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Extract a LinkedIn voice profile with AI: Tone analysis, writing style & ghostwriter guide

Feed Juma a LinkedIn URL. Get a voice guide with LinkedIn copywriting patterns, tone markers, and post examples every ghostwriter needs.

Juma reads the LinkedIn profile URL you share and returns a structured voice guide built from the person's actual posting history. The guide covers tone, vocabulary, post structure, content themes, and engagement patterns, giving any LinkedIn ghostwriter everything needed to match that writing style from day one.

1

Build a voice profile from LinkedIn

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Example Flow result

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  • Include the LinkedIn profile URL. The AI pulls the profile bio, headline, experience, and recent posts directly. Without the URL, the analysis relies on web search, which misses engagement data and post formatting.
  • Mention if the person recently changed roles. A CMO who joined three months ago has a thin LinkedIn history at the new company. Pointing this out tells the AI to look at their previous posting patterns and note which voice elements will carry over versus what needs to adapt to the new role.
  • Specify whether the guide is for ghostwriting or voice alignment. A ghostwriting guide needs granular detail: exact hook patterns, paragraph lengths, emoji usage, CTA conventions. A voice alignment guide for an internal team needs broader principles. Mentioning the purpose shapes the level of detail.
  • Request a specific time period if voice has evolved. People's LinkedIn voice shifts over time, especially after a promotion, company change, or viral post. Asking for "the last 6 months" or "since they became CEO" focuses the analysis on the current voice, not historical patterns that no longer apply.
2

How do you analyze a LinkedIn company page voice?

Company pages communicate differently than personal profiles. Give Juma a company LinkedIn URL and a note about the analysis purpose. You get back:

  • Institutional tone and vocabulary
  • Content themes and posting frequency patterns
  • Formatting conventions by post type
  • Where the voice is consistent and where it fragments

This step is useful before onboarding a company as a new client or briefing a content team taking over the account.

Prompt
Copy

Analyze the LinkedIn voice of HubSpot's company page (https://www.linkedin.com/company/hubspot/). We're onboarding them as a client and need to match their tone.

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3

How do you compare two executives' LinkedIn voices?

Share both LinkedIn profile URLs and describe the relationship between the two executives. The comparison covers:

  • Where the voices overlap in tone and vocabulary
  • Where they diverge in structure and content themes
  • Which topics each person owns naturally
  • Guidance on keeping each voice distinct as both accounts grow

Running this step before ghostwriting for both accounts prevents the voice drift that makes two leaders sound like the same person.

Prompt
Copy

Compare the LinkedIn voices of our client's CEO and CTO. The CEO posts weekly, the CTO just started. Map the differences and recommend how to keep both voices distinct.

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4

How do you write LinkedIn posts that match someone's documented voice?

Give Juma the voice guide from the previous step and the topics you want to cover. Each post matches the documented style across:

  • Hook structure and opening line pattern
  • Paragraph length and line break conventions
  • Vocabulary and CTA language
  • Tone calibrated to the person's current posting era

The first three posts serve as a calibration test: if they sound right, the voice guide is accurate and the ghostwriting relationship can move into regular production.

Prompt
Copy

Using the voice profile we just built, write 3 LinkedIn posts for next week. One thought leadership piece on AI in retail, one industry commentary, one behind-the-scenes.

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Set up your client project: LinkedIn Profile & Post History, Ghostwriting Brief, Voice Reference Examples & Content Themes

Voice extraction is rarely a one-time task. Ghostwriting teams return to the voice profile every time a new batch of posts goes out, when a new writer joins the account, or when the executive's role shifts and the tone needs to evolve with it. Without a shared project, every new session means re-pulling the profile, re-establishing what sounds right, and rebuilding context that the previous writer held in their head. A Juma Project stores the voice guide, the reference posts, and the guardrails once. Set it up and every draft, every comparison, and every new post series the team writes after that starts from the same source of truth.

What to add

LinkedIn Profile & Post History

The executive's or company's LinkedIn URL and any saved post examples worth preserving. The AI pulls live data directly from the profile, but saving high-performing posts in the project ensures the best reference material is never lost to LinkedIn's post history limits.

Ghostwriting Brief

Who the writer is drafting for, what the executive wants to be known for, and any role or company changes that affect how the voice should evolve. This context tells Juma whether to carry over historical voice patterns or adapt them to a new position.

Voice Reference Examples

Two to four posts the executive considers their best work, with a short note on what made each one land. These serve as the primary benchmark when Step 4 puts the voice profile to work — new drafts get measured against posts the executive has already approved, not just extracted patterns.

Content Themes & Off-Limits Topics

Topics the executive returns to regularly and subjects that are off the table — competitors not to mention, internal matters to avoid, opinions the brand has decided not to take publicly. This prevents the ghostwriting team from drafting posts the executive will immediately reject.

Guide Juma with project info

Add a short description to each knowledge item in the project's info field so Juma knows what each file contains and when to use it. For example:

  • LinkedIn Profile & Post History: "Executive's LinkedIn URL and saved high-performing posts. Use as the primary data source for voice extraction and pattern analysis."
  • Ghostwriting Brief: "Who we're writing for, their positioning goal, and any recent role changes. Use to frame the voice guide and adapt historical patterns to the current context."
  • Voice Reference Examples: "Executive-approved posts with notes on what worked. Use as the benchmark when drafting new posts in Step 4."
  • Content Themes & Off-Limits Topics: "Recurring topics the executive owns and subjects that are off the table. Check before drafting any post series."
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Extract the voice. Write every post like the executive wrote it themselves.

Frequently Asked Questions

How much time does this Flow save compared to manually reviewing LinkedIn posts?

This Flow reduces a three-to-five-hour manual process to minutes. Manually reading 20-30 posts, identifying patterns, and writing a style guide from scratch takes a typical ghostwriter half a day. Give Juma a LinkedIn URL and a short briefing note, and it returns a structured, six-dimension voice guide ready to share with the writing team.

The time saving compounds across a full client roster. Instead of scheduling a briefing session, pulling scattered screenshots, and writing a document from scratch for each new client, you share the voice guide in the same conversation where the scope is set. For agencies managing multiple LinkedIn ghostwriting accounts at once, voice profiles for the entire roster can be created and updated in the time it previously took to document a single one. The output arrives formatted as a working reference document, not a raw analysis, so the ghostwriting team can start using it immediately without restructuring the content.


What does the LinkedIn voice profile include?

The voice profile covers six dimensions: tone, vocabulary, post structure, content themes, engagement patterns, and a "write like / don't write like" section with annotated examples. Each dimension draws from the person's real posts, not from how they describe their own writing, so the output reflects how they actually communicate rather than how they think they do.

Tone maps where the person falls on the formal-to-casual spectrum with specific post markers. Vocabulary documents repeated phrases, avoided jargon, and how they handle industry terminology. Structure records average post length, paragraph style, line break patterns, hook types, and CTA conventions. Content themes identifies the topics they return to and the angles they take. Engagement patterns records which post types earn the most audience response. The "write like / don't write like" section is the most operationally useful part for a ghostwriter: it provides direct examples of what to replicate and what to avoid, formatted as a checklist a writer reviews draft by draft.


Why does a voice profile built from real posts outperform a brand voice document?

A brand voice document describes how someone wants to sound. A voice profile built from real posts shows how they actually write. The gap between the two is where ghostwriting fails: a brief that says "authoritative but approachable" will be interpreted differently by every writer who reads it.

A profile built from 20-30 real LinkedIn posts captures the specific patterns that make someone's writing recognizable, including habits they would never think to list in a workshop. These include how they open a personal experience post versus an industry commentary, whether they favor rhetorical questions or direct statements, and which CTA types they use consistently versus which they never touch. A well-built voice profile turns adjective-based briefing into a concrete, testable set of rules. Building a LinkedIn personal brand on evidence rather than adjectives is what produces a voice that feels consistent across dozens of posts rather than recognizable only in isolation. When a writer finishes a draft, they check it against the profile instead of asking the client whether it sounds right.


Can this Flow analyze a LinkedIn company page, not just a personal profile?

Yes. Company pages follow different conventions than personal profiles, and the same Flow handles both. Provide a company LinkedIn URL and Juma returns the institutional tone, content themes, formatting conventions, and how the voice shifts across post types such as product announcements, thought leadership, and hiring content.

Company pages tend to have a more fragmented voice history than personal profiles because multiple writers often contribute over time. The analysis notes those inconsistencies and identifies the dominant patterns that have shaped the page's identity. If you are onboarding a company as a new client, running this analysis before your first briefing call gives you a working understanding of how they currently communicate on LinkedIn. This makes it easier to spot the gaps between their current voice and the direction they want to take, and it gives the briefing conversation a concrete starting point rather than a blank page. Step 2 of this Flow covers the company page analysis in full.