The after-hours cliff is real,
and here is its size.
We called the same 100 Southern California senior living communities three times in one week. On a Wednesday morning, 77.3% of calls reached a live person. On Tuesday night, 60.8% did. On Sunday night, 53.6% did.
On that Sunday night, 16 calls rang for at least six rings or 30 seconds with nobody answering and no voicemail picking up in that window. Two more were busy lines, corrected after a second-phone check. Another 8 reached a phone menu with no way to a person. Across all 300 calls, an AI agent answered 0.
Those counts were added to the analysis after the results were known. The deviation log records it as DEV-018. The registered headline number is the live-person share above.
The 100 were drawn at random, by a public lottery number, from all 428 licensed communities with 36 to 150 beds in eight Southern California counties.
77.3%
Reached a live person, Wednesday 10 AM to noon
60.8%
Reached a live person, Tuesday 8 to 10 PM
53.6%
Reached a live person, Sunday 8 to 10 PM
23.7 pts
Gap, the same communities, Wednesday morning against Sunday night
Conflict of interest
Elevyr sells Sloane, an AI admissions agent that answers phone calls for senior living communities around the clock. A poor after-hours number helps us sell it. That is why every rule for this study was registered in public before the first call, why the headline was written in advance for every possible result and why the call-level data is below for anyone to check.
The short version
How often does a senior living community answer the phone after hours?
In this Southern California sample, about half the time on a Sunday night, against roughly three calls in four on a weekday morning.
- Weekday morning: 75 of 97 calls reached a live person (77.3%). Sunday night: 52 of 97 did (53.6%).
- The same communities, compared with themselves: 30 answered on Wednesday morning but not on Sunday night. Only 7 went the other way.
- The hour matters more than the weekend. Tuesday night (60.8%) looked much like Sunday night. Both fell well short of the morning.
- Answering and helping are different things. On Sunday night, only 55.8% of the people who picked up could say whether the community was taking new residents. On Wednesday morning, 84.0% could.
- Nobody answered with AI. Not one community, on any night.
- Why 97 calls, not 100: 3 of the listed numbers were disconnected every time we called, so each night’s share is out of the 97 numbers that worked.
A human answering service counted as a live person. So did a receptionist who could not answer a single question. A voicemail, a phone menu that never reached a person and an AI voice all counted as no. The rules were fixed before anyone dialed, and the registration is public on OSF.
If you run a smaller home
If you run a six bed board and care home, this page can read like an accusation that nobody answers your phone. It is not about your home. Every community in this study had 36 to 150 beds, and nothing smaller was in the draw.
The closest the data comes is the smaller half of the sample, 36 to 80 beds. On Wednesday morning it reached a person on 70.6% of calls, against 81.0% for 81 to 150 beds. On Tuesday night it was 52.9% against 65.1%. On Sunday night the gap vanishes: 52.9% against 54.0%.
These groups are small and their ranges are wide. The protocol labels every subgroup descriptive, with no significance test, so none of this shows that smaller communities answer less. What it cannot tell you is what happens when a family calls your own number on a Sunday night. Do you know?
What share of calls reached a live person each night?
Share of calls to working numbers that reached a live human. The range is a 95% Wilson interval with a finite population correction, as registered. Each session dialed all 100 communities. 3 numbers were disconnected every time, so each share is out of the 97 numbers that worked.
| Session | Reached a person | Calls | Share | 95% range |
|---|---|---|---|---|
| Wednesday, 10 AM to noon | 75 | 97 | 77.3% | 69.1% to 83.5% |
| Tuesday, 8 to 10 PM | 59 | 97 | 60.8% | 52.1% to 68.8% |
| Sunday, 8 to 10 PM | 52 | 97 | 53.6% | 44.9% to 62.0% |
The study is powered to detect a large gap. It is not powered to estimate a precise rate. Each night’s share carries a range several points wide, printed next to it. The comparison below is the stronger result.
What this means: Even on an ordinary weekday morning, about one call in four reached no one. On a Sunday night it was closer to one in two.
Did the same communities answer less on Sunday night?
Yes. This is the main test, and it compares each community with itself. 30 communities reached a person on Wednesday morning and not on Sunday night. 7 went the other way. Everything else was the same both times.
That is a gap of 23.7 percentage points, with a 95% range of 12.1 to 35.1 points. An exact McNemar test gives p = 0.00019. A community that was reachable by day was often unreachable on a Sunday night, and the reverse was rare.
| Same community | Sunday: person | Sunday: no person |
|---|---|---|
| Wednesday: person | 45 | 30 |
| Wednesday: no person | 7 | 15 |
What this means: The drop happened inside the same buildings. Many communities that picked up on a weekday morning did not pick up on a Sunday night.
The two bold cells are the whole test. Anyone can recompute it from them by hand. Pairs where either number was out of service are left out: 3 communities.
Is it the hour or the day of the week?
The hour. Tuesday night exists in this study to answer exactly this. Wednesday morning against Tuesday night changes only the hour. Tuesday night against Sunday night changes only the day.
| Comparison | Person first time, not second | The reverse | Gap (points) | 95% range | p |
|---|---|---|---|---|---|
| Wednesday morning vs. Tuesday night (the hour) | 22 | 6 | 16.5 | 6.2 to 27.0 | 0.0037 |
| Tuesday night vs. Sunday night (the day) | 19 | 12 | 7.2 | -4.2 to 18.6 | 0.28 |
Moving from morning to night costs a clear share of calls. Moving from Tuesday night to Sunday night may cost a little more, but the range crosses zero, so this study cannot tell a Sunday night from any other weeknight. Both of these are registered secondary comparisons.
What this means: Any evening is the problem, weekday or weekend. This study measured two evening windows and one morning. It did not measure early evening, Saturday or overnight, so it cannot say how those hours compare. Nothing here suggests they look like the morning.
When a person answered, could they help?
The caller asked one question of every person who answered: are you taking new residents? At night, close to half of the people who picked up could not say.
| Session | People who answered | Could say whether taking residents | Share | 95% range |
|---|---|---|---|---|
| Wednesday, 10 AM to noon | 75 | 63 | 84.0% | 75.1% to 89.6% |
| Tuesday, 8 to 10 PM | 59 | 31 | 52.5% | 41.6% to 63.2% |
| Sunday, 8 to 10 PM | 52 | 29 | 55.8% | 44.0% to 66.8% |
This is a softer measure than the main result. It depends more on what the caller heard and how the caller judged it, and the people who designed the study have a stake in it. Read it second.
What this means: Picking up is only half the job. At night, a family that did reach a person often still could not learn the one thing it called to ask.
Where the person was
We asked this only when the person who answered could not tell us whether the community was taking new residents. Across the three nights that was 63 of the 186 people who answered. Of those 63, 59 said they were at the community, 4 were unsure and none said they worked for an answering service. The other 123 could answer the residents question, so they were never asked where they were, and a scripted answering service among them would not show up here. Answering services also often pick up in the community’s own name. This study cannot tell you how many communities use an answering service after hours. It does not change the main result, because a live person counts as a yes whether they work on site or for a service.
| Session | Could not help, said at the community | Could not help, not sure | Said answering service |
|---|---|---|---|
| Wednesday, 10 AM to noon | 11 (14.7%) | 1 (1.3%) | 0 (0.0%) |
| Tuesday, 8 to 10 PM | 26 (44.1%) | 2 (3.4%) | 0 (0.0%) |
| Sunday, 8 to 10 PM | 22 (42.3%) | 1 (1.9%) | 0 (0.0%) |
Shares are of the people who answered that session.
Did any community answer with an AI voice agent?
No. On every night, 0.0% of calls were answered by a conversational AI. The upper end of the 95% range is 3.6%, so AI answering is at most rare in this sample. Because nothing answered with AI, the registered companion number, calls handled by anyone human or AI, is the same as the main result: 77.3% on Wednesday, 60.8% on Tuesday and 53.6% on Sunday.
What this means: In this sample, no community has filled the after-hours gap with software yet. The analysis plan named this outcome before the first call: a result near zero is a white-space finding. It describes where the market is today. It says nothing about whether AI answering works.
Did size, price or our own prospect list make a difference?
The three subgroups registered in advance, and only those. Splitting a sample of 100 leaves small groups with wide ranges, so these are descriptive only, with no significance test.
Licensed beds
| Group | Wednesday: share (range, calls) | Tuesday: share (range, calls) | Sunday: share (range, calls) |
|---|---|---|---|
| 36 to 80 beds | 70.6% (55.6% to 81.4%, 34) | 52.9% (38.7% to 66.6%, 34) | 52.9% (38.7% to 66.6%, 34) |
| 81 to 150 beds | 81.0% (70.8% to 87.6%, 63) | 65.1% (54.2% to 74.3%, 63) | 54.0% (43.3% to 64.2%, 63) |
Published starting rate, from the community’s own website
| Group | Wednesday: share (range, calls) | Tuesday: share (range, calls) | Sunday: share (range, calls) |
|---|---|---|---|
| $6,000 a month or more | 71.4% (39.3% to 88.3%, 7) | 42.9% (19.5% to 71.3%, 7) | 42.9% (19.5% to 71.3%, 7) |
| Under $6,000 a month | 80.0% (62.7% to 89.3%, 25) | 72.0% (54.5% to 83.7%, 25) | 56.0% (39.3% to 71.1%, 25) |
| No rate published | 76.9% (66.6% to 84.2%, 65) | 58.5% (47.8% to 68.2%, 65) | 53.8% (43.3% to 64.0%, 65) |
Operator appears in Elevyr’s own prospect list (a check on us, not a finding)
| Group | Wednesday: share (range, calls) | Tuesday: share (range, calls) | Sunday: share (range, calls) |
|---|---|---|---|
| On the list | 83.3% (70.8% to 90.3%, 42) | 64.3% (50.9% to 75.3%, 42) | 64.3% (50.9% to 75.3%, 42) |
| Not on the list | 72.7% (61.2% to 81.3%, 55) | 58.2% (46.6% to 68.7%, 55) | 45.5% (34.6% to 56.9%, 55) |
One flag, reported as a flag. Communities whose operator appears in Elevyr’s prospect list reached a person more often on Sunday night than the rest. The prospect list leans toward higher-priced operators, which is why this check was registered. The groups are small and their ranges overlap, so it points at the sample, not at a finding.
What this means: Every one of these groups reached a person less often on Sunday night than on Wednesday morning. Size and price did not make the gap go away, and no group is large enough to rank against another.
What else the calls showed
Numbers that no longer work
3 of 100 listed numbers were out of service in every session, after a second-phone check. They are the only calls left out of the results, which is the one exclusion the protocol allows.
Who ended the unanswered calls
A skeptic’s first question is whether the caller hung up too soon. The rule was six rings or 30 seconds. On Sunday night, 27 of the 45 unanswered calls ended because the community’s own phone system sent the call to voicemail or a menu before the rule applied. The caller ended 16. On Tuesday night the split was 22 and 16, and on Wednesday morning 11 and 10. The rest are the corrected calls from the second-phone check, which have no ending recorded.
That rule bound far more often than we planned for. Protocol 4.3 expected 90% or more of unanswered calls to end with the community’s phone system rolling over on its own. The phone system ended 60.0% of them on Sunday night, 57.9% on Tuesday night and 50.0% on Wednesday morning. So a call that rang out here means nothing picked up within six rings or 30 seconds. It does not mean the community had no voicemail, and this study cannot say what a longer wait would have reached. It changes the main result only if a person would have answered after the limit.
How long an answered call took
The median answered call ran 44 seconds on Wednesday, 50 on Tuesday and 55 on Sunday. That is measured from the start of the call to the moment the result was logged, so it includes ringing and overstates the time anyone at a community spent on the phone.
Did the checks change the answer?
Two sensitivity analyses were committed to in advance. Dropping the calls corrected after the second-phone check gives the figures from before the correction. Dropping the second call to each of two phone lines shared by two licenses leaves every conclusion in place: the Wednesday against Sunday gap stays clear, and no night moves by a meaningful amount. We describe that one in words because its exact figures would reveal how those two specific lines were answered. Both are in the deviation log below.
What this study does not show
It covers Southern California only. Whether the rest of the state or the country looks the same is unknown, and nothing here claims it does.
Licensed beds are not luxury. The frame is every licensed residential care community in eight Southern California counties with 36 to 150 beds. Size says nothing about price or private-pay mix. Price appears only as a subgroup, read off each community’s own website.
The number we dialed may not be the number a family would dial. The state roster lists each license’s phone number of record, which can differ from the number a family finds by searching. We kept the roster number, because swapping in a search result would put our own judgment back into a mechanical sample.
The roster is dated May 25, 2025, the newest file the state publishes. Some communities have since closed or changed hands. Dead numbers are counted and reported, not hidden.
One caller placed every call and was paid by Elevyr. The caller was never told what we expected to find, and the main outcome, whether a person spoke, leaves little room for judgment. There are no recordings to audit, by design, because California requires two-party consent to record.
Every community heard from the same number three times in four days, in the same order: Sunday, Tuesday, then Wednesday. That number was new, and Google’s spam filter labeled it on some phones. A label could lower pickup, but it was the same on every night, so it cannot explain the gap between nights. If anything, communities that learned to ignore the number would hurt Wednesday, the last session, which shrinks the gap rather than inflating it.
Sunday’s calls were placed in the right window but followed Wednesday’s dial order (DEV-012). The order within a session only spreads calls across the evening, so this is disclosed rather than treated as fatal.
Everything rests on one field week. A single unusual week would move every number together. The week was chosen to avoid holidays.
Every change from the registered plan
A study with no logged deviations is less believable than one that shows its work. Each line below is summarized. The full log is published word for word, with community names, numbers and the caller’s name withheld. Read the full deviation log.
| Entry | Date | What changed |
|---|---|---|
| DEV-001 | 2026-07-31 | The caller changed from a blind contractor to the study’s designer, after two contractors went unresponsive. Superseded by DEV-005 before any call. |
| DEV-002 | 2026-07-31 | Field week moved for lack of a caller. Same seed, same sample, same dial order. |
| DEV-003 | 2026-07-31 | Calling line set to a free Google Voice number with recording off. Superseded by DEV-007. |
| DEV-004 | 2026-08-02 | Field week moved again because the caller could not field the session. Same seed, same sample. |
| DEV-005 | 2026-09-20 | The caller changed to a paid research assistant who is not the designer and was never told the hypothesis. |
| DEV-006 | 2026-09-23 | Field week moved to the week of September 27. Same seed, same sample, covariate file unchanged. |
| DEV-007 | 2026-09-24 | Calling line moved to a paid Quo number with recording off. Google’s filter labeled the new number as spam on some phones. |
| DEV-008 | 2026-09-24 | Coding rule added before any call: an automated call screener is not an answer. |
| DEV-009 | 2026-09-24 | Two pairs of sampled communities share one phone line. Kept as drawn, with a pre-committed sensitivity check. |
| DEV-010 | 2026-09-24 | Price covariates coded from each community’s own website and frozen before any call, with five reading rules written down. |
| DEV-011 | 2026-09-25 | Coding rule, a post-field check and two sensitivity analyses added before any call, so a blocked call could not be miscounted as a dead number. |
| DEV-011 check | 2026-09-30 | The post-field check, run from a second phone. Three lines were confirmed dead. Two returned a busy signal and were corrected to no-answers. |
| DEV-012 | 2026-09-28 | Sunday’s session was run on schedule but logged under Wednesday’s label and dial order. Relabeled in a copy; the original is kept untouched. |
| DEV-013 | 2026-09-30 | The call logger never recorded ring counts or phone menu depth, and its call length covers the whole call. No main result uses those fields. |
| DEV-014 | 2026-09-30 | Tuesday’s export was not committed to version control at the end of its session. It matches its own automatic backup and the schedule exactly. |
| DEV-015 | 2026-09-30 | When a count is zero, the lower end of its range is shown as 0.0% instead of the value the registered formula gives. |
| DEV-016 | 2026-09-30 | A busy signal on the post-field check is read as a connected line, and correction rows replace the rows they correct in the analysis input. |
| DEV-017 | 2026-09-30 | The public data file withholds three registered columns, because with them a reader could trace some communities to their own results. |
| DEV-018 | 2026-10-02 | Plain counts added to the analysis output after the results were known: how each unanswered call ended, how often the phone system ended it, and who was asked the answering-service question. No existing number changed. |
Check our work
Everything needed to rerun the draw and the analysis is here. No email, no form.
- The call data (CSV). One row per call. Rows are shuffled and community numbers are reassigned, so no row can be tied to a named community. Three registered columns are withheld for the same reason (DEV-017), so the price and prospect subgroups above cannot be rerun from this file. Every other number on this page can.
- analyze.js, the analysis script registered before the first call. Every number on this page comes from its output.
- The analysis output (JSON), exactly as analyze.js wrote it.
- 00-draw.js, which draws the sample from the state’s public roster. The registered seed is 0203102737, the five white balls of the California SuperLotto Plus draw held after the study was registered, so nobody could pick the sample in advance.
- The full deviation log.
How the study was designed, and every rule that was fixed before the first call, is on the method page and in the OSF registration. For more original data on the same industry, see California senior-care bed loss by county.
From Elevyr, not from the study
What we built for the calls nobody answers
Everything above this line is measured. This section is our view, and we sell the product in it.
Sloane is an AI admissions agent. It answers every call to a community, at any hour, every day of the year. It answers the questions a family asks first, including whether the community is taking new residents, and it books the tour on the community’s own calendar. On a Sunday night in this study, 53.6% of calls reached a person, and only 55.8% of those people could answer that first question.
“Nobody else is doing this” is a fair thing to notice, and the study confirms it. Nobody in this sample answered with AI. That means the gap is still open. A family calling at night compares your voicemail to whichever community picked up.
What a missed call costs depends on your own numbers: how many calls come in after hours, how many become tours and what a resident is worth to you. This study does not measure those, so we will not guess them here. The Voicemail Tax walks through the math, and the pricing page shows what Sloane costs for a community your size.
Corrections
If you find an error, write to ed@elevyr.com. Corrections are made on this page with a dated note, not quietly.
Cite this study
These results may be reproduced with attribution and a link. No permission form, no email required. No individual community is named anywhere in this study, and none will be.
Plain text
Elevyr, "The After-Hours Answer Study: Results," September 2026, https://www.elevyr.com/research/after-hours-results
HTML
<a href="https://www.elevyr.com/research/after-hours-results">Elevyr, "The After-Hours Answer Study: Results," September 2026</a>
Press and data requests go to ed@elevyr.com.
Sloane, our AI Admissions Agent for senior living, answers every call at any hour. That is the product this study could have been built to sell, which is exactly why it was built the hard way.