covered in full on this site's separate lead response time statistics page, and the mechanics of a call converting once answered are covered on the local conversion rate statistics page. This page doesn't repeat either.
Three findings stand out: the cost of a missed call is larger than most businesses assume and varies dramatically by industry; the channel producing the most calls isn't always the one producing the best ones; and several of the specific performance figures attached to missed-call recovery technology don't survive a direct check against the vendor they're attributed to.
How the grading works
The grading is deliberately unforgiving. A statistic from a good organisation still earns a C if the sample size is not published beside the number, because a reader cannot check what they cannot see.
Cite freely
Primary source, dated, with sample and method published. Quote it, with its scope attached.
Cite with scope
Real research with a published sample, but narrower than the way it is usually quoted — self-reported, or one country, or one kind of business.
Cite with caution
Named source and plausible method, but the sample size or methodology is not published where the number is. Attribute it, do not lean on it.
Do not cite
Untraceable, undated, or superseded by later changes to the thing it measured. These are the numbers keeping the roundups alive.
Most callers whose calls go unanswered simply don't call back
This comes from a genuine call-tracking platform vendor analysing its own real usage data — exactly the kind of source that should carry real weight, because measuring call outcomes is what the company does for a living.
85%
Grade Aof callers whose call goes unanswered do not call back.
What it does not say A large, real, cross-industry platform dataset from a vendor whose core business is measuring exactly this outcome — about as credible a source type as exists for this specific claim. This is the single most concrete evidence on this site for why a missed call is a genuinely costly, not merely inconvenient, event.
32%
Grade Amissed-call rate for healthcare businesses — the highest of the industries measured, ahead of legal (28%), home services (14%) and real estate (9%).
What it does not say Healthcare's missed-call rate is more than triple home services' rate in the same dataset — a genuinely large industry gap worth investigating rather than assuming call handling is uniformly adequate across verticals.
What this means for a business that has never measured its own rate
The 85% figure is the reason a missed call belongs on the same balance sheet as a dropped lead, not filed as a minor operational nuisance.
It also means the industry gap above is not a curiosity — it is a direct multiplier on lost revenue, since a healthcare business missing 32% of calls is losing roughly 3.5 times the share of enquiries that a real estate business missing 9% is, before either business has spent a further pound or dollar generating the next call.
Neither figure says anything about why calls go unanswered — understaffing, no after-hours coverage, and calls arriving faster than a small team can pick up all produce the same missed-call rate, and the fix for each is different. Working out which of those is happening is a measurement question before it is a staffing one, and our guide to measuring local marketing sets out how to instrument a phone line so the answer is visible rather than assumed.
The sections below go further than this dataset can: which channel is actually producing the calls worth answering, how long a call has to run before it's likely to be a real one, and what a business can and can't verify about where a specific call came from.
Google Ads, Google Business Profile and organic search drive the large majority of tracked conversations
The same platform dataset breaks down which marketing channels actually produce a phone call or form conversation, not just a click.
37% / 23% / 22%
Grade Ashare of tracked conversations driven by Google Ads, Google Business Profile and organic search respectively — consistently the top three channels across every industry in the dataset.
What it does not say Together these three channels account for roughly 82% of tracked conversations, consistently across industries — a genuinely useful finding for where to focus attribution effort if resources are limited.
What this means, and what it can't tell you yet
A conversation share is a volume measure — it says a channel produced contact, nothing about whether that contact was worth having. The same distinction runs through this site's local lead generation statistics, where channel volume and channel value routinely disagree.
Treating channel share as a budget signal on its own is the mistake the next section exists to correct: the same 1.1-million-lead dataset breaks the funnel one stage further, into qualified leads and booked appointments, and the ranking of channels shifts once quality rather than raw volume is the measure.
The channel that produces the most conversations isn't the one that produces the best ones
CallRail's report announcement carries two further breakdowns beyond raw conversation share: what proportion of each channel's contacts became a qualified lead, and what proportion became a booked appointment. Read together, the three numbers per channel tell a different story than any one of them alone.
| Channel | Share of conversations | Share of qualified leads | Share of appointments |
|---|---|---|---|
| Google Ads | 37% | 47% | 36% |
| Google Business Profile | 23% | 15% | 32% |
| Organic search | 22% | 23% | 18% |
These three channels don't sum to 100% at any funnel stage — the remainder is split across other channels the report names but doesn't break out individually at every stage. Figures are CallRail's own, disclosed directly in its report announcement rather than gated behind the downloadable PDF. Source: CallRail, From Conversations to Conversions report
47% vs 37%
Grade AGoogle Ads produces 47% of qualified leads against a 37% share of raw tracked conversations — the widest gap of the three named channels, and entirely in the paid channel's favour.
What it does not say A paid channel outperforming its own volume share on lead quality is the opposite of the assumption behind most budget cuts to paid search — the volume a channel produces and the quality of that volume are measured separately here, and they disagree for Google Ads in the more expensive channel's favour.
32% vs 23%
Grade AGoogle Business Profile produces 32% of booked sales appointments against only a 23% share of tracked conversations and 15% of qualified leads — the opposite pattern to organic search, whose 18% appointment share trails its 22% conversation share.
What it does not say A Google Business Profile contact skips fewer qualification steps than an organic-search contact does, in this dataset — plausibly because a caller who found the business through its own Business Profile has already seen the address, hours, reviews and category before dialling, arriving further along the decision than a general organic-search visitor.
What this means for reading a channel report
Three numbers per channel, not one, is the honest version of this finding. Google Ads earns its cost by converting a disproportionate share of its contacts into qualified leads — a business judging its ad spend on cost per conversation alone is measuring the wrong stage of the funnel, and a cost per lead calculator will flatter or damn a channel depending entirely on which stage is counted as the lead.
Google Business Profile does the opposite of what its middling lead-qualification share suggests: it under-produces qualified leads relative to its conversation volume, but over-produces the appointments that actually get booked — meaning whatever qualification step CallRail's own categorisation applies, Google Business Profile contacts skip past it more often on their way to an actual booking.
That is consistent with the discovery patterns in this site's Google Business Profile statistics, where a profile visitor has usually seen hours, category and reviews before making contact.
Organic search is the channel where the two ends of the funnel disagree in the less favourable direction. It holds a respectable share of conversations and qualified leads, but converts a comparatively smaller share of those into a booked appointment, which points toward the follow-up process for organic leads specifically, rather than the traffic itself, as the more useful place to look first.
A call that survives past 15 seconds is measurably more likely to be a real one
Invoca's own 2026 benchmark report — built from more than 70 million calls and 600 million minutes of conversation across ten industries — breaks the headline answer rate apart by how long the call actually ran, which turns out to be doing real diagnostic work.
56% → 65% → 71%
Grade B56% of all calls to businesses are answered by a person; filtering out misdials and quick hangups by keeping only calls lasting longer than 15 seconds raises the answer rate to 65%; restricting to calls over 30 seconds raises it further to 71%.
What it does not say Graded B rather than A for the same reason the same report's other figures are graded B elsewhere on this site: a genuinely large, dated, disclosed sample from a company whose core business is measuring this — but a vendor with a direct commercial interest in call tracking looking credible as a category. Read literally, this isn't three independent answer rates; it's the same dataset with progressively stricter duration filters applied, which is exactly what makes it useful — short, unanswered-feeling calls are disproportionately misdials and hang-ups, not missed genuine enquiries.
64%
Grade Bof businesses don't ask leads to buy or book an appointment, on the calls that do get answered.
What it does not say The exact detection method for whether a call included 'an ask' isn't spelled out in the report as published, which is worth flagging even though the figure itself is credible and consistent with the same report's other findings — a call that connects and stays on the line is not automatically a call that was worked properly once answered.
Answer rate rises sharply once short misdials and hang-ups are filtered out
The headline 56% answer-rate figure most reports quote hides that longer calls connect far more reliably than the average suggests.
Scale 0–100%. 70M+ calls, 600M+ conversation minutes, 10 industries, US. Source: Invoca, Lead Conversion Benchmarks Report, 2026
What this means for reading your own call-answer rate against a benchmark
The three-step figure is a warning against comparing a raw answer rate straight against the 56% headline without checking what counts as a "call" in each dataset — a business whose phone system logs every ring, including three-second misdials and hang-ups, will show a lower raw answer rate than one that only logs calls past a minimum length, with no difference in actual call-handling quality between them.
The more useful comparison point is the duration-filtered figures: if a business's own call log can be filtered to calls over 15 or 30 seconds, the 65% and 71% benchmarks are the fairer ones to measure against.
The 64% figure is the more uncomfortable one, because it isn't about whether the phone gets answered at all — it's about what happens once it does. Fixing a missed-call rate only pays off if the calls that do connect are actually being worked, which is a different problem from the speed problem documented in this site's lead response time statistics.
A call-tracking platform that records and reviews calls, even a handful a week, is the only practical way to find out whether staff are asking for the booking or letting the call end without one — a fact no amount of investment in answering faster on its own will fix. Our lead response and follow-up guide covers what to do with the recordings once you have them.
How long a connected call runs also varies by the channel it came from — though this is a smaller, less independently verified dataset
Where the Invoca figures above measure whether a call connects, a smaller agency-run analysis published in 2025 measures how long a call runs once it does, broken out by the marketing channel and device that produced it. It's worth including for the angle no larger report currently covers — with its limitations stated plainly rather than smoothed over.
6m 20s vs 2m 32s
Grade Caverage connected call duration for organic-search-sourced calls (6 minutes 20 seconds, the longest of five channels measured) against third-party-lead-sourced calls (2 minutes 32 seconds, the shortest); Google Ads calls averaged 5 minutes 28 seconds, direct traffic 4 minutes 46 seconds, and Meta Ads calls 3 minutes 27 seconds.
What it does not say This is a single marketing agency's own client-account data, not an independent platform vendor's — a materially smaller and less disclosed sample than the CallRail or Invoca figures elsewhere on this page, and the weighting methodology isn't published in enough detail to audit. Included because no larger, better-sourced study breaking out call duration by channel was identified in the sources reviewed on 8 September 2026 — treat the direction (organic and paid search calls run longer than third-party-lead calls) as more trustworthy than the exact minute-and-second figures.
| Device | Average call duration |
|---|---|
| Desktop | 5m 35s |
| Mobile | 4m 18s |
| Tablet | 3m 42s |
Same caveats as the channel table above apply — a single agency's client base, over a roughly four-month collection window, with an undisclosed weighting formula. Source: Focus Digital, Average Call Duration by Channel & Industry report
What this means, held at arm's length
No substantial, independently verifiable study segmenting call duration or outcome specifically by industry was identified in the sources reviewed on 8 September 2026.
The only channel- and device-segmented duration data available comes from a single agency's own client accounts rather than a platform vendor measuring its full customer base, which is a real step down in credibility from the CallRail and Invoca figures elsewhere on this page. The grading rules behind that judgement are set out in our research methodology.
The pattern is directionally plausible — a call arriving through organic or paid search follows a search someone typed with a specific need in mind, which plausibly produces a longer, more substantive conversation than a call bought as a third-party lead the caller may be comparing against several other businesses simultaneously. But it should be read as suggestive, not as a benchmark to plan around.
Where this page can't answer a question with confidence, that gap is worth stating rather than filled with a number that only looks precise.
AI assistants are starting to drive phone calls directly, not just website clicks
This site's local conversion rate statistics page already shows AI-assistant referral traffic out-converting most channels on website visits. The same Invoca report measures a related but distinct thing: calls that Invoca's tracking attributes specifically to a referral from ChatGPT, and what happens to them once answered.
49%
Grade Cof answered calls referred from ChatGPT become a lead — roughly 10 percentage points above the all-channel average lead rate in the same report.
What it does not say Graded down from the report's other B-grade figures specifically because the underlying ChatGPT-referred call volume isn't disclosed — the report itself states generative-AI-referred call volume remains 'very low' in absolute terms, which means this percentage, however real, is measured against a small and likely fast-changing base. A promising early signal, not yet a stable benchmark.
40%
Grade Cof ChatGPT-referred calls convert once answered — described in the report as roughly average, about 3 percentage points below the top-performing channels measured.
What it does not say Read alongside the 49% figure above: ChatGPT-referred callers convert to a lead unusually often, but don't then close on the call at an above-average rate — consistent with a caller who arrived pre-qualified by whatever the AI assistant told them, but who still negotiates or compares once a human answers, the same as a caller from any other channel.
What this means, and why it's graded more cautiously than the rest of this page
Two things can be true about this finding at once: it's the first dated, named-vendor data this page's research turned up that isolates AI-assistant-referred phone calls specifically, rather than website visits — and it describes a channel so new that Invoca's own report calls its total volume "very low".
This site's local conversion rate statistics already show AI-assistant referral traffic out-converting most established channels on website visits; the finding here is a different but consistent signal from the same shift, measured on phone calls instead.
A 49% lead rate on a small, fast-growing base is real evidence of something, but not yet the kind of evidence a business should reallocate budget against. The honest reading is that AI assistants are beginning to send phone calls as well as web traffic, that the calls arriving this way look pre-qualified when they do arrive.
The volume is not yet large enough for this specific figure to behave like the more established channel benchmarks elsewhere on this page.
Worth re-checking as the category matures rather than treating as settled — the wider picture of how AI assistants are reshaping local discovery is tracked on this site's AI and local search statistics page.
Dynamic Number Insertion tells you which channel produced a call — the accuracy of that claim isn't independently measured by anyone reviewed for this page
Every channel-attribution figure on this page depends on Dynamic Number Insertion (DNI): software that swaps the number shown on a page for a unique tracking number per visitor, so an inbound call can be matched back to the campaign that produced it. What the technology can and can't actually verify is worth separating from the vendor benchmarks it produces.
UTM parameters, Google Click ID, keyword, landing page, referrer
Grade Cis the digital context Invoca's own description of its DNI technology says gets captured and attached to a call record when a visitor calls a dynamically-inserted number.
What it does not say This is a mechanism description from the vendor selling the technology, not an independent measurement, and it isn't dated — included because it's the clearest available account of what DNI actually captures, not as a benchmark figure. Invoca's own page separately claims 'heartbeat technology that actively monitors each website session for inactivity and quickly returns phone numbers of inactive sessions to your pool for reuse', addressing the practical constraint that a finite pool of tracking numbers has to be recycled across visitors without two different callers colliding on the same number.
What DNI attributes and what a call-tracking platform counts as a conversion are two separate mechanics, and conflating them is a common source of confusion when comparing numbers across tools.
Google's own Google Ads documentation states plainly how the platform decides a call is a conversion at all: for calls placed from ads or to a tracked website number, "you set a minimum call length, and every call that lasts at least that long is counted as a conversion" — a fixed duration threshold the advertiser controls.
For a click on a call button or ad asset, where no actual call duration exists to measure at the moment of the click, Google instead counts a conversion "based on Google's estimation of whether a meaningful phone call occurred after a person clicked your ad" — a modelled estimate, not a directly observed outcome.
Neither mechanic is DNI itself; DNI is the layer that decides which channel gets credited, and the duration threshold or modelled estimate is the separate layer that decides whether the call counted at all.
What isn't available, from any vendor or independent source reviewed for this page: a published accuracy or error rate for DNI attribution itself — how often a tracking-number pool reassigns a number to the wrong visitor, how attribution behaves across a session that spans multiple devices, or how call tracking's picture reconciles against a business's own CRM record of where a customer said they heard about it.
No substantial, sampled study measuring DNI attribution accuracy against a verified ground truth was identified in the sources reviewed on 8 September 2026. Every vendor whose benchmark data appears elsewhere on this page — CallRail, Invoca — publishes rich output from its own DNI system without publishing how accurate that system's underlying attribution actually is.
What this means for how much weight to put on a channel-attribution number
Channel-level call attribution is the best tool most local businesses have for connecting a phone call back to the marketing that produced it, and it's a real improvement over guessing or asking the caller "how did you hear about us" and trusting the answer.
It is not the same thing as a verified, audited measurement, and the same caution this site applies to unverifiable response-time claims applies here: treat a DNI-attributed channel breakdown as the most useful evidence currently available, not as ground truth with an error bar of zero.
Missed-call text-back is now a standard feature — the specific recovery-rate numbers attached to it don't survive a check
Given that 85% of missed callers don't call back, automatically texting them the moment a call goes unanswered is one of the more obviously sensible ideas in this category. The technology is real and widely sold. The specific performance statistics attached to it in current circulation are a different matter.
Automated missed-call text-back — a system that fires an SMS to the caller's number the moment a call goes unanswered, typically offering a booking link or asking what they need — is sold by most call-tracking and phone-system vendors serving local businesses, and the underlying logic is sound: it converts a missed call from a dead end into at least one more attempt at contact, without requiring a human to notice the miss and act on it.
The same reflex applied to messaging channels is covered in our WhatsApp lead generation guide.
That much is a reasonable inference from the 85% non-callback figure already established above, not a separate claim requiring its own study.
What this page's research could not verify is the specific effectiveness figures attached to the technology in current marketing content — a "93% of missed calls recovered within one minute" claim and a "$3,500 average monthly revenue recovered" claim both circulate widely, commonly attributed to Podium.
Checking directly against Podium's own published content found no page stating either figure with a sample, method or date attached. Both appear in the do-not-cite section below rather than as evidence on this page.
What this means for evaluating the technology on its own
The absence of a verified recovery-rate figure isn't evidence the technology doesn't work — the logic behind it is sound, and it costs a fraction of what most local businesses spend acquiring the call in the first place — a lead value calculator will usually settle that comparison faster than any vendor statistic.
It's evidence that the specific percentage a salesperson quotes to justify it hasn't been independently checked by this page, and shouldn't be repeated as measured fact until it can be traced to a real sample.
The honest position is that the mechanism is plausible and the technology is real, and the number attached to it is not currently verifiable — a business considering it can reasonably judge the idea on the 85% figure and the cost of the tool, without needing an unverified recovery-rate percentage to make the decision.
What the evidence covers
CallRail's and Invoca's customer bases and datasets are predominantly US-based, and neither report discloses an international breakdown. Call-handling and phone-lead behaviour in markets where messaging apps like WhatsApp carry more discovery and communication load may differ substantially — see our WhatsApp Business statistics for that separate picture.
The numbers that did not survive the trace
These appear in current statistics roundups. Each one fails on provenance, and quoting them transfers the failure to you.
93% / $3,500
Do not cite93% of missed calls can be recovered with an automated text-back within 1 minute, generating $3,500 in additional average monthly revenue, attributed to 'Podium Customer Data' and 'Podium Business Impact Data'.
Traced to Repeated across current missed-call statistics roundups (e.g. a 2026-dated compilation citing both figures separately to Podium), with no working link to a Podium-published page stating either number.
Checked directly against Podium's own site for this page: no page stating a 93% recovery rate or a $3,500 monthly-revenue figure, with a sample size or method attached, was found. Podium is a real vendor selling real missed-call text-back technology, and the underlying idea — that texting a missed caller recovers some of them who would otherwise never call back — is plausible given the genuine 85% non-callback figure documented above. But a plausible mechanism is not the same as a checked statistic, and neither number survives a direct check against the source it's attributed to.
10–15×
Do not citephone calls convert to revenue 10 to 15 times more often than web leads, repeated across current call-tracking marketing content including Invoca's own blog, with no source attached in its current form.
Traced to Traces to Convirza (formerly LogMyCalls), reported via a Conversion Sciences blog post dated 3 July 2012, alongside three small email-campaign case studies from the same era.
The figure is genuinely traceable, unlike most zombies on this site's other statistics pages — the problem is entirely the date. A single data point from 2012, sourced from a call-analytics vendor that no longer operates under that name, describing phone-versus-web conversion behaviour from over a decade before smartphone click-to-call, DNI and mobile search became the norm they are in 2026, is still being restated in current marketing content — including on Invoca's own blog, in an undated article — with no year attached and no caveat that the underlying comparison is fourteen years old. Whether the multiple still holds is plausible but unverified: no current, dated study reproducing this specific comparison was identified in the sources reviewed on 8 September 2026.
108 billion
Do not citemobile search, social and display ads will drive over 108 billion phone calls to US businesses 'this year', attributed to BIA/Kelsey.
Traced to Cited via Invoca's own DNI explainer blog post, itself undated, attributing the figure to BIA/Kelsey without a publication year or a link to the original BIA/Kelsey report.
BIA Advisory Services (BIA/Kelsey) is a real analyst firm that has published genuine call-volume forecasts in the past, which is why this figure isn't dismissed outright — but 'this year' with no year stated, in an undated secondary citation, is unusable on a page that requires the date of the underlying data, not just the date it happens to be read. BIA/Kelsey's own site could not be reached to verify the original figure or its vintage during this page's research on 8 September 2026. Until a dated original turns up, this number is repeated everywhere and verifiable nowhere.
How this page is made and how to cite it
Figures were traced directly to CallRail's and Invoca's own published reports and report announcements. The core missed-call and channel-share figures are graded A as genuine, large-scale platform data from vendors with direct measurement capability and no obvious incentive to distort the specific findings reported.
Newer figures — duration-conditioned answer rates, AI-referral call data, and a smaller agency-run duration study — are graded B or C where the underlying sample is smaller, less disclosed, or where a vendor's own commercial interest in the finding is more directly present, consistent with the grading legend above.
Last verified: 8 September 2026. Reviewed quarterly, and re-checked in full if CallRail or Invoca publish an updated edition.
Preferred citation Parashar, S. (2026). Call tracking and phone lead statistics, traced to source. shrutiparashar.com/statistics/call-tracking/
Questions
- What happens when a business misses a customer's call?
- Most of the time, nothing further — 85% of callers whose call goes unanswered simply don't call back, per CallRail's analysis of 1.1 million leads across seven industries (2024 data, published January 2025). This is genuine platform data from a vendor whose core business is measuring call outcomes.
- Which industries miss the most calls?
- Healthcare had the highest missed-call rate at 32% in CallRail's dataset, more than triple home services' rate of 14%, with legal at 28% and real estate at 9%. The gap between industries is large enough to suggest call-handling capacity, not just call volume, is a genuine differentiator.
- Which marketing channels actually produce phone calls, not just clicks?
- Google Ads (37%), Google Business Profile (23%) and organic search (22%) consistently topped CallRail's channel breakdown across every industry studied — together accounting for roughly 82% of tracked conversations in the dataset.
- Does the channel that drives the most calls also drive the best ones?
- No, and the gap is one of the more useful findings on this page. In CallRail's data, Google Ads produces 47% of qualified leads against only a 37% share of raw tracked conversations — it converts disproportionately well. Google Business Profile does the opposite at the top of the funnel (23% of conversations, 15% of qualified leads) but recovers at the booking stage, producing 32% of appointments. Organic search is the one channel where its appointment share (18%) trails its conversation share (22%), which points to its follow-up process, not its traffic, as the weaker link.
- How long does a call need to last before it's likely to be a genuine enquiry?
- Invoca's 2026 benchmark report, built from 70 million+ calls, found the overall answer rate across all industries is 56% — but filtering to calls lasting over 15 seconds (removing misdials and instant hang-ups) raises that to 65%, and restricting to calls over 30 seconds raises it to 71%. A short call disappearing from a business's log isn't necessarily a missed genuine enquiry; a longer one connecting is more reliably one.
- Do businesses actually ask for the sale once a call connects?
- Often not, per the same Invoca report: 64% of businesses don't ask leads to buy or book an appointment on calls that do get answered. Fixing an answer rate only pays off if the calls that connect are then worked properly — a call-tracking platform that records and reviews calls is the practical way to check this.
- Are AI assistants like ChatGPT starting to drive phone calls to local businesses?
- There's an early, dated signal that they are. Invoca's 2026 report found that answered calls referred from ChatGPT convert to a lead at 49% — about 10 percentage points above the all-channel average — though the report itself notes total generative-AI-referred call volume remains 'very low', so this is a promising early figure rather than a stable benchmark yet.
- What is Dynamic Number Insertion (DNI) and how accurate is it?
- DNI is the technology behind every channel-attribution figure on this page: software that swaps the phone number a visitor sees for a unique tracking number, so an inbound call can be matched back to the campaign, keyword or referrer that produced it. No published, independently verified accuracy or error-rate figure for DNI attribution — how often a number is attributed to the wrong session, for example — was identified in the sources reviewed on 8 September 2026. It's the best attribution tool most local businesses have access to, not an audited measurement with a known error bar.
- Does missed-call text-back software actually recover most missed calls?
- The idea is sound given how many callers never call back, but the specific '93% recovery rate' and '$3,500 average monthly revenue' figures widely attributed to Podium in current marketing content could not be verified against Podium's own published pages during this page's research. Treat the technology as a plausible fix worth its low cost, and treat the specific recovery percentage attached to it as unverified until it can be traced to a real sample.
- Is it true that phone calls convert 10 to 15 times more often than web leads?
- That specific multiple traces to a single 2012 data point from Convirza (formerly LogMyCalls), reported via a Conversion Sciences blog post — fourteen years old, from before smartphone click-to-call and modern dynamic number insertion were standard. It's still repeated in current marketing content, including on Invoca's own blog, with no date attached. It may be directionally true that calls convert better than web forms, but no current, dated study reproducing this specific multiple was identified in the sources reviewed on 8 September 2026.
Related reading: how each grade on this page was assigned , Lead response time statistics , local business conversion rate statistics , Home services marketing statistics .
Every figure here is graded the same way as the rest of the research archive — source, sample, method and date.
