Juliana de Moor's audit covers 7 public posts, including 7 with both reaction and comment counts. The measured median is 28 interactions. Careers & leadership is the most represented detected theme (6/7; themes can overlap). Start with a concrete follow-up to an existing subject, then test the opening and reply invitation across a consistent four-week sample.
7 of 7 posts have both public counts. Their median is 28 interactions. Compare future experiments with your own sample rather than an unrelated peer score.
“Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. SE in SF: first inte” has 69 visible interactions. That is 2.5× the sample median. Its topic and opening are candidates for a follow-up experiment; this does not identify why it performed.
4 of 7 posts contain a question. Measured posts generated 16.2 comments per 100 reactions. Counts can include the author's replies and do not measure lead quality or sentiment.
The median gap between sampled dates is 3.5 days; the longest is 7 days (6 intervals). Missing posts can exaggerate gaps, so this is not a complete publishing calendar.
Profile & visual identityImage preview, section grades, missing data and specific fixesExplore
SOURCE PROFILE PREVIEW
Juliana de Moor
Headline not supplied by the source
These are source images, which may be resized. An unavailable image does not mean it is missing on LinkedIn.
PROFILE CHECKLIST
Your first impression, section by section.
Open any section to see the evidence and a practical fix. Unknown data is not a failed check.
Profile picture
A+15/15 observed points
15 / 15 points assessable
PassProfile image supplied5/5
What we observed
The source supplied an image URL.
Keep it strong
Choose a current, recognizable photo. Preview the circular crop at comment size and leave space around your head.
PassImage decodes and fits its display shape10/10
What we observed
Returned image: 200 × 200px. Dimensions and decoding were measured on the returned image, which may be a resized LinkedIn thumbnail. Original resolution, face framing, lighting and professional suitability were not assessed automatically.
Keep it strong
Use a square original, check sharpness at full size, and preview the circular crop. A small provider thumbnail does not prove your original upload is low resolution.
Cover & visual identity
A+10/10 observed points
10 / 10 points assessable
PassCover image supplied5/5
What we observed
The source supplied an image URL.
Keep it strong
Use a simple cover that says who you help and what you do. Keep important text clear of the profile-photo overlay.
PassImage decodes and fits its display shape5/5
What we observed
Returned image: 800 × 199px. Dimensions and decoding were measured on the returned image, which may be a resized LinkedIn thumbnail. Original resolution, face framing, lighting and professional suitability were not assessed automatically.
Keep it strong
Preview your cover on desktop and mobile. Start with a 1584 × 396 canvas and keep the message readable without tiny text.
Name & identity
A+10/10 observed points
10 / 10 points assessable
PassReadable display name5/5
What we observed
Source text: “Juliana de Moor”
Keep it strong
Use the name people know you by, consistently across your profile and other professional channels. Single names and all writing systems are supported.
PassName field stays focused on identity5/5
What we observed
Source text: “Juliana de Moor”
Keep it strong
Move URLs, contact details and sales calls to action into About or Contact info. Keep your actual name unchanged.
Headline & positioning
UnknownNeeds source data
0 / 15 points assessable · partial coverage
UnknownHeadline supplied—
What we observed
Not returned in readable form by the source.
What to do
State your role or specialty in the headline, using terms your intended reader understands.
UnknownEnough context to explain your work—
What we observed
Not returned in readable form by the source.
What to do
Use this structure: [role or specialty] · Helping [audience] achieve [outcome]. Replace every bracket with a truthful detail.
UnknownHeadline is concise enough to scan—
What we observed
Not returned in readable form by the source.
What to do
Keep the headline focused on one main promise. Move your longer story into About.
About & descriptions
Partial5/5 observed points
5 / 20 points assessable · partial coverage
PassReadable introduction5/5
What we observed
Truncated source excerpt: “Hey! I’m Juliana 👋 Director of Recruiting at Better Career, where we focus on helping…”
Keep it strong
Lead with who you help, the problem you solve and the work you do today.
UnknownAn introduction with supporting detail—
What we observed
Truncated source excerpt: “Hey! I’m Juliana 👋 Director of Recruiting at Better Career, where we focus on helping…”
What to do
Add a specific example of your work, your approach, and the kinds of opportunities you welcome. Length is a structure check, not a quality guarantee.
UnknownEasy-to-scan paragraph structure—
What we observed
Truncated source excerpt: “Hey! I’m Juliana 👋 Director of Recruiting at Better Career, where we focus on helping…”
What to do
Break About into short paragraphs: current focus, relevant proof, then how to connect.
UnknownA clear next step—
What we observed
Truncated source excerpt: “Hey! I’m Juliana 👋 Director of Recruiting at Better Career, where we focus on helping…”
What to do
End with one relevant next step, such as who should message you and what to include. This automated check recognizes English phrases and links; review other languages manually.
Experience & proof
UnknownNeeds source data
0 / 15 points assessable · partial coverage
UnknownProfessional experience identified—
What we observed
No readable entries were returned. We cannot conclude this section is empty.
What to do
List relevant roles with an accurate title and organization. Connect them to the work you want to do next.
UnknownExperience includes useful descriptions—
What we observed
Not returned in readable form by the source.
What to do
For each relevant role, explain your responsibility, a concrete contribution, and an outcome you can substantiate. Do not invent numbers. Masked source descriptions need manual review.
Education & learning
UnknownNeeds source data
0 / 10 points assessable · partial coverage
UnknownEducation or learning entry identified—
What we observed
No readable entries were returned. We cannot conclude this section is empty.
What to do
Add relevant education or structured learning you want to share. Name the institution or course accurately; formal degrees are not required for a strong professional story.
UnknownLearning context is described—
What we observed
Not returned in readable form by the source.
What to do
Describe your subject, course or qualification and one relevant project or skill. Use the full qualification name where helpful. We assess clarity, never institution prestige or degree level.
Location & context
A+5/5 observed points
5 / 5 points assessable
PassReadable location5/5
What we observed
Source text: “Napa”
Keep it strong
Use an accurate city or region if you want it visible. Do not add a home address. Omitted provider data is not penalized.
Read all available profile text
Headline
Not returned in readable form by the source.
About
Hey! I’m Juliana 👋 Director of Recruiting at Better Career, where we focus on helping…
This is a truncated source excerpt.
Experience
No readable entries returned.
Education
Name unavailable
California Polytechnic State University-San Luis Obispo
Hidden entries are omitted from this readable preview. Source text is not independently verified.
VISUAL REVIEW
Check how your profile looks.
The automatic image grade checks file readability and shape. Use this checklist to review the visual choices it cannot judge.
Is your face recognizable in the small circular crop?
Is the image sharp, evenly lit, and free of distracting clutter?
Does the banner communicate your work without overlapping your photo?
Are colors and typography consistent with your professional identity?
A transparent presentation checklist, not a LinkedIn ranking, talent assessment or prediction of reach. Grade thresholds: A+ 90, A 80, B 65, C 50, D 35, F below 35.
Score = earned points ÷ assessed points × 100. Coverage is assessed weight out of 100. Unavailable and masked data are excluded. Scores with different coverage are not directly comparable.
Truncated text earns only checks already demonstrated in the visible excerpt; the unseen remainder is not marked wrong. Text rules measure structure, not factual accuracy, writing quality or every language equally.
Photo and banner grades cover image availability, decoding and shape only. Face framing, lighting, expression, visual style and authenticity require a human review. No appearance, identity or personality judgments are made.
An education entry is evidence of profile context, not verified credentials. School prestige, age, degree level and background do not affect the score.
Section weights: photo 15, cover 10, name 10, headline 15, About 20, experience 15, education 10, location 5. Passed checks earn their full weight; improvements earn zero; unknown checks are excluded.
PerformanceYour own baseline, strongest posts and publishing rhythmExplore
YOUR OWN BASELINE
Performance, with perspective.
Interactions across the sample
Publication date · UTC
69
09-28
41
10-01
27
10-05
17
10-07
55
10-14
21
10-19
28
10-21
View chart data
Measured interactions by post
Date UTC
Reactions
Comments
Total
2026-09-28 15:30
66
3
69
2026-10-01 14:00
33
8
41
2026-10-05 14:00
18
9
27
2026-10-07 15:36
17
0
17
2026-10-14 16:00
46
9
55
2026-10-19 14:35
15
6
21
2026-10-21 15:00
27
1
28
Post totals at collection time. Older posts have had more time to collect reactions and comments.
EARLY VS RECENT SAMPLE
41→28
Median visible interactions: 41 for the earliest 3 measured posts and 28 for the latest 3. The middle post is excluded to keep group sizes equal. This compares selected posts of different ages, not account growth.
TYPICAL VS STRONGEST
28/69
Median / highest measured interaction total. A breakout can lift the average; the median provides another view of a typical sampled post.
Publishing rhythm
Median gap: 3.5 days · Longest gap: 7 days · 6 observed intervals.
Explore 3 groups and supporting posts
Publishing days in UTC — descriptive, not recommended times
Unknown means the source did not verify the format. Small or unequal groups do not establish a winning format.
Hooks and writing structure
Read writing structure for 7 posts
Text rules applied to every sampled post
Opening
Hook type
Words
Paragraphs
Final CTA
Tags / mentions
One of the worst things a recruiter can do is introduce a hiring manager to a candidate they could n
Number-led
229
1
Not detected
0 / 0
You don't see many people in jobs longer than a year and a half anymore. Especially on the startup s
Question
258
1
Detected
0 / 0
The difference between a good SE and a great SE usually comes down to one thing: They tie everything
Question
259
1
Detected
0 / 0
He had less than 60 days to find a job. If he didn’t, he’d have to pack up his family and leave the
Question
255
1
Detected
0 / 0
Our last 21 hires went from submission to signed offer in a median of 20 days. The goal now is to ma
Question
196
1
Detected
0 / 0
I didn't talk for ten days. No phone. No writing. No communication of any kind. Just silence, and my
Number-led
210
1
Not detected
0 / 0
Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN.
Number-led
69
1
Not detected
0 / 0
Hook type uses the first nonempty line. CTA detection checks the final paragraph for a question or action phrase. Paragraphs use blank-line breaks. These rules can miss meaning and linked mentions.
Hashtags in the sample
No data available for this grouping.
Tags travel with the topic, author and format. These associations cannot isolate a hashtag's effect.
Recommended next stepsPrioritized actions, effort and what to measureExplore
PRIORITIZED RECOMMENDATIONS
Less guessing. Clear next steps.
Ordered from building a useful baseline to testing individual writing choices. Potential impact describes the purpose of an experiment, not a promised uplift.
01Develop a specific follow-up
Medium effort
OBSERVATION
The sample includes “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ”. Its visible interaction total is 69.
DO THIS
Build a follow-up to “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ”. Add a concrete example, a decision you made and one lesson. Keep the format similar so topic development is the main experiment.
Potential impact: Test repeatable interest in an existing subject
Metric to watch: Reactions and comments after the same seven-day window; compare with the baseline median
Median text length is 229 words with 1 paragraphs. 0 of 7 openings are classified as statements.
DO THIS
For the next post related to “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ”, open with a specific problem and a concrete outcome you can substantiate. Move context into the second paragraph. Avoid invented results or curiosity gaps that the post does not resolve.
Potential impact: Improve clarity; any engagement effect remains to be tested
Metric to watch: Median interactions across at least three comparable posts per opening approach
4 of 7 final content lines contain a detected question or action phrase; 4 posts contain a question anywhere. These are text rules, not semantic judgments.
DO THIS
End one upcoming post with a focused trade-off question connected to careers & leadership. Ask readers to share a decision and why. Read replies before deciding whether the discussion was useful.
Potential impact: Test whether a clearer invitation supports useful discussion
Metric to watch: Public comments per post and manual review of reply relevance
7 dated posts span 23 days. Observed cadence is 1.8 posts per week.
DO THIS
Choose two slots per week for the four-week experiment below, or reduce the schedule if your capacity is lower. Keep the slots consistent and log every published post. Two slots are a planning choice, not a LinkedIn benchmark.
Potential impact: Create comparable records and a manageable learning loop
Metric to watch: Planned versus published posts, time spent, and median interactions at seven days
0 of 7 posts contain hashtags and 0 contain visible @mentions. LinkedIn may return linked mentions as plain text, so detection can undercount.
DO THIS
Use relevant topic labels only when they clarify the subject. Mention people only when they contributed or are directly relevant. Test a consistent tagging approach on comparable posts; do not attribute performance changes to tags alone.
Potential impact: Keep context and attribution useful
Metric to watch: Median interactions for tagged/untagged samples, with sample sizes and topic differences
Turn one idea related to “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ” into a concise checklist or document post. Keep a similar topic and ask the same type of question. Label this a new format experiment, not a proven winning format.
Potential impact: Learn whether a different presentation helps explain the same idea
Metric to watch: Public interactions at the same post age; at least three posts in each format before comparison
Content ideas & basic outlineThree starting ideas and a simple structure for your next postExplore
INCLUDED IN YOUR FREE REPORT
A starting point for your next post.
Simple ideas from this profile’s available evidence. Choose one, add your own experience, and review the result.
IDEA 1
The next chapter
Follow up on “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ”: what changed since publishing, what stayed difficult, and the next step. Only include outcomes you can verify.
Break the work behind “Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. ” into three decisions. Add an example or screenshot you have permission to share.
Two SE offers accepted this month! Senior SE in NYC: first interview to offer in 13 days. THIRTEEN. SE in SF: first interview to offer in 22 days. NYC and SF are two of the harder markets to close SE searches in right now. Both moved fast for the same reason: candidates responded quickly, clients decided quickly. Shout out to our candidates, clients & team. Pastry + coffee to celebrate 🤷♀️
The difference between a good SE and a great SE usually comes down to one thing: They tie everything back to value. A good SE can run a standard demo and answer questions. But the SEs who really stand out spend less time showing how much they know and more time understanding what the customer actually cares about. When I debrief with hiring managers after demo rounds, this is the most common reason a strong candidate doesn’t get the offer. And it usually starts well before the demo. If a prospect says they need better reporting, a great SE won’t just add the reporting dashboard to their demo checklist. They’ll want to know what’s wrong with the current reporting, who it affects, and why fixing it matters to the business. So when they finally show that dashboard, it’s built around the VP who spends six hours a week pulling numbers by hand. That’s also why value isn’t one-size-fits-all. Even on the same call, different people want different answers. The technical buyer wants to know how it works. The business leader wants to know what changes for them. The strongest SEs can speak to both without losing either. And it’s why feature dumping is such a missed opportunity. You can show someone 25 impressive features, but if only three address the problems they came to solve, you’ve spent most of the demo on the wrong things. For the SE leaders here, what’s one thing you notice during a demo that immediately tells you, “This person really knows what they’re doing”?
I didn't talk for ten days. No phone. No writing. No communication of any kind. Just silence, and my own mind, for ten days straight. It was a Vipassana meditation retreat in Indonesia. You wake up at 4am, meditate for ten hours a day, eat twice, sleep, and then get up and do it all over again. It was one of the hardest things I've done, and also one of the most life changing. After the 10 days, I had a level of focus I didn't know was possible. Work felt different. Even reading emails and having conversations felt different, and it’s all because my brain had been so overstimulated for so long that I'd forgotten what it was like to think clearly. What surprised me most was who else was there. A lot of them were managers and executives whose bosses had actually encouraged them to go, because people came back sharper, calmer and more productive. I'm not saying everyone needs to do a Vipassana retreat. But I do think we underestimate how much noise we carry around, and we keep adding to it with more tools, more content and more things to do. Ten days of nothing did more for my focus than any productivity hack I've tried.
One of the worst things a recruiter can do is introduce a hiring manager to a candidate they could never actually hire. Imagine you're hiring a Solutions Engineer, and I introduce you to someone who checks all the boxes. You love everything about them, but there's one problem: they're expecting $220K, and your budget is $160K. You make an offer anyway, hoping they'll be excited enough about the opportunity to compromise. They decline, and now every candidate I introduce to you gets compared to someone who was never within your budget. This is one of the reasons I spend so much time understanding what candidates actually want before introducing them to clients. I want to know their salary expectations, career goals, preferred working environment, and whether they'd seriously consider the opportunity if an offer came through. I also want to understand where the hiring manager has flexibility and where they don't, because there's very little value in creating excitement around a candidate when the expectations on both sides don’t align. The problem is that the other candidates aren't going to put their job searches on hold while the hiring manager figures this out. They're interviewing with other companies, and some will inevitably receive offers. I've always felt that a good recruiter should help hiring managers understand what's realistically available within their budget, rather than set expectations they can't meet.
Our last 21 hires went from submission to signed offer in a median of 20 days. The goal now is to make that even faster, and AI is a big part of how we're doing it. It isn't removing the human touch. We still run every screen ourselves and talk to every candidate and hiring manager directly. What it's changed is how fast we learn. Every piece of hiring manager feedback, whether it comes through Slack, email or a sync call, goes into a living scorecard for that role. If a hiring manager tells us a candidate's technical depth wasn't there, the scorecard updates, and the next candidate gets asked the question that would have caught it. So we're asking better questions every week and spotting fit (and misfit) before a candidate ever reaches the hiring manager's calendar. The number we care about most is sub-to-start: how many candidates a client has to interview to make one hire. Every candidate we take out of that number is hours back on a hiring manager's week. That's the whole goal: save our clients as much time as possible. How is your team using AI in hiring right now?
You don't see many people in jobs longer than a year and a half anymore. Especially on the startup side. And to be fair there can be good reasons for that. A candidate might have three roles in three years and on paper, that looks like they’re job-hopping. But when you actually talk to them, you find out: - The first company had an acquisition - The second was supposed to sell but didn't, and they had layoffs - The third ran into financial trouble None of that means the person isn't looking for something stable. In fact, a lot of the candidates I talk to are actively seeking stability but they're just coming out of situations that were beyond their control. For AEs, there’s another layer to this, especially when they’ve been selling something with a longer sales cycle. Someone might leave before they’ve had enough time for the deals they were working to actually close, which can make their performance a little harder to judge from a resume alone. That’s where you have to look beyond tenure and ask better questions: What pipeline did they build? How were they performing against the expectations for that stage of their ramp? What deals were they working? And, most importantly, why did they leave? I think hiring managers sometimes look at a resume and make a quick judgment about a candidate’s tenure without understanding the full story. And candidates…if you've moved around, you need to be ready to explain why in a way that makes sense. Because the context ALWAYS matters.
He had less than 60 days to find a job. If he didn’t, he’d have to pack up his family and leave the US. This was right after Covid, and I had just started my career in recruiting. Finding a job was difficult for almost everyone at the time and for candidates on visas, the pressure was on another level. I was working at a large agency with plenty of openings, so I started reaching out to account managers across the company, trying to find a client who might be open to sponsorship. A lot of the initial answers were no. And I remember pushing back with a simple question: “Have you actually asked them?” A lot of the time, we were assuming the answer would be no because of how difficult the market was, without actually putting the question to the client. Sponsorship added another layer of complexity to an already difficult hiring process, so it was easy to assume a client probably wouldn’t go for it. But this candidate didn’t have the luxury of us assuming. So I kept asking account managers to go back to their clients and actually have the conversation. Eventually, we found an opportunity. He went through several rounds of interviews and got the job. I still remember how grateful he was. He had built a life in the US with his family, and this job meant they could keep that life. Years later, that experience is still the clearest answer I have for why I love this work.
17reactions
0comments
A RECORD YOU CAN RETURN TO
Saved audit history.
Reading a saved report does not start a new collection. A fresh snapshot requires confirmation and uses your current review allowance. Refresh availability and shared spending limits are checked before it starts.
A comparison appears after another audit is saved. A single snapshot cannot establish follower growth.
Help improve this report
Independent analysis of publicly available information. Not affiliated with LinkedIn or the profile owner. Impressions, profile views, private analytics, and follower growth are not available in this snapshot.