# The Wrong-Searcher Profile Retune, Read Week by Week to the Right Recruiters

*Take a no-edit baseline of your search appearances, trace a wrong-searcher mix to one profile field, and judge each Wednesday refresh as a real gain or inflation.*

- Canonical URL: https://www.refolk.ai/candidates/guides/wrong-searcher-profile-retune
- Pillar: Positioning and materials
- Format: Teardown
- Published: 2026-10-16
- Last reviewed: 2026-10-16
- Reading time: 22 min
- Keywords: linkedin search appearances wrong job titles, how to read linkedin search appearances, why are recruiters not finding my linkedin profile, linkedin profile showing up for wrong roles, how long for linkedin profile changes to show in search, get more relevant recruiter inmails linkedin

## Key takeaways

- LinkedIn refreshes search appearance data weekly on Wednesdays and shows only aggregated searcher titles and companies, so a retune is a one-reading-per-week experiment.
- An edit only counts as working when the share of target in-house searchers moves outside the min-max range of 2 to 3 no-edit baseline weeks.
- A rise in the appearance count while the target-searcher share stays flat or falls is inflation, and the usual cause is broad keyword text in the headline feeding implicit skills.
- In Refolk's index of professional profiles, 24.6% of US recruiter-titled people work at Staffing and Recruiting employers, so a broad edit drifting toward agency searchers is the expected base rate.
- Open to Work titles, which allow up to five, match your desired role regardless of your current title, so audit them before editing the headline.
- A location change from suburb to metro area cannot help while the title filter still excludes you, so fix the title match first.

This guide is for anyone whose LinkedIn profile does get found, just by the wrong people. The count looks healthy, but the searchers are agency sourcers hiring for titles you have moved past, and the in-house recruiter for the job you want never gets in touch. It follows one candidate's six-week retune from a no-edit baseline through three single-field edits, two of them wrong turns, and gives you the log, the field map and the decision rule to run the same loop on your own profile.

I describe each week of the worked example by where it lands against the baseline range, not by raw counts. Raw counts don't carry over between profiles. Position against your own baseline does.

## What does the LinkedIn search appearances page actually show?

The search appearances page shows how many times your profile was listed in search results over the past week, plus an aggregated view of who was searching and which titles you were found for. LinkedIn's help page says the data "is updated weekly on Wednesdays and you can access it via your notifications or email."

A **search appearance** is one listing of your profile in someone's search results. It is not a click. LinkedIn says plainly that the count "does not necessarily indicate that your searchers clicked through."

What the page gives you to work with:

- **The weekly count.** Listings in the past week.
- **Top searcher job titles.** The most common titles among people whose searches listed you.
- **Top searcher companies.** Where those searchers work.
- **Job titles you were found for.** The titles your profile matched on. For diagnosis, this is the most useful list on the page.

What it does not give you:

- **Individual searchers.** The page offers only "a high level overview of their companies and job titles."
- **Search keywords.** Some older third-party pages say keywords appear. LinkedIn's current help text doesn't mention them. If your page shows keywords, log them, but don't build a method that depends on them.
- **A documented free vs Premium split.** LinkedIn's help text ties Premium only to Who's Viewed Your Profile, which covers the last 90 days. Whether free members see a reduced version of search appearances is not publicly established. Write down what your own page shows on day one so later changes in the view don't get mistaken for changes in your results.

## Which profile fields do recruiter searches match on?

Recruiter searches match first on structured fields: job titles, location, companies, skills, schools, industries and spoken languages. Free text such as your headline and descriptions comes in through keywords and implicit skills. When a recruiter searches for a job title, the scope setting decides whether your current title, your past titles or your Open to Work titles count.

#### How a recruiter search reaches your profile

1. **Plain-English prompt** - AI-assisted search turns the request into job title, location and industry inputs
2. **Hard filters** - Job titles, Location, Companies, Skills, Schools, Industries, Languages, each set to Can have, Must have or Doesn't have
3. **Keywords and Skills Match** - Boolean in Job titles, Companies and Keywords; implicit skills pulled from headline, summary, title and descriptions
4. **Ranking** - Similarity of experience and skills, location, likelihood of a response; similar titles added when results run thin

*Your profile has to get through the hard filters before keyword hits and ranking can help it, so a wrong title match outweighs every other field.*

The mechanics that matter for diagnosis:

- **Title scope.** Recruiters can scope a title to Current or Past, Current, Past, Past not Current, or Open to work (that last one is Recruiter only). If your old title is still the strongest match on your profile, the "Current or Past" scope keeps you in those searches.
- **Open to Work titles.** You can pick up to five. One practitioner reports that the Open to Work title filter "does not look at current role. It looks at what the person has flagged as their next desired role."
- **Implicit skills.** Skills Match counts skills "extracted from text within any section of the member's profile, such as the summary, position description, title, and headline." LinkedIn says these "are not directly editable by the member." The only way to change them is to change the text they come from.
- **Same-country rule.** For Skills Match, "The member and the job must be in the same country, except for the European Economic Area."
- **Seniority.** One Recruiter filter guide says seniority is "Inferred by LinkedIn's algorithm, not self-reported."
- **Query expansion.** LinkedIn engineering says the system "adds results with semantically similar titles, like 'Software Developer' for 'Software Engineer,' when the number of returned results from the original query is too small." That is how a rare internal title gets padded into nearby searches for titles you never held.
- **Response likelihood.** Ranking weighs "the likelihood of a response from an interested candidate." This is the route by which job-seeking signals can outrank title fit.

Use the found-for list to point at a field:

| What the found-for list shows | Field most likely behind it | Check first |
|---|---|---|
| Titles you held years ago | Past titles under a "Current or Past" scope | Is your current title the market name for your target? |
| Titles you never held | Query expansion from a rare current title | Is the current title an internal label? |
| Your old role, though you have moved on | Open to Work titles or job alerts | All five Open to Work titles and your alerts |
| Broad skill terms, agency searchers | Headline and summary feeding implicit skills | Headline keyword density |
| Right titles, wrong geography | Location | Metro area rather than suburb or bare city |

Practitioners disagree about where to start. One checks the title first, then skills, then the wording of your experience. Another calls job alerts the "Most Common Cause" and starts with alerts and preferences. Both orders are cheap to check, so read both before you edit anything.

## Who is searching for you: the recruiter base rate

About one in four recruiter-titled people in the US works at an agency. That makes agency searchers the normal background, and you will always see some. What tells you something is a share that rises after an edit.

**24.6% - of US recruiter-titled profiles sit at Staffing and Recruiting employers**

In Refolk's index, 24,452 of 99,489 US profiles titled Recruiter, Talent Acquisition, Sourcer or Talent Partner work at staffing-industry employers.

| Segment | Profiles | Share |
|---|---|---|
| US, all industries | 99,489 | 100% |
| US, Staffing and Recruiting | 24,452 | 24.6% |
| US, non-staffing | 75,037 | 75.4% |
| UK, all industries | 8,084 | US has 12.3x as many |

*Source: Refolk's index. Titles matched: Recruiter, Talent Acquisition, Sourcer, Talent Partner. Shares and the ratio are derived.*

Which titles dominate also differs by market. The samples below are small (n=25 each), so read them as direction, not measurement.

| Title | US all | US staffing | UK all |
|---|---|---|---|
| Recruiter | 9 (36%) | 13 (52%) | 9 (36%) |
| Talent Partner | 2 (8%) | 2 (8%) | 7 (28%) |
| Talent Acquisition | not in top 10 | not in top 10 | 4 (16%) |
| Healthcare-specific recruiter titles | 0 | 3 (12%) | 0 |

*Source: Refolk's index sample output, top titles per segment. Percentages derived.*

How to use the two tables:

- **Plain "Recruiter" is ambiguous.** It is the top title in every segment and makes up more than half of the US staffing sample. On its own it proves nothing about who you are reaching.
- **"Talent Partner" leans in-house in the UK.** It appears 3.5x as often in the UK sample as in the US one. A UK searcher list heavy on Talent Partners plausibly means in-house teams. Given the sample size, confirm it with the company names.
- **Niche-specific recruiter titles point to agencies.** In the US, healthcare-specific recruiter titles turned up only in the staffing sample.

No documented method exists for telling agency from in-house in the aggregated lists. Career coach Dave Soteros suggests reviewing "Top companies your searchers work at" to spot staffing agencies. That is the best available check, with one caveat: industry tags apply to the whole employer, so open each company page and look at its job postings before you tag it.

**Searcher classification rubric**

```
TARGET IN-HOUSE: recruiter or talent title AND employer is in your target industry or company list AND its postings are for its own roles
AGENCY: employer industry is Staffing and Recruiting, OR its postings are for unnamed clients, OR the title names a niche ("healthcare recruiter")
PEER / NON-RECRUITER: searcher title is a practitioner or manager title, not a talent title
IRRELEVANT: anything outside your target function, geography or industry
UNSURE: log it, open the company page next refresh, and leave it out of the shares until it is resolved
```

*Tag every searcher title and company in each refresh. When the title and company disagree, the company tag wins.*

## The retune procedure, step by step

The retune is a weekly loop. You change one field, wait for a refresh whose whole window falls after the change, and judge the edit by whether your target-searcher share left its baseline range. Everything else in this guide supports this procedure.

#### The measure-and-attribute loop

1. **Take a no-edit baseline** - Record count, found-for titles, searcher titles and searcher companies across 2 to 3 Wednesday refreshes with no edits, ending with a min-max range for each.
2. **Classify the searchers** - Tag each searcher title and company as target in-house, agency, peer or non-recruiter, or irrelevant, and write the mix for each week.
3. **Trace the mismatch to one field** - Compare found-for titles against current title, past titles, headline, Open to Work titles, job alerts, skills, location and industry, and write down one hypothesised field.
4. **Edit that field only** - Change only that field, ideally just after a Wednesday refresh, and log the time with a before and after text snapshot.
5. **Wait for a fully post-edit reading** - Allow 1 to 3 refreshes and judge only from the first week that falls entirely after the edit.
6. **Decide keep, revert, or escalate** - Keep if the target in-house share moved outside the baseline range; treat a count rise with a flat or falling target share as inflation and revert.
7. **Move to the next variable** - Repeat the edit, wait and decide steps for the next field, one logged change per refresh cycle, roughly every 2 to 3 weeks in an active search.
8. **Check downstream signals** - Compare profile views and InMails against the mix change to learn whether the remaining problem is visibility or the click.

> **Rule:** One logged field per refresh cycle
>
> If two fields change before the same refresh, you can't tell which one moved the mix. One field, one timestamp, one verdict, then the next field.

**Weekly retune log entry**

```
REFRESH DATE (Wednesday):
FIELD CHANGED SINCE LAST REFRESH: none / [field name]
EDIT TIMESTAMP:
BEFORE TEXT:
AFTER TEXT:
WINDOW FULLY POST-EDIT? yes / no / unknown
APPEARANCE COUNT:            BASELINE RANGE: [min] to [max]
JOB TITLES FOUND FOR:
TOP SEARCHER TITLES:
TOP SEARCHER COMPANIES:
MIX: target in-house __ / agency __ / peer __ / irrelevant __ / unsure __
TARGET SHARE OUTSIDE BASELINE RANGE? above / inside / below
VERDICT: keep / revert / escalate / keep watching
NEXT HYPOTHESISED FIELD:
```

*One block per Wednesday refresh. Copy the found-for and searcher lists exactly as they appear on the page.*

## How long do LinkedIn profile changes take to show in search?

The only documented timing is LinkedIn's weekly Wednesday refresh. Re-indexing claims of 24 to 48 hours come from third parties with no sources. So the practical answer is to judge an edit from the first refresh whose whole week falls after it, and to expect to need two or three of those.

| Source | Claim | Sourced? |
|---|---|---|
| LinkedIn Help | Weekly, Wednesdays | Primary |
| rankln | Re-index 24-48h, count 7-10 days, sustained 3-6 weeks | Unsourced |
| StylingCV | Re-index about 48h | Unsourced |
| JuicedResume | Watch 2-3 weeks per edit | Practitioner |
| Quest Search | Edit every 2-3 weeks | Practitioner |

LinkedIn's only stated lag applies to external search engines, where "it can take several weeks for search engines to detect and display changes." That concerns your profile turning up in a web search, not in LinkedIn's own recruiter search. Don't mix the two up.

Nobody has published how much the count moves from week to week with no edits. One guide warns it "can swing widely with no change on your part," because it depends on how many people searched your terms that week. That is why the baseline exists. Your own no-edit weeks are the only noise floor you have.

#### Placing an edit against the Wednesday window

1. **Wednesday refresh** - Log the reading and close the verdict on the previous edit
2. **Same day** - Make the single edit and log its timestamp and text
3. **Following week** - Change nothing; the window now covers only post-edit days
4. **Next Wednesday** - First clean reading; compare against the baseline range
5. **One to two more weeks** - Confirm the shift holds before calling it real

*Editing right after a refresh makes the next window entirely post-edit, so the first reading you judge isn't diluted by pre-edit days.*

> **Note:** The window boundary is an inference
>
> LinkedIn says the count covers the past week but doesn't document exactly where the window starts and ends. The advice to edit just after a refresh is a precaution. If an edit lands mid-week, treat the next reading as mixed and judge from the one after it.

## The teardown: one candidate's six weeks

The worked example is a senior product manager at a payments company. She lives in a commuter suburb outside London and wants in-house Talent Partners at London fintechs, people hiring senior product managers, to find her. What she had was a busy page, and almost all of it was the wrong people.

### Weeks 1 and 2: baseline, no edits

Two refreshes with no edits. Two is the minimum. A third would have been better, and the plan ended up producing a third baseline-like reading by accident (see week 4).

- **Found-for titles.** Product Owner, Scrum Master and Business Analyst. Senior Product Manager was missing.
- **Searcher titles.** Mostly plain "Recruiter", with a few contract and delivery-recruiter titles and a few peers. No Talent Partners.
- **Searcher companies.** Mostly staffing and contract agencies, which she confirmed by opening each company page and checking whether its postings named clients.
- **Count.** It moved between the two weeks with nothing changed, which set a min-max range for the count and another for the target share. The target share sat near the bottom in both weeks.

### Diagnosis

She checked both orders the sources suggest. First she audited job alerts and all five Open to Work titles. They already listed only senior product manager variants and had no Product Owner alerts, so they were ruled out. Then she looked at the title. Her current title was the company's internal label, "Product Owner II". Rare internal titles get padded into similar-title searches by query expansion, and the found-for list matched that exactly. **Hypothesis: the current title.**

### Week 3: the wrong turn on the headline

She didn't edit the title first. The ranking checklists all lead with the headline, so she rewrote hers as a long string of skill keywords: product strategy, roadmapping, agile, payments, stakeholder management and more.

- **Count:** well above the baseline maximum. Read alone, it looked like a breakthrough.
- **Mix:** the agency share rose. Most of the new searchers were sourcers with generic titles. The target in-house share didn't rise and, as a share, fell slightly.
- **Found-for titles:** unchanged. Still Product Owner and its neighbours.
- **Why:** headline text feeds implicit skills and Keyword hits. Those widen broad searches without changing what the title filter admits. With roughly one in four US recruiter-titled people sitting at staffing employers, broad keyword searches come mostly from agencies, and that is the pool she had widened into.
- **Verdict:** inflation. Revert.

> **Watch out:** A bigger count was the wrong turn
>
> The keyword headline produced the highest count of the six weeks and the worst searcher mix. Ranking pages claim multipliers such as "27x more recruiter searches" for listing five or more skills, with no published source, and they all measure the count, not who is searching.

### Week 4: revert, and a third baseline

She restored the original headline right after the week 3 refresh and changed nothing else. The week 4 reading came back inside the baseline range for both count and mix. That confirmed the inflation came from the headline and gave her a third no-edit-equivalent week, which widened her baseline range a little.

### Week 5: the location change that did nothing

Next she followed advice written for recruiters, which says to use "the metropolitan area rather than the bare city name", and changed her location from the suburb to the London metro area.

- **Count:** inside the baseline range.
- **Mix:** inside the baseline range. The same agencies, still no Talent Partners.
- **Why:** the title filter comes first in the recruiter's workflow. In-house searches for senior product managers in London were excluding her on title before location was ever checked. Fixing the location didn't matter while the title filter kept her out.
- **Verdict:** escalate. She kept the change, because metro is correct regardless, and moved to the field the diagnosis had named in the first place.

### Week 6: the current title

She changed the current title from "Product Owner II" to "Senior Product Manager", the wording used by the target postings she had saved. The internal label stayed in the role description so the history still read accurately.

- **Found-for titles:** Senior Product Manager and Product Manager appeared. Scrum Master dropped out.
- **Searcher titles:** Talent Partner appeared for the first time, alongside fewer contract-recruiter titles.
- **Searcher companies:** London fintech and payments employers appeared. She tagged them in-house after checking that their postings were for their own roles.
- **Count:** within the baseline range, not above it.
- **Mix:** the target in-house share rose above the baseline maximum for the first time.
- **Verdict:** keep, and confirm over the next one or two refreshes.

> The best week of the six had an ordinary count and the right searchers.

| Week | Change in force | Count vs baseline | Target in-house share | Verdict |
|---|---|---|---|---|
| 1-2 | None | Sets range | Sets range, low | Baseline |
| 3 | Keyword headline | Far above | Flat to down | Inflation, revert |
| 4 | Headline reverted | Inside | Inside | Baseline confirmed |
| 5 | Location to metro | Inside | Inside | No effect, escalate |
| 6 | Current title fixed | Inside | Above range | Keep, confirm |

### What the teardown can't tell you

- **Location and title are confounded.** The location change was still in force when the title fix landed. The title fix probably did the gating and the metro location probably helped the London searches, but separating the two would mean reverting location for a cycle. She decided that wasn't worth a lost week.
- **One post-edit week per edit is the minimum.** Practitioners suggest watching each edit for two or three weeks. The six-week pace traded certainty for speed, which is why week 6 is marked "confirm", not "done".
- **Downstream results come later.** One week of InMails is too thin to judge. Step 8 starts after the mix holds.

Choosing the new title meant reading her saved postings for the wording in-house teams actually use. [Refolk](/candidates) scores how well your history fits each posting you apply to, which is a quick way to see whether the title you're about to put on your profile matches the roles you are targeting.

## Reading a refresh: did the edit move the mix or just the count?

An edit worked if the share of target in-house searchers moved outside your baseline range. What happened to the count doesn't settle it. Put each refresh in one of four quadrants and act on that.

#### Reading a post-edit refresh

Horizontal axis runs from Count inside baseline range to Count above baseline range. Vertical axis runs from Target share inside baseline range to Target share above baseline range.

| Quadrant | What it means |
| --- | --- |
| Precision gain | Keep the edit; the right searchers came without extra noise |
| Real reach gain | Keep, then check views and InMails to make sure the click follows |
| No effect | Revert or keep if harmless, then escalate to the next field |
| Inflation | Revert; the edit broadened you into agency or irrelevant searches |

*Only a target share outside the baseline range counts as a win, and a rising count with a flat target share means you broadened into the wrong searches.*

Two numbers come up whenever people judge results, and neither should anchor yours:

- **"About 190 to 355 in a week."** One person reports that after "Recruiter became my top searcher title," weekly appearances went from about 190 to 355. It is a single self-report, and her top searcher became a generic title, which by itself doesn't distinguish agency from in-house.
- **"A healthy number is above 15%."** This is a recruiter-side response-rate figure with no source. LinkedIn publishes no candidate-side ratios for appearances to views to messages.

For step 8, compare profile views and InMails against the mix change, not against the count. If the in-house share is up but views from those companies stay flat, people are finding you and then not clicking. That is a headline and photo problem in the results card, not a matching problem, and it needs a different fix.

## How the retune goes wrong

Most failed retunes come from reading the evidence wrong: a count mistaken for a result, noise mistaken for signal, or the wrong field blamed. Each failure below shows what it looks like on the page and the check that catches it.

1. **Reading the count as success.**
   - *Looks like:* appearances jump after a keyword-heavy headline.
   - *Why it lies:* headline text feeds implicit skills and Keyword hits, which widens broad agency searches.
   - *Check:* did the target in-house share rise, or only the total?

2. **Editing mid-window.**
   - *Looks like:* a muted or contradictory first reading.
   - *Why it lies:* the weekly window straddles the edit and mixes before and after data. This is an inference, not documented behaviour.
   - *Check:* log the edit time against the Wednesday refresh and judge from the first fully post-edit week.

3. **Treating noise as signal.**
   - *Looks like:* a one-week move you attribute to your edit.
   - *Why it lies:* no published week-to-week variance exists, and the count depends on how many people searched that week.
   - *Check:* the result has to fall outside the min-max of 2 to 3 no-edit weeks.

4. **Fixing the wrong field.**
   - *Looks like:* a rewritten headline and found-for titles that don't change.
   - *Why it lies:* Open to Work titles match your desired role regardless of current title, so a stale one keeps pulling the old searchers.
   - *Check:* audit all five Open to Work titles and your job alerts and preferences before anything else.

5. **A location fix that fails silently.**
   - *Looks like:* suburb to metro, and nothing changes. This was week 5 of the teardown.
   - *Why it lies:* if the title filter excludes you, location never gets evaluated.
   - *Check:* confirm the found-for titles match your target before you touch location.

6. **Misreading agency vs in-house.**
   - *Looks like:* a company tagged in-house that is actually a recruitment process outsourcer, or the reverse.
   - *Why it lies:* industry tags apply to the whole employer. Outsourced recruiting firms, and in-house teams inside staffing companies, blur the split.
   - *Check:* open each searcher company page and read its industry and its job postings.

7. **Open to Work inflating mismatched appearances.**
   - *Looks like:* more searches from unrelated functions after switching it on.
   - *Why it lies:* response likelihood is a ranking factor. LinkedIn's own documented failure had "searches for dentists" returning "candidates with software engineering titles as the search models were prioritizing job seeking candidates."
   - *Check:* compare the searcher mix one week with Open to Work on and one week with it off, changing nothing else.

8. **Stacked edits.**
   - *Looks like:* a good week you can't explain or repeat.
   - *Why it lies:* two fields changed in one cycle can't be told apart.
   - *Check:* one logged change per refresh cycle. If you must revert and change something else in the same cycle, accept that the reading is mixed.

## Keeping the profile tuned after the retune

Once the target share holds above your baseline for two or three refreshes, the retune is finished. After that, the work is upkeep. During an active search, one recruiting firm advises reviewing "every 2-3 weeks during active job searches, making one or two meaningful changes each time." For attribution I would hold that to one change per cycle.

What to keep doing:

- **Keep logging every Wednesday.** It costs minutes, and a drift back toward agency searchers shows up there before it shows up in your inbox.
- **Re-baseline after any big change.** That includes a new job, a move or a switch of target. Your old range no longer describes the profile.
- **Re-check the page itself.** LinkedIn changes what the search appearances page shows from time to time. Compare it against your day-one notes, and if a list disappears or gets renamed, start a new baseline instead of comparing across the change.
- **Keep the resume in step with the profile.** When the right recruiters start writing, the first thing they ask for is a resume, and it should use the same title the profile now matches on. Refolk writes the resume from your own history and tailors it to each posting, so the title that fixed your searcher mix also appears on what you send.

#### Before you call the retune done

- [ ] My log has at least two no-edit baseline weeks with a written min-max range for count and target share.
- [ ] Every searcher company in the log is tagged after opening its company page, with unsure entries left out of the shares.
- [ ] All five Open to Work titles and my job alerts name only target roles.
- [ ] My current title uses the wording target postings use, with any internal label kept in the role description.
- [ ] Every edit in the log has a timestamp, before and after text, and a verdict from a fully post-edit week.
- [ ] No two edits share a refresh cycle, or the mixed reading is marked as mixed.
- [ ] The target in-house share has stayed above the baseline maximum for at least two refreshes.
- [ ] I have compared profile views and InMails against the mix change and noted whether the remaining problem is visibility or the click.

## Frequently asked questions

### Why are recruiters not finding my LinkedIn profile for the job I want?

Usually they are finding it, just for a different job. Recruiter filters match on job titles, location, companies, skills, schools, industries and languages, scoped to current or past roles or Open to Work titles. If your current title is an internal label, or your Open to Work titles list an old role, the title filter routes you to the wrong searches. Check the job titles you were found for before changing anything else.

### How long do LinkedIn profile changes take to show in search appearances?

The only documented timing is that LinkedIn updates search appearance data weekly on Wednesdays. Third-party claims of re-indexing within 24 to 48 hours have no sources behind them. In practice, judge an edit from the first refresh whose whole week falls after the change. Practitioners suggest watching each edit for two or three weeks before deciding.

### Is a higher search appearance count a good sign?

Not on its own. The count also depends on how many people happened to search your terms that week, and broad keyword text can raise it with agency searches you do not want. A smaller count from target in-house recruiters beats a larger count from the wrong searchers. Judge each refresh by the target-searcher share against your baseline range, not by the total.

### Can I see who searched for my LinkedIn profile?

No. LinkedIn shows only an aggregated overview of searchers' companies and job titles, never individual people. The count is how many times you were listed in results, which does not mean anyone clicked. Whether free members see less of this page than Premium members is not publicly established, so check what your own page shows and note it in your log.

### Does turning on Open to Work bring more relevant recruiters?

It can bring more recruiters without making them more relevant. LinkedIn's ranking weighs the likelihood that a candidate responds, and a documented case had dentist searches returning software engineers because job-seeking signals were prioritised. Test it directly: read the searcher mix for one week with Open to Work on and one week with it off, changing nothing else.

---

*From the Refolk guide library. I revise these guides rather than replacing them, so the current version is always at https://www.refolk.ai/candidates/guides/wrong-searcher-profile-retune*