Frequently asked questions about LinkedIn
The answers below come from Karvi's analysis of 26,507 LinkedIn profiles of Brazilian professionals since January 2026. Six categories: basic optimization, headline, about, skills, algorithm, and career scenarios.
Profile optimization
How do I improve my LinkedIn profile?
A strong LinkedIn profile works across 6 dimensions: headline, about, experiences, skills, completeness, and activity. Each section needs to tell the same professional story β the 360Brew algorithm evaluates semantic coherence across sections, not isolated keyword counts. Scattered profiles lose visibility.
For most Brazilian professionals, the biggest opportunity is the Skills section. Data from 26,507 profiles analyzed by Karvi shows an average of 3.1/10 in Skills β half the Headline score (6.0/10). It's the dimension with the most room for gain per hour invested.
Where to start: review the 10 roles you want most, note the exact terms used, update your skills with those terms. Then re-read headline and about, checking they still describe the same position.
What do recruiters look for in a LinkedIn profile?
Recruiters check in sequence: headline (specific enough to justify opening the profile), skills (LinkedIn Recruiter uses skills as the first search filter), and experiences (they look for quantified deliveries, not a list of responsibilities).
The decision to open the profile happens before reading any experience. A generic headline ("Marketing Analyst") doesn't earn the click. A specific one ("Performance Marketing Analyst Β· E-commerce Β· Meta Ads") does.
At the end of the assessment, the recruiter checks whether headline, about, and experiences tell the same story. Incoherence between sections reduces confidence in the candidate even when the track record is solid.
How long does it take to optimize a LinkedIn profile?
A full review across the 6 dimensions takes 2 to 4 hours. Headline and about: 30-45 minutes each. Experiences: 60-90 minutes, especially if you need to transform lists of responsibilities into deliveries with numbers. Skills and completeness: 20-30 minutes.
The return isn't proportional to the time. The first two hours produce 80% of the result. Headline (10 minutes) and skills (20 minutes) alone already deliver measurable improvement in visibility.
Maintenance: 30 minutes a month to update skills and log new achievements is enough for stable profiles. In tech, skills deserve a quarterly review β technical vocabulary changes faster than in other fields.
Should I keep my profile in Portuguese or English?
Depends on the market you want to reach. For roles at mid-sized Brazilian companies: Portuguese. For multinationals or senior positions: English β global recruiters search using English terms even for local roles.
In tech, the Brazilian standard is migrating to English for technical roles. "Software Engineer Β· Backend Β· Node.js" appears in more recruiter searches than the Portuguese equivalent, even for Brazilian roles.
The bilingual solution works well: about in Portuguese, technical terms in English in experiences and skills. Captures searches in both languages without losing authenticity.
Is it worth paying for LinkedIn Premium?
Depends on the goal. In active search, Premium Career shows how many candidates applied for the same role, who viewed your profile, and how you rank in recruiter searches. That data helps prioritize where to optimize first.
For networking, InMail delivers real returns with personalized messages β generic ones perform poorly even when paid. For people not in active search, most Premium features don't translate into measurable results.
Optimize all 6 dimensions on the free account before subscribing. A well-optimized free account generates more visits than Premium with a weak profile.
Headline and About
What's the formula for a strong LinkedIn headline?
The most effective structure is: role + context + edge, separated by Β· (middle dot). Examples: "Software Engineer Β· Distributed Systems Β· 10 years in fintechs," "Data Analyst Β· SQL + Python Β· Retail & e-commerce." Each part answers a different question: who you are, where you operate, what sets you apart.
The most common mistake is using just the job title ("Project Manager") with no edge. Generic titles compete on visibility β those with specific context win the click. The second mistake is replacing the edge with vague phrases ("Passionate about challenges and digital transformation").
The headline appears in LinkedIn Recruiter search results and in the feed every time you interact with content. It's read in under 6 seconds. Every word takes valuable space.
How many words should the About section have?
LinkedIn only shows the first 3 lines before the "see more" β about 60 to 70 words. Those lines need to contain your strongest positioning. The rest develops context, proof, and call to action.
The ideal length is between 200 and 300 words. Under 100, the profile looks incomplete. Over 500, it's rarely read to the end. The middle ground lets you include keywords, value proof, and a call to action.
A structure that works: hook in the first 2 lines, what you do in 3-4 sentences, proof with numbers or achievements, call to action on the last line. Simple to follow and covers both findability and visit-to-contact conversion.
Should I write the About in first or third person?
First person, no exceptions on career profiles. The About is the only field where a personal voice is expected. "I've worked in product for 8 years..." sounds like a real conversation. "Professional with 8 years of experience..." sounds like a 2010 corporate resume.
Third person creates distance. The reader feels they're reading a bio written by a PR rep, not by the professional. This weighs especially on roles that demand close communication and relationships.
The exception is corporate-representation profiles where the voice is the brand's. For personal profiles, first person is more effective and more aligned with LinkedIn's 2026 tone.
Does the headline appear in recruiter searches?
Yes. LinkedIn Recruiter shows name, headline, and current company in the search result. The recruiter decides whether to open the profile based on those three. A vague headline gets the profile ignored even when skills and experiences are strong.
The headline is also indexed by the 360Brew algorithm to evaluate semantic coherence with other sections. A headline that describes a positioning different from the listed skills creates signal conflict and reduces search ranking.
Beyond recruiter search, the headline appears when you comment, like, or post. It's the main passive-visibility mechanism on LinkedIn β it works for you even when you're not in active search.
Skills and Experience
How many skills should I list on LinkedIn?
Between 15 and 25. Below 10, the profile loses specific search filters and looks incomplete. Above 40, the signal dilutes and it becomes hard for the algorithm and the recruiter to identify your area of specialization.
The first 3 skills shown publicly (before expanding the section) are the most strategic. Put the skills most relevant to the role you want in those slots, not the oldest ones or the ones with the most endorsements.
Data from 1,998 profiles analyzed by Karvi shows an average of 3.1/10 in Skills β the lowest-scoring dimension of the 6. The problem is almost never quantity: it's lack of specific hard skills. Generic soft skills without backing in experiences carry reduced weight in the algorithm.
State of LinkedIn in Brazil 2026 β data from 26,507 profiles
Which skills to prioritize on the profile in 2026?
Trackable hard skills come first: tools (advanced Excel, Salesforce, Python), certifications (PMP, AWS, Google Analytics), methodologies (Scrum, OKR). These activate specific search filters in LinkedIn Recruiter.
To know which to prioritize in your case: search the 10 roles you want most, list the skills that appear in most of them, and add the ones you have but haven't included yet. The exercise takes 30 minutes and starts from real demand, not guesswork.
Soft skills should appear sparingly and backed by experiences. "Leadership" as a skill makes sense when you led teams in the listed roles. Without that backing, the 360Brew algorithm reduces the weight of the claim β it cross-checks skills against evidence in the experiences.
How to describe professional experience without slipping into the generic?
Use Google's XYZ framework: "Accomplished X by doing Y, measured by Z." Instead of "Responsible for content strategy," write "Increased organic traffic by 180% by restructuring the SEO content strategy, measured in GA4 over 12 months." The structure forces specificity.
There are four dimensions to quantify: scale (team size, number of customers), time (deadline, cycle speed), percentage (revenue growth, cost reduction), and absolute (value in $, units, users). Every role has at least one of these, even support or admin functions.
For roles without obvious numbers: use scope of responsibility, problem complexity, or size of the organization impacted. "Implemented onboarding process for 3 teams of 15 people" is already more precise than "Responsible for new-hire onboarding."
Do skill endorsements still count for anything?
They count, but with different weight than in the past. Endorsements work as social validation β recruiters check how many people confirmed a skill, especially when the endorser holds a relevant role in the field. An endorsement from a CTO for "Software Architecture" weighs more than 50 endorsements from profiles without context.
With the 360Brew algorithm, semantic relevance matters more than count. Skills with many endorsements but no mention in experiences carry reduced weight. Skills that appear both in the dedicated section and in role summaries have a stronger semantic signal.
In practice: ask close colleagues for specific endorsements on your 3 most strategic skills. Endorsing in return creates natural reciprocity. Don't spread requests across the whole list.
Should I include metrics in every experience?
Yes, in at least one achievement per role. One number per role is the minimum. Concrete numbers already differentiate the profile from dozens of candidates describing the same responsibilities without quantifying anything.
For roles without obvious numeric metrics: use scale, complexity, or scope. "Managed project with 12 stakeholders across 4 departments on a 6-month timeline" is a valid scope metric β even without percentages or dollar values.
Never invent metrics or inflate percentages. Experienced recruiters spot implausible numbers, and inconsistencies during interviews trigger immediate distrust. Only use numbers you can explain and back up.
Visibility and Algorithm
What is LinkedIn's 360Brew algorithm?
360Brew is LinkedIn's AI model, deployed in March 2026. It's a decoder-only model with 150 billion parameters that replaced more than 30 specialized models. It unifies feed, recruiter search, job suggestions, and connection recommendations under a single language model.
The practical difference: 360Brew evaluates semantic coherence across profile sections, not isolated keyword counts. Headline, about, experiences, skills, and activity need to tell the same story. Fragmented profiles β skills without backing in experiences, about that contradicts the headline β lose reach in searches.
The model was described in a paper published on arXiv in January 2025 by LinkedIn's Foundation AI Technologies team. The feed rollout was confirmed on the company's engineering blog in March 2026.
Why doesn't my profile show up in recruiter searches?
The most common causes: skills missing or misaligned with the terms recruiters search for, incomplete profile (no photo, no about, no custom URL), and a generic headline that doesn't activate relevant keywords. Skills is the most frequent cause.
When a recruiter filters by "Project Management" in LinkedIn Recruiter, the system cross-checks against the declared Skills section, not mentions in the about or experiences. If the skill isn't in the dedicated section, the profile simply doesn't appear in the filter, regardless of how many times the term shows up in other fields.
To identify the problem in your specific profile, Karvi's diagnosis maps the gaps across the 6 dimensions with the greatest impact on recruiter visibility.
Do hashtags still work on LinkedIn?
Hashtags lost direct weight with the 360Brew algorithm. Before, adding high-volume hashtags increased post reach. With the current model, hashtags outside the profile's semantic positioning dilute the signal instead of amplifying it.
What still works: 2-3 hashtags relevant to your field, used consistently. A developer who uses #PythonDeveloper and #MachineLearning on every post builds a semantic fingerprint the algorithm recognizes. Fifteen scattered hashtags fragment that signal.
Prioritize content quality over hashtag volume. A substantial post with 2 relevant hashtags reaches more of the right audience than a weak post with 10 scattered hashtags.
How do I show up more in network recommendations?
LinkedIn recommends profiles to 2nd- and 3rd-degree connections based on semantic coherence. 360Brew uses the visitor's profile as a seed and suggests semantically similar professionals. To appear more in recommendations, your profile needs to be consistent with the type of professional you want to attract.
Two practical levers: connecting with professionals in your field expands the relevant 2nd-degree network. Keeping consistent thematic activity β comments and posts on topics from your field β reinforces the semantic fingerprint the algorithm uses for recommendations.
Well-filled skills also influence recommendations: LinkedIn uses skills as a vector to calculate similarity between profiles. Updating skills and adding recent certifications expands the surface for automatic matching.
Career scenarios
How to update LinkedIn for a career change?
A career change requires explicit repositioning across three sections. The headline must declare the new positioning, not the previous role. The about needs to explain the transition: which experience from the prior history is transferable to the new field, and why the change makes professional sense.
In experiences, reread old roles and highlight the aspects that intersect with the new field. An accountant moving to software product could have managed financial systems, defined requirements for internal tools, or trained teams on new processes. All of that is transferable.
In skills: add the new field's abilities you already have, even if acquired in other contexts. Take courses on the most-used tools in the new area and add the certifications. A transitioning profile needs to show the new signal clearly from the start.
How to build a LinkedIn profile for your first job?
Without formal experience, the sections that matter most are headline (clear positioning of what you're after), skills (everything learned in courses, projects, and informal work), and education (capstone projects, relevant academic work, honors).
Personal projects carry equivalent weight to experiences for early-career candidates. Describe them with the same delivery-and-metrics structure: number of users of the app you built, capstone grade, hours dedicated, languages or tools used.
The volunteering and extracurricular projects section is the most ignored by beginners, but it works as proof of initiative. One well-described personal project entry is worth more than a long list of courses without demonstrable results.
How to adapt LinkedIn for international roles?
For international roles, the profile needs to be in English β at least headline, about, and experience titles. International recruiter search systems work with English terms.
Add scale context for recruiters who don't know Brazilian companies: "XYZ Corp (3,000 employees, leading fintech in Brazil)" or "ABC Ltda (R$800M revenue, top 3 e-commerce in Brazil)." International recruiters have no way to gauge a company's size from the name alone.
For US roles: include the American equivalent of Brazilian certifications and add English as a skill with an explicit level. An English profile with quantified experiences and scale context works in any market.
Should I disconnect from companies where I was laid off?
There's no reason to disconnect. Layoffs are common and recruiters don't make automatic judgments about them. Most senior professionals have been through it at some point, and recruiters know it. What matters is what you did before leaving and how you repositioned afterward.
Make sure the experience at that company has value description β measurable deliverables β and that the post-layoff period isn't empty. Freelance, personal projects, courses, or volunteering during the period should appear on the timeline.
The only reason to remove an experience is if it completely contradicts the current positioning with no possible bridge. Even then, the absence of a period raises questions in interviews. When in doubt, keep it and adjust the description to highlight what's transferable.
Karvi β questions about the analysis
How does Karvi's analysis work?
Karvi analyzes your LinkedIn profile with AI across the 6 dimensions that determine visibility: headline, about, experiences, skills, completeness, and activity. You paste the profile URL, the AI processes the sections, and returns a score per dimension with a specific diagnosis.
The diagnosis shows where your profile is strong and where it's losing points, with concrete suggestions for each section. The analysis is based on patterns extracted from 26,507 Brazilian profiles processed by Karvi since January 2026.
The free diagnosis covers the 6 dimensions. The full, paid analysis adds AI-suggested rewrites for headline, about, and experiences, plus comparison with high-rated profiles in your field.
What's included in the free diagnosis?
The free diagnosis includes scoring across the 6 dimensions, identification of the main semantic-coherence gaps, and the profile's ranking against Karvi's base of 26,507 analyzed Brazilian profiles.
Not included in the free diagnosis: AI-suggested rewrites for the sections, detailed comparison with high-performance profiles in your field, and an exportable PDF report β those are part of the full, paid analysis.
The free diagnosis serves as a starting point β you see where the profile loses points before deciding on the full report. No signup needed to start.
How much does Karvi's full report cost?
Plans and pricing are on Karvi's pricing page. The model is one-time payment per analysis, no monthly subscription. You only pay for the report after seeing the free diagnosis and deciding the deep-dive is worth it.
The free diagnosis happens before any charge, so you see the result and what the full analysis includes before deciding.
Does Karvi store my profile?
Karvi processes the profile's public content β sections visible to any LinkedIn-logged-in visitor β to generate the diagnosis. The data is used exclusively for the requested analysis: not shared with third parties, not used for advertising, and not sold.
Karvi doesn't have access to your LinkedIn credentials, your private messages, or any data outside the public sections. Processing uses only information already publicly visible on the profile.
For details on how data is handled, see Karvi's privacy policy. For specific questions about your data, get in touch directly.
Does Karvi compare my profile with other professionals?
Yes. The diagnosis includes a comparison of how your profile ranks against the 26,507 Brazilian profiles in Karvi's base. You see the percentile in each dimension β "your skills are at the 40th percentile" means 60% of analyzed profiles have skills scoring higher.
The comparison doesn't expose individual profiles of other users β it's aggregated benchmarking by dimension. The comparison is done by professional field when the field is identifiable, for example: "against Product profiles identified in the base."
The goal is context: a Skills score of 6/10 sounds reasonable in isolation, but benchmarking shows whether that's above or below your field's average. Karvi uses that context to rank recommendations by impact.
See how your profile compares
These questions explain the frameworks. Karvi shows where, in your profile, points are being lost β with a diagnosis across the 6 dimensions and concrete suggestions for each section.
Find out where your profile loses points β free diagnosisFree diagnosis β no credit cardState of LinkedIn in Brazil 2026
Data from 26,507 profiles: Skills 3.1/10, Headline 6.0/10 and more.
How to optimize your LinkedIn profile
Complete guide to the 6 dimensions with frameworks and practical examples.
LinkedIn 360Brew Algorithm
How the 150B-parameter model evaluates semantic coherence of the profile.