How Avery Calculates Your LinkedIn Score: Sub-Components

People often ask how a LinkedIn score is actually calculated, and the honest answer for most tools is that nobody outside the company knows. A single number appears, a few red and green badges follow, and you are left guessing which change would move it. This post opens up how Avery builds its score: where the number comes from, why a single weak line can pull a whole pillar down, and why that changes the order in which you should fix things.

A note on what this post is and is not. It describes how Avery's scoring is structured. It is not a statistical study of profiles, and it contains no aggregate claims about how many profiles score what. Where I use numbers, they come from a constructed example, clearly labeled, so you can follow the arithmetic.

The structure: four pillars, many sub-components, one goal

Avery scores a profile in layers.

Layer 1: Sub-components. Each pillar is made of several smaller judgments, roughly three to five per pillar, and each is scored from 1 to 10. A sub-component is a narrow question, such as how clearly one part of your profile communicates a specific thing to a stranger. Across all four pillars there are around 16 of these.

Layer 2: Pillars. The four pillars are First Impression, Your Story, Proof, and Visibility. Each pillar score is a weighted average of its sub-components, on the same 1 to 10 scale.

Layer 3: The overall score. The four pillar scores are combined into one overall score from 0 to 100. This final step is mode-weighted: it depends on the goal you tell Avery you are pursuing.

Layer 4: Findings. From the sub-component scores, Avery produces roughly nine ranked findings, the specific changes most likely to move your result, in priority order.

The reason for this structure is practical. A single score tells you nothing about what to do. A pillar score tells you where to look. A sub-component score tells you what to change. The layers exist so the number can be turned into an action list.

Why the goal changes the math

The same profile can earn different overall scores depending on what you want it to do, because different goals depend on different pillars. Avery supports distinct modes: job search, pipeline (attracting inbound opportunities), rebrand (changing careers or industries), and thought leadership, with an adjusted version for students. In the standard modes, the weighting that combines the pillars into the overall score is what changes; the student mode also adjusts thresholds for the stage of a career.

For a job search, the first seconds a recruiter spends on your profile matter most, so First Impression and Your Story carry the heaviest weight. For thought leadership, Proof and Visibility carry more, because authority is built on evidence and reach. We unpack that distinction in why the same LinkedIn profile scores differently by goal and in the deeper comparison of job search versus thought leadership scoring.

The practical point for you: before you act on any score, check which goal it was calculated for. A profile with a modest score in thought leadership mode might be quite strong for a job search, and optimizing the wrong pillars wastes effort.

A constructed example: how one weak line moves a pillar

To make the arithmetic visible, here is an illustrative case. These numbers are invented to show how the layers interact. They do not describe any real person or any average.

Imagine a profile where the Proof pillar has four sub-components, scored like this:

Sub-component A: 7. Sub-component B: 6. Sub-component C: 2. Sub-component D: 7.

If each counted equally, the pillar average would be (7 + 6 + 2 + 7) divided by 4, which is 5.5. One weak sub-component, the 2, pulled the pillar from about 6.7 down to 5.5. That is a drop of more than a full point from a single weakness.

Now imagine fixing only that sub-component, raising it from 2 to 6. The pillar becomes (7 + 6 + 6 + 7) divided by 4, which is 6.5, a gain of a full point from one targeted change. Compare that with polishing a sub-component that is already a 7. Raising it to 8 adds only 0.25 to the pillar average. Same effort, one quarter of the return.

That is the whole logic behind the fix order Avery recommends: the lowest sub-components usually offer the largest gains per hour of work. Our post on how Avery prioritizes LinkedIn profile fixes goes further into how the ranking works.

Three things this structure explains

1. Why polishing the strong parts feels productive and moves little

Most people improve what they already like. They refine a headline that was fine, add another skill to a long list, or adjust a photo that was acceptable. Those changes feel like progress because they are visible and easy, but they are usually changes to sub-components already scoring 7 or higher. The arithmetic above shows why the payoff is small. The unglamorous work, a missing quantified result, an About section that never says what you want next, is where the points are.

2. Why a "good" overall score can hide a serious problem

Because the overall score is an average of averages, a strong pillar can mask a weak one. A profile with excellent First Impression and Visibility but very little Proof can still land in a respectable range. The overall number looks acceptable while one pillar is actively costing you credibility with the people who read past the headline. This is why Avery reports pillar scores and findings alongside the total, and why you should read them before you read the big number. Our guide on what separates a 60 from an 80 looks at how the bands behave in practice.

3. Why the projected score is a planning tool

Avery shows a projected score, an estimate of where the profile could land if you made the recommended changes. It is tied to the findings, so it only makes sense if you make the changes and make them well. A projection is a planning tool, not a promise. We explain how to read it in what Avery's projected LinkedIn score means.

A method you can use without Avery: Score Your Own Weakest Three

You do not need software to apply the idea. Here is a 20-minute self-check built on the same logic.

Step 1: Name your goal. Write one sentence: "I want this profile to help me [get interviews / attract inbound leads / change careers / build authority]." Everything else depends on this line.

Step 2: List the four jobs your profile has to do. A stranger should be able to tell, within a few seconds, who you are and what you do (First Impression). They should be able to follow where you are going and why (Your Story). They should see evidence you did what you say (Proof). They should have a reason to find you or remember you (Visibility).

Step 3: Rate yourself honestly on 12 small questions. For each pillar, write three narrow questions and score yourself from 1 to 10. For example, under Proof: "Does my most recent role contain at least one result with a number or a clear outcome?" Under Your Story: "Does my About section say what I want next?" Be harsh. Scoring yourself an 8 on everything produces a self-assessment, not a diagnosis.

Step 4: Circle your three lowest scores. Those are your first fixes, regardless of which pillar they belong to.

Step 5: Fix one, then re-read the profile as a stranger. After each fix, look at your profile on a phone with fresh eyes. Does the change show up where a recruiter would notice it?

This will not replace a full audit, because self-scoring has blind spots. People tend to rate their own writing too generously and to forget what a reader without context sees. But it will show you the principle in action, and it will keep you from the most common mistake, which is polishing the parts you already like.

Where the structure has limits

It is worth being clear about what a structured score can and cannot do.

It measures the profile, not the person. A low score means the page is not communicating well. It says nothing about your ability.

It measures against a goal. A different goal produces a different weighting, and a score is only meaningful relative to the mode it was calculated in.

It cannot see what is off the page. A strong network, a trusted referral, or a reputation in your field can outperform a high-scoring profile. A profile is one input into how people find and judge you.

A higher score is not a guarantee of results. Scores guide your effort. The market, your timing, and your target roles still matter.

We also write about the reverse failure, where a profile is optimized so thoroughly for a number that it stops sounding like a human. If that is a worry, how to make LinkedIn not sound AI-written is a good companion.

What to do with this

Take one idea away: improve your weakest sub-components first, because that is where the arithmetic pays. If you want the full breakdown for your profile, with every pillar scored, every sub-component rated, and roughly nine findings ranked by impact, get your Avery audit. You will see exactly which lines are pulling your score down, in the order to fix them.