Sections: the block-by-block anatomy of a send

What this screen is

The sidebar calls it Sections. Open it and the page is headed Newsletter structure per brand, under a subtitle reading "Section consistency, occupancy, order stability, and structural metrics per brand." You come here to see a brand's template skeleton without opening thirty emails one at a time.

Newsletrix reads each analysed email as a stack of named blocks, with names like hero, product_grid, category_cta, blog_teaser and footer. Sections gives you two views of that stack. Occupancy tells you how often each block shows up across the editions inside your filter, and the consistency heatmap tells you where each block sat inside each edition, as a position number on a coloured cell.

Those names are Newsletrix's own reading of the email's visual structure. They are not labels the sender wrote. Nothing fixes the vocabulary, so each block gets whatever label suits it, and two similar emails can end up with different names for the same block. Most of the odd numbers on this screen trace back to that.

Opens and clicks are not here. Newsletrix receives these emails as an ordinary subscriber, so it can describe what a sender chose to build and nothing at all about how their audience reacted. Despite the word "stability" in the subtitle, no stability score appears anywhere on the screen either.

Use it one brand at a time. Leaving the Brand filter on "All brands" pools every sender you track into a single denominator, which flattens every occupancy percentage and mixes unrelated templates into one heatmap.

Open it when

• You are reverse-engineering a competitor's newsletter template before designing your own.
• A brand's emails feel inconsistent and you want proof of which blocks are permanent fixtures and which were one-off experiments.
• You are deciding where to place a new block, such as a product grid, blog teaser or referral module, and want to see where competitors put theirs.
• You need to show a client or a team the ordered anatomy of one brand's newsletter over the last quarter.
• You suspect a template redesign: a block that used to sit at position 2 now sits at position 6, or has stopped appearing entirely.

Screen anatomy

The page is a single column. Header at the top, then the filter card, four tiles, the occupancy chart, and the heatmap at the bottom. Numbers on the mock match the walk-through underneath it.

1. Filter card Three fields side by side. Brand is a dropdown that starts on the placeholder "All brands"; Date from and Date to are date pickers, both empty by default. There is no Apply button, so every change reloads the whole page immediately.
2. Total editions The denominator for everything else on the screen. If it reads 128, a block at 100% occupancy appeared in all 128 of those emails.
3. Avg links / section Total links in the emails divided by the total number of blocks listed. Two unrelated totals, one over the other. No link is ever attributed to a specific block anywhere in Newsletrix.
4. Section occupancy across editions (top 10) Horizontal bars, one per block name, sorted by how many editions contain it and cut to the ten most frequent. The axis runs 0 to 100 and never goes past it.
5. Section consistency heatmap (section × edition) Blocks as rows, edition dates as columns, newest edition on the left. The number in a cell is the block's position inside that edition, counting from 1. Darker means earlier.
6. Short rows shift left A row only holds cells for the editions where that block appeared, so blog_teaser here has three cells against five date columns and they do not line up with the dates above them. Read each row as a sequence of appearances rather than a calendar.
7. Page header and help button The title, the subtitle, and a round question-mark button on the right. It opens a fixed explainer called "Structure That Drives Results".
8. Avg sections / edition and Unique sections The other two tiles. The first is the mean number of blocks per email; the second is how many distinct block names exist in the filtered set. Compare them to each other rather than in isolation.
9. Loading state While the screen is loading, everything below the filter card is replaced by a single spinner. With no Apply button, typing a date by hand can set off several of these one after another.
10. Empty state With nothing matching, the four tiles read 0, the occupancy card keeps its heading and its 0 to 100 axis but draws no bars, and the heatmap card disappears completely. There is no illustrated empty screen.

Every panel explained

Total editions

How many newsletter editions fall inside the current brand and date filter.

How it is calculated. One count per distinct analysed email inside the filters. An email only counts once its analysis has finished, so newsletters that have arrived but not yet been analysed are invisible here. Editions that produced no blocks at all still count.

How to read it. Treat it as the denominator for every percentage on the page. Below roughly 8 to 10 editions, occupancy becomes coarse: over 3 editions the only possible values are 33.3, 66.7 and 100.

Avg sections / edition

The mean number of blocks in an email inside the current filter.

How it is calculated. Every block from every edition is counted, then divided by Total editions and rounded to one decimal. Repeats count. A block name that appears twice inside one email adds two.

How to read it. A rough measure of template length. Four to six is a compact email; twelve or more is a long newsletter assembled from many independent modules.

Avg links / section

A link-density figure for the average block.

How it is calculated. All links found in the emails inside the filters, divided by every block listed in those same emails, rounded to one decimal. No link is left out of the top of that fraction.

How to read it. High values point to product-grid-heavy templates. Low values point to editorial blocks with a single call to action. Compare brands with the same date range rather than reading the absolute number.

Unique sections

How many distinct block names exist across the filtered set.

How it is calculated. A count of distinct names, exactly as they appear. It is case-sensitive, and near-identical names are never merged.

How to read it. Always read it against Avg sections / edition. Close together means one fixed template. Several times larger means either the brand improvises every send, or the same block is picking up a different label from one email to the next. The occupancy chart separates the two. Genuine variety leaves a long tail of distinct names; naming drift leaves near-duplicates such as hero and hero_banner.

Section occupancy across editions (top 10)

For each of the ten most frequent blocks, the share of editions that contain it.

How it is calculated. For every distinct block name, count how many editions contain it at least once, divide by Total editions, multiply by 100 and round to one decimal. Blocks are sorted by raw appearance count, descending, and the chart draws only the first ten. The axis runs from 0 and stops at 100.

How to read it. Split the bars into three bands. Anything at or near 100% is the brand's fixed furniture, usually the header, the hero and the footer. Between roughly 20% and 60% sit the situational blocks, tied to campaigns, seasons or whatever content existed that week. Under 10% you are looking at an experiment, or at naming noise from a single send. A block sliding out of the top band across two consecutive quarters is the clearest early signal of a template change you will get here.

Section consistency heatmap (section × edition)

A matrix with blocks as rows and editions as columns, newest edition first. Each cell carries the position of that block inside that edition.

How it is calculated. Column headers are the send dates of the editions in scope, formatted like "Mar 14, 2026", each with a hover title showing the date and the subject line. A cell's number is the block's place in that edition, counting from the top. Colour follows that position in four fixed steps. Positions 1 to 3 take the darkest indigo, 4 to 5 mid, 6 to 7 light, 8 and beyond the palest. Hovering shows "Position: N". The grid scrolls horizontally, gains its own vertical scroll once the rows outgrow the card, and keeps the Section column and header row pinned.

How to read it. Scan one row at a time, left to right. A run of identical dark cells carrying the same number is a block that never moves. Scattered numbers mean it floats, and gaps mean the brand skipped it that week. Columns are far less trustworthy than rows, for the reason below.

Help modal: "Structure That Drives Results"

The round question-mark button opens a short explainer beginning "Newsletter Structure Analysis reveals how your content organization impacts reader engagement." and listing Layout Patterns, Section Organization, Visual Hierarchy, Content Density, Navigation Elements and Template Consistency.

How it is calculated. It is not. The text is fixed, identical for every account, and it never touches your data.

How to read it. As positioning, not as a metric list. Visual hierarchy, content density and template consistency are not computed anywhere on this screen.

Empty and loading states

There is no illustrated empty state. With zero matching editions you get four zeroes, an occupancy card that still shows its heading and axis but has nothing to plot, and no heatmap card.

How it is calculated. The heatmap card appears only when there is at least one block to draw, so it vanishes rather than showing an empty grid. The four tiles behave differently again. They are hidden outright when the screen fails to load, so a failure shows no tiles at all rather than zeros, and nothing on screen announces it. The grey line "No data available" belongs to that failure, not to a genuinely empty result. It stands in for the chart while nothing has loaded.

How to read it. Four zeroes with an empty chart almost always mean the filter is too tight, or that the sends in that window have not been analysed yet. No tiles at all, with "No data available" where the chart should be, means the screen never finished loading. Reload the page.

Metric definitions

Filters and controls

Some controls are deliberately absent, so you can stop hunting for them. Sections has no export of any kind, no sort control, no search box or section-name search, no date presets such as "Last 30 days", and no way to select more than one brand at once. For a downloadable version of the same underlying data, use the Newsletter section flows drill down table on the Structures screen, which has an Export CSV button.

How to use it

1. Pick one brand, then a window with enough sends Set Brand to a single sender and set Date from and Date to so that Total editions reads at least 8, ideally 10 or more. Below that, occupancy percentages jump in coarse steps and tell you very little.
2. Read the four tiles as one template profile Avg sections / edition gives template length. Compare it with Unique sections: close together means one fixed template, several times larger means variety or inconsistent naming. Keep Avg links / section as a cross-brand density figure, not a block-level fact.
3. Sort the occupancy bars into three bands Near 100% is fixed furniture, 20% to 60% is situational, under 10% is experiment or noise. Write down the fixed set. That list is the brand's actual template, whatever their design system claims.
4. Move to the heatmap and read rows, not columns For each block in your fixed set, check whether its position number is stable. A block that is always 1 or always 2 is anchored. A block whose number wanders between 3 and 8 is placed by whoever built that send.
5. Re-run the same brand on the previous quarter Change only the two date fields. A block that moved bands, or a position number that shifted by three or more, is a template redesign you can date to within a few sends.
6. Take the fixed set into your own template review Compare the blocks a competitor ships in every email with the ones you ship occasionally. Those gaps are the cheapest structural changes available to you.

Limits and caveats

• Block names and their order come from Newsletrix reading the email's visual structure, not from labels the sender wrote. Two similar emails can end up with different names for the same block.
• Avg links / section is a ratio of two separate totals. No link is attributed to a specific block anywhere in the product, and the link count includes unsubscribe, preference-centre and social links.
• The occupancy chart shows only the ten most frequent blocks. Everything else is invisible on this screen.
• Heatmap rows hold one cell per appearance, not one per edition, so rows with gaps shift left and stop aligning with the date headers above them.
• A block name repeated inside one email reports the position of its first occurrence for every repeat.
• Emails that have not been analysed are excluded entirely. Emails where no links were found still count their blocks, which pulls Avg links / section down.
• Nothing on this screen is a performance measurement. Newsletrix subscribes to these newsletters like any other reader and cannot see another sender's opens or clicks.

FAQ

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