Block type distribution

Block type distribution is the breakdown of how often each content block type appears across a set of pages or documents, expressed as a share of all blocks. Modern editors and page builders assemble content from discrete blocks: paragraphs, headings, images, video embeds, code samples, tables, callouts, and interactive widgets. Counting how each type is used tells you what your content is actually made of.

The metric matters because structure shapes how content performs. A knowledge base article that is ninety per cent text blocks is harder to scan than one that breaks ideas up with headings, images, and callouts. A product page with no media blocks may convert poorly. Block type distribution turns a vague sense that pages feel flat into a number you can track and set standards against.

It is most useful as a comparative measure. Looking at the distribution for a single page tells you little, but comparing the distribution across a content library, or against a target mix, shows which templates drift away from the structure you intend.

A worked example shows the shape of it. If a documentation set contains 4,000 blocks and 2,800 of them are text, then text makes up 70 per cent of the distribution. If images account for 600 blocks, they are 15 per cent, and if code samples account for 200, they are 5 per cent. Reading those shares together tells you the library is text-dominant and may benefit from more visual support.

Block type distribution is a set of percentages, one for each block type, that sum to 100. You count blocks by type across the pages in scope, then divide each count by the total. The shares are most useful when you measure them against a target mix or compare them across templates.

1. 1

   Define the scope

   Decide which pages or documents the distribution covers. A single template, a content category, or the whole library each tell a different story, so set the boundary before counting.

2. 2

   Count blocks by type

   Tally how many blocks of each type appear within scope. Most editors expose this through an export or content API, so the count does not have to be manual.

3. 3

   Calculate the share of each type

   Divide the count for each type by the total number of blocks and multiply by 100. The result is that type share of the distribution.

4. 4

   Compare against a target or baseline

   Set the shares next to a target mix or a previous period so you can see which block types are over-represented or under-used relative to the structure you intend.

A metric tree connects the distribution to the choices that produce it. The overall mix at the top is the result of authoring habits, the templates people start from, and the rules editors apply during review. Decomposing it this way moves the analysis from observing a skewed mix to fixing the upstream cause, which is usually a default template or a missing guideline.

There is no universal correct mix, because the right distribution depends entirely on content type. A reference manual leans technical, a marketing landing page leans visual, and a tutorial sits in between. The ranges below describe typical block shares for common content types and are meant as starting points, not rules.

Improving block type distribution is about shaping the structure authors start from and reach for, rather than reworking finished pages one at a time. The actions below address the usual causes of a skewed mix: weak templates, no agreed target, and content that is never reviewed for structure.

1. 1

   Treating one mix as correct for everything

   A landing page and a reference manual should have very different distributions. Holding every page to a single target mix produces uniform content that suits no purpose well.

2. 2

   Counting blocks without weighting size

   A single large image block carries more visual weight than a one-line callout, yet a raw count treats them equally. Be aware that share by count can understate the prominence of large media.

3. 3

   Chasing the number instead of the goal

   Adding image blocks purely to hit a media share target produces decorative padding. Let the content goal drive the mix, and use the distribution to confirm it, not to manufacture it.