- Where
- Analysis / Brands
- App route
/brand-comparison- Answers
- How do the brands I track stack up?
- Needs
- Analysed newsletters; 2+ send days for cadence
- Updates
- After each analysis; brand list lags up to 10 min
What this screen is
The per-newsletter screens answer "how good was this email". Brands answers "how does this sender behave, compared with that one". Each analysed newsletter is grouped under its brand and averaged into one row. That row carries the email count, average spam score, SPF, DKIM, DMARC and BIMI pass counts, average size, promotion intensity, an overall quality score, and an estimated open rate and click rate.
There are four tabs. Overview holds the Deliverability health card and the nine-column brand table. Scoring turns each brand into one 0-100 number and a letter grade across five weighted pillars. Editorial cadence measures publishing rhythm and flags brands that have gone quiet. Compare brands puts 2 to 5 brands side by side on performance, volume, content, shared themes and category breakdowns. Only the comparison waits for a button press.
Two kinds of numbers sit next to each other here. Email count, size, spam score, authentication results, send days and cadence statistics are measured from the messages your tracking address received. Estimated open rate and CTR, effectiveness, word counts, image ratios, email types, categories, objectives and CTA phrases are Newsletrix's own reading of the content of each email. Newsletrix subscribes like any other reader and never sees a competitor's real opens or clicks. There is also no minimum sample anywhere: a brand with two analysed emails looks as confident as one with two hundred, so check Email Count before trusting a row.
Open it when
- You need one number and one letter grade per competitor for a deck; the Scoring tab has a Save as PDF button.
- A competitor has gone quiet and you want to know whether that is unusual for them; the cadence tab flags Quiet and Silent against each brand's own interval.
- You want to see which tracked senders fail SPF, DKIM, DMARC or BIMI, to benchmark your own setup.
- You are planning a send calendar and want the weekdays your peer set actually uses; the Publishing calendar and the Day of week distribution table both show it.
- You suspect two brands are fighting over the same categories, subject keywords or CTA phrases; the Overlap card lists only what every selected brand shares.
Screen anatomy
The mock shows the Overview tab as it opens with three tracked brands; the Scoring and Compare brands tabs are shown further down.
Brand comparison metrics
Compare brands by email count, spam score, size, promotion level, and overall scoring.
| Brand | Email Count | Spam Score (0-10) |
DNS Auth (SPF/DKIM/DMARC/BIMI) |
Avg Size (KB) |
Promotion % (0-100) |
Avg. Score | Est. Open Rate (%) Industry 15.7% |
Est. CTR (%) Industry 2.01% |
|---|---|---|---|---|---|---|---|---|
| About You | 42 | 1 | SPF: 42/42 DKIM: 42/42 DMARC: 39/42 BIMI: 0/42 |
68.41 KB | 34.2% | 88.6 | 18.6% | 2.35% |
| Deichmann | 27 | 5 | SPF: 27/27 DKIM: 25/27 DMARC: 19/27 BIMI: 0/27 |
142.07 KB | 78.4% | 58.9 | 14.2% | 1.80% |
| Zalando | 18 | 3 | SPF: 18/18 DKIM: 17/18 DMARC: 10/18 BIMI: 0/18 |
91.20 KB | 55.0% | 79.8 | 16.9% | 2.10% |
- Tab bar Overview (the default), Scoring, Editorial cadence and Compare brands. Switching between them is instant. The cadence tab redraws when you change one of its filters, and the comparison waits until you press its button.
- Deliverability health One expandable row per brand with an overall auth chip, average spam score, sample count and four pillar chips. The worst brand sorts to the top and opens automatically; the expanded row shows a bar per pillar with pass count over sample count and a Fix guide button.
- Brand comparison table Nine columns: Brand, Email Count, Spam Score (0-10), DNS Auth (SPF/DKIM/DMARC/BIMI), Avg Size (KB), Promotion % (0-100), Avg. Score, Est. Open Rate (%) and Est. CTR (%). One row per brand, sorted by email count and then name. The last two headers carry a fixed Industry benchmark chip that does not come from your data.
- Legend The colour key for spam score, email size and DNS authentication. Colours encode the bucket, not the exact value.
- Page header The title "Brand comparison metrics", its sub-line, and a help icon that opens the "Multi-Brand Performance Analysis" explainer.
- Scoring tab A ranked grid of brand cards with a 0-100 composite, a letter grade and five weighted pillar bars, plus Save as PDF. Shown in the next mock.
- Editorial cadence tab Four KPI tiles (Brands tracked, On track, Quiet, Silent), an info note, a filter card (Brand, From date, To date), the eight-column cadence table with its own legend, the Publishing calendar and the Interval distribution histogram.
- Compare brands tab A brand picker with search, checkbox tiles and saved watchlists. After you press Compare selected brands: Performance, Volume and Content tables with Δ and Winner columns, the Overlap card and six category breakdown tables.
- Empty states The Overview table says "No brand data available. Please analyze some newsletters first.", the cadence tab says "No cadence data available for the selected filters.", and the Compare tab shows nothing until you run a comparison.
Every panel explained
Deliverability health (Overview)
SPF, DKIM, DMARC and BIMI pass rates and the average spam score per brand, with a Fix guide for each pillar.
How it is calculated. For each pillar, the pass rate is the number of the brand's emails whose headers recorded a pass, divided by the number of its emails that have header metrics. Bands: 95% and above Pass (green), 80 to 94 Partial (amber), 50 to 79 Weak (orange), below 50 Fail (red). The chip beside the brand name is the plain mean of the four pillar rates on the same bands. Brands with no header metrics are left out of this card. Spam score prints to one decimal: 2 or lower reads good, up to 5 acceptable, above 5 bad.
How to read it. The top row is the brand with the weakest authentication footprint. 100% SPF and DKIM with 0% BIMI just means BIMI was never set up; a brand failing DMARC has a real inbox-placement problem you can benchmark yourself against.
Results come from the authentication headers stamped on the copies your tracking mailbox received, not from a live DNS lookup, so they can differ from an external audit. The Fix guide gives the standard steps for that pillar, not an audit of that brand. This card uses four bands (95/80/50) while the table below uses three (80/50), so a brand can be Partial here and green there.
Brand comparison table and legend (Overview)
One aggregate row per brand across nine columns, with a colour legend pinned underneath.
How it is calculated. Email Count is the number of distinct analysed newsletters. Spam Score is the mean per-email spam score, rounded to a whole number: 0-2 Good, 3-5 Moderate, 6 and above High. DNS Auth prints pass count over the number of emails with header metrics for each check, green at 80% or more, amber from 50 to 79%, red below. Avg Size is the mean raw size in KB to two decimals: 50 KB or less Good, 50 to 100 OK, over 100 Large. Promotion % is the mean promotion percentage to one decimal, drawn as a bar whose fill is the value itself, green to 30, amber to 60, red above. Avg. Score is the mean quality score to one decimal, green at 80 or more, blue from 60, amber from 40, red below. Est. Open Rate and Est. CTR average the per-email estimates, to one and two decimals. Rows sort by Email Count descending, then name. The Industry chips are a fixed Mailchimp 2024 benchmark for the industry in your benchmark settings (retail by default: 15.68% open, 2.01% CTR) and carry a warning triangle because that source is older than 18 months.
How to read it. Scan Spam Score and Avg Size first, because those are measured. Then Avg. Score as the quality summary. The last two columns are estimates. Rank brands with them; do not quote them in a client report as measured performance. The DNS colour divides by the sampled count, so a brand with one sampled email flips bands on a single message.
An average size of exactly 0 prints N/A, and a Promotion %, Avg. Score, Est. Open Rate or Est. CTR of exactly 0 prints a dash, the same as missing data. Spam Score is the exception: a real 0 prints 0 and only a missing value prints a dash. A brand with no header metrics shows 0/0 in red for all four DNS checks.
Weighted scoring index (Scoring)
One card per brand, ranked by composite score, each with a 0-100 number, a letter grade, the note "N newsletters · n/5 pillars" and five weighted pillar bars. The card header carries the pillar legend and a Save as PDF button.
How it is calculated. Content (30%) is the brand's Avg. Score. Deliverability (25%) is the mean of the SPF, DKIM and DMARC pass rates (BIMI excluded) minus a spam penalty of 5 points per point of average spam score, capped at 40. Cadence (20%) is 100 minus the interval standard deviation as a share of 14 days, so 0 days of variance scores 100 and 14 or more scores 0. CTA (15%) is the estimated CTR divided by 10, so a 10% CTR scores 100. Readability (10%) is 100 minus twice the distance of Promotion % from 50, so it peaks at 50% promotional content and reaches 0 at 0% or 100%. Each pillar is clamped to 0-100; a pillar that cannot be computed is dropped and the remaining weights are scaled up to fill the gap. Grades: A at 85 or more, B at 70, C at 55, D at 40, F below. A brand with no computable pillar shows a dash for both.
How to read it. The number is a portfolio-level summary for a report; the bars show which pillar drags it down. Compare grades only between cards with the same pillar count, because a 4/5 card was scored on rescaled weights.
The Cadence pillar fills in only when the brand also appears in the Editorial cadence tab for the date range set there (the last 90 days by default), so changing those dates silently changes Scoring. "Readability" is a promotion-balance proxy, not a reading-level score, and CTA is an AI estimate, not measured clicks. Save as PDF opens your browser's print dialog rather than handing you a ready-made file.
Cadence KPI row (Editorial cadence)
Four tiles, Brands tracked, On track, Quiet and Silent, counted over the brands in the current cadence filter. They appear only when at least one brand matches the filter.
How it is calculated. A brand is Silent when the days since its last send have reached its average interval plus two standard deviations, Quiet at the average plus one standard deviation, and On track otherwise. The standard deviation is floored at half a day. A brand with fewer than two distinct send days in the window gets no status and counts only in Brands tracked. On track shows "N% of tracked"; Quiet shows "Overdue - monitor closely" and Silent shows "Haven't sent in 3x their usual interval" when non-zero.
How to read it. Quiet means overdue relative to that brand's own rhythm; Silent means well past it. Days since last send are counted from today, so keep the To date at today when you read these tiles.
The tile says three times the usual interval; the rule is the average plus two standard deviations. A brand that sends every 7 days with a 1 day deviation is Silent after 9 days, not 21.
Cadence table (Editorial cadence)
Eight columns per brand: Brand (pill plus a cadence badge), Total Editions, Per Week, Per Month, Avg Interval (days), Median Interval (days), Std Dev (days) and Min / Max (days), with its own legend.
How it is calculated. Total Editions counts distinct calendar days with a send, so two emails on one day count once. Per Week divides that by the window length in weeks and Per Month by 30-day months, where the window is your From and To dates, 90 days by default. Intervals are the day gaps between consecutive send days; from them come the average, median, standard deviation (0 with a single interval), minimum and maximum, all 0 when there is no gap. The badge reads red "Silent · Nd", amber "Quiet · Nd", or a grey "Next ~date" forecast equal to the last send plus the rounded average interval.
How to read it. Avg Interval is the rhythm, Std Dev is how reliable it is. Interval colours: 7 days or less green (daily or weekly), 8 to 14 blue (bi-weekly), 15 to 30 amber (monthly), over 30 red (infrequent). Std Dev: 3 days or less green, 4 to 7 amber, over 7 red.
Per Week and Per Month divide by the filter window, not the brand's own active span, so a brand you started tracking mid-window looks less frequent than it is.
Publishing calendar (Editorial cadence)
A calendar heatmap, one cell per day, tinted by how many newsletters landed that day across all brands in the filter, with month labels, a Mon to Sun summary bar and a Less/More legend.
How it is calculated. Sends are summed per date across brands. The grid runs from the Monday of the earliest send week to the Sunday of the latest. Tint is the day's count divided by the busiest day: 0 grey, up to a quarter lightest, then half, three quarters, and solid above that; when the busiest day has a single send, every active day is solid. The subtitle reads "N total · peak M/day" and names the busiest weekday.
How to read it. Vertical stripes mean a fixed send day; gaps mean pauses. Pick one brand in the Brand filter to see its own pattern, because with All brands a shared spike can be two different senders.
Interval distribution histogram (Editorial cadence)
A bar chart titled "Distribution of days between newsletters", x axis "Interval (days)", y axis "Frequency", pooling every gap from every brand in the filter.
How it is calculated. Bin width is the largest interval divided by 20, rounded down, with a minimum of 1 day, so there are at most 20 bins. Each bar is labelled by its lower edge, for example "7+ days".
How to read it. A tall bar at 7+ days means your watchlist is mostly weekly; a long right tail means some senders go dormant. Because the bin width follows the data, the chart is not comparable across two date ranges.
Brand picker and watchlists (Compare brands)
A searchable list of every brand with its analysed newsletter count, checkbox tiles, an "n/5 selected" counter, saved watchlists and the Compare selected brands button.
How it is calculated. Select 2 to 5 brands: below 2 the button is disabled, at 5 the remaining tiles are disabled. A watchlist stores a name and the brand set in your browser; saving under an existing name (case-insensitive) replaces it, and applying one drops brands that no longer exist and trims to 5. A brand analysed in the last few minutes can take up to 10 minutes to show up in this list.
How to read it. The count beside each brand is how many analysed newsletters it has for your account. It ignores the workspace selector, unlike every aggregate elsewhere on the page.
Performance metrics (Compare brands)
Rows "Avg Open Rate (Est.)", "Avg CTR (Est.)" and "Effectiveness score", one column per selected brand in the order you picked them, plus Δ and Winner columns.
| Metric | About You | Deichmann | Zalando | Δ | Winner |
|---|---|---|---|---|---|
| Avg Open Rate (Est.) | 18.6% | 14.2% | 16.9% | 4.4 pp | About You |
| Avg CTR (Est.) | 2.4% | 1.8% | 2.1% | 0.60 pp | About You |
| Effectiveness score | 0/100 | 0/100 | 0/100 | - | tie |
| Metric | About You | Deichmann | Zalando | Δ | Winner |
|---|---|---|---|---|---|
| Total newsletters | 42 | 27 | 18 | 24 | About You |
| Unique subjects | 41 | 25 | 18 | 23 | About You |
| Days active | 38 | 24 | 17 | 21 | About You |
| Avg per day | 1.1 | 1.1 | 1.1 | - | tie |
How it is calculated. Each cell averages the per-email estimates for that brand, to one decimal, printed as 0 when missing. Δ is the largest value minus the smallest across the selected brands, in percentage points. Winner names the brand with the highest value and tints the row green; when every brand ties, the cell reads "tie" and Δ shows a dash. Effectiveness renders as "x/100".
How to read it. The winner leads on that row only. Δ tells you whether the gap is worth acting on; a 0.3 point spread on an estimated rate is noise.
All three rows are estimates, and the analysis does not currently produce an effectiveness value at all, so that row reads 0/100 for every brand. These averages cover the brand as a whole, so if another Newsletrix account tracks it too, its copies can land in the figures. Select a workspace and every comparison table narrows to the newsletters your tagged tracking addresses received, which removes that effect.
Volume and content metrics (Compare brands)
Two tables. Volume: "Total newsletters", "Unique subjects", "Days active", "Avg per day". Content: "Avg word count", "Avg image ratio", "Median image ratio".
How it is calculated. Total newsletters counts every analysed newsletter; Unique subjects counts distinct exact subject strings; Days active counts distinct calendar days with a captured send; Avg per day is total divided by days active, to one decimal. Higher wins on all four. Word count and image ratio average the per-email estimates to one decimal (word count then rounded to a whole number); the median is the middle value, or the mean of the two middle values. Avg word count treats lower as better, so its winner is the shortest brand; the image ratio rows treat higher as better and show Δ in percentage points.
How to read it. Days active is not the age of the tracking, and Avg per day can never fall below 1.0. A personalised or dated subject line inflates Unique subjects. A big gap between average and median image ratio means a brand alternates between text-only and image-heavy sends; emails without an estimate are simply left out of the mean.
Overlap - what these brands play on together (Compare brands)
Three panels, Subject keywords, Product categories and CTA phrases, listing only the items every selected brand shares, each with an "N shared" count, per-brand counts and a leader badge.
How it is calculated. Each brand contributes its top 5 subject keywords (words of three or more letters from the subject lines, with common words ignored), its top 5 promoted categories and its top 8 CTA phrases. A label reaches the panel only when every selected brand has it on that list, and matching ignores case and surrounding spaces. Rows sort by total count and the first 8 per panel are shown. The leader badge marks the first brand with the highest count and is hidden when every count is identical.
How to read it. These are the shared plays. If "sale" is shared and one brand's count is triple the others, that brand leans on discounting hardest.
Adding a fifth brand often empties the card ("No common ground yet") because one brand's sixth keyword is no longer a candidate. A single empty panel shows its own hint, for example "No keyword in every brand's top 5." Accented subject words are split into fragments rather than kept whole.
Category breakdown cards (Compare brands)
Six pivot tables: "Top categories", "Email type distribution", "Email length distribution", "Top business objectives", "Day of week distribution" and "Top subject keywords". Rows are labels, columns are brands in the order you picked them, each cell a proportional bar, plus a Leader column.
How it is calculated. Categories, objectives and subject keywords use each brand's top 5 only; email type, email length and day of week include every value that occurs. Labels that differ only in case or spacing count as one row. Rows sort by how many brands have a non-zero count, then by total, capped at 10. Bar width is the cell count divided by the largest count anywhere in that table, with a 2% floor; non-leading bars are faded and a zero cell shows a dash. Leader marks the single brand strictly ahead of the runner-up.
How to read it. Rows near the top are what the market does together; a lone tall bar in one column is something only that brand does. Day of week comes from the email's date header and is measured; type, length, categories and objectives are AI classifications.
Metric definitions
| Metric | What it means | How it is produced | Scale |
|---|---|---|---|
| Email Count | Newsletters analysed for the brand | Distinct analysed newsletters grouped by brand name | Integer |
| Spam Score | Header-derived spam risk of the received copies | Per email: penalty points for SPF, DKIM and DMARC failures (3 each, softer results 1 to 2), plus any spam-filter score already stamped in the headers, plus 5 if the headers flag it as spam; capped at 10, then averaged | 0-10, lower better |
| DNS Auth | Emails that passed SPF, DKIM, DMARC, BIMI | Pass count over emails with header metrics | Count/count |
| Avg Size (KB) | Average raw email size | Mean of each email's raw size in KB | KB |
| Promotion % | How discount-heavy the copy is | Per email: discount wording in the copy x15 (max 40) + promo keywords present x3 (max 30) + AI promo-frequency rating (high 20, medium 10, low 5) + AI-detected discounts x10 (max 30), capped at 100; then averaged | 0-100 |
| Avg. Score | Overall email quality | Per email: 100, minus 5 per spam point, minus (KB over 100)/10 up to 20, minus (Promotion % over 70)/3, plus (effectiveness minus 50)/10 and (est. open rate minus 20)/5 when present, clamped 0-100; then averaged | 0-100 |
| Est. Open Rate / Est. CTR | AI-estimated engagement, not measured | Mean of the per-email estimates | Percent; CTR to 2 decimals (1 in Compare) |
| Industry chip | Static reference beside the two estimate headers | Mailchimp 2024 value for your benchmark industry: open rate retail 15.68, SaaS 19.29, media 22.15, B2B 21.56, nonprofit 25.17; CTR 2.01, 2.08, 4.62, 2.72, 2.79 | Percent; flagged stale after 18 months |
| Weighted scoring index | One composite brand score | Content 30%, Deliverability 25%, Cadence 20%, CTA 15%, Readability 10%; missing pillars dropped and weights rescaled | 0-100; A 85+, B 70+, C 55+, D 40+, else F |
| Scoring pillars | The five inputs to the index | Content = Avg. Score. Deliverability = mean of SPF, DKIM, DMARC rates minus min(40, 5 x spam score). Cadence = (1 - std dev / 14) x 100. CTA = est. CTR / 10 x 100. Readability = 100 - 2 x |50 - Promotion %| | Each 0-100 |
| Total Editions | Distinct send days in the window | Calendar days with at least one send | Integer |
| Per Week / Per Month | Publishing frequency | Total Editions divided by window days / 7 and window days / 30; default window 90 days | 2 decimals |
| Avg / Median Interval | Typical gap between editions | Mean and median of positive day gaps between consecutive send days | Days; 7 or less green, 8-14 blue, 15-30 amber, over 30 red |
| Std Dev | Consistency of the gaps | Standard deviation of those gaps; 0 with fewer than 2 gaps | Days; 3 or less green, 4-7 amber, over 7 red |
| Min / Max | Shortest and longest gap | Smallest and largest interval; 0 when none | Days |
| Quiet / Silent | Overdue against the brand's own rhythm | Days since last send at or above average + 1 std dev (Quiet) or + 2 std dev (Silent); std dev floored at 0.5 day | On track / Quiet / Silent / none |
| Next expected send | Forecast of the next edition | Last send date plus the rounded average interval; only when the average is non-zero | Date |
| Effectiveness score | AI marketing-effectiveness score | Mean per brand, shown as x/100; the analysis does not currently produce it, so usually 0 | 0-100 |
| Volume rows | Total newsletters, Unique subjects, Days active, Avg per day | Counts of newsletters, distinct subjects and distinct send days; total divided by active days | Integers; Avg per day 1 decimal |
| Avg word count | Typical length | Mean of the per-email word count estimates, rounded | Words; lower wins |
| Avg / Median image ratio | Share of visual content | Mean and median of the per-email image-to-text estimates | 0-100 percent |
| Δ | Spread across the selected brands on one row | Largest value minus smallest; dash when all tie | Row unit; pp for rates |
Filters and controls
| Control | What it does | Default |
|---|---|---|
| Tabs | Switch between Overview, Scoring, Editorial cadence and Compare brands. No data reloads on switch. | Overview |
| Workspace selector | The global workspace in the sidebar scopes Overview, Scoring, cadence and comparison data to newsletters delivered to tracking addresses carrying that group tag. Brand picker counts are not scoped. | All workspaces |
| Cadence: Brand | Limits the cadence tab to one brand. Options read "Brand (count)". | All brands |
| Cadence: From / To date | Sets the cadence window. Empty means the last 90 days ending today. A From date after the To date, or a date not in YYYY-MM-DD form, is rejected. | Empty (last 90 days) |
| Deliverability rows | Click a brand row to expand or collapse its pillar bars; Fix guide opens the steps for that pillar, Close hides them. | Worst brand expanded |
| Scoring: Save as PDF | Opens the browser print dialog with a print layout of the scoring cards. | - |
| Compare: search | Filters the brand list by name, with a clear button. No match shows "No brands match" with your text. | Empty |
| Compare: brand tiles | Select 2 to 5 brands; the counter reads "n/5 selected" and a clear link empties the selection. Tiles disable once 5 are picked. | None selected |
| Compare: Watchlists | Name the selection and press Save (or Enter) to keep it in this browser; click a chip to reapply it or the trash icon to delete it. Disabled below 2 brands. | None |
| Compare selected brands | The only control that runs the comparison. Disabled outside 2 to 5. | - |
A few things are deliberately missing. There is no CSV or data export, so the Scoring print button is the only way to get anything out. The Overview and Scoring tabs carry no date range or brand filter and always cover everything analysed. No screen here applies a minimum sample threshold.
How to use it
- Read Email Count before anything else On Overview, note how many analysed newsletters each brand has. A row built on three emails will swing with the next send; treat its averages as provisional.
- Sort out deliverability Expand the top row of Deliverability health, note which pillar fails, and compare it with your own SPF, DKIM, DMARC and BIMI setup. A competitor failing DMARC is a gap you can exploit; BIMI at 0% usually just means it was never configured.
- Set the cadence window, then read Quiet and Silent On Editorial cadence, leave the dates empty for the last 90 days or set the period you care about, keeping the To date at today. Read Avg Interval and Std Dev per brand before you trust a flag.
- Only then open Scoring The Cadence pillar uses the window you just set. Compare grades between cards with the same pillar count only; a 4/5 card was scored on rescaled weights.
- Compare 2 to 5 brands and save the set Pick the brands, press Compare selected brands, read the Winner and Δ columns, then the Overlap card and the breakdown tables. Save the selection as a watchlist so the next review is one click.
Run the Compare tab with a workspace selected. It scopes every comparison table to the newsletters your tagged tracking addresses received, which also keeps other accounts' copies of the same brand out of the averages.
Limits and caveats
- Only Email Count, Avg Size, Spam Score, the DNS pass counts, day-of-week counts and cadence statistics are measured from the messages. Estimated rates, Effectiveness score, word counts, image ratios, email types, lengths, categories, objectives and CTA phrases are estimates Newsletrix makes from the content of each email.
- Authentication results reflect what your receiving mailbox recorded on the copies it got, not a live DNS check of the sender's domain.
- Nothing is weighted by sample size and there is no minimum sample threshold.
- The Weighted scoring index mixes measured and estimated inputs, uses proxies for two pillars, rescales weights when a pillar is missing, and takes its Cadence pillar from whatever date range the Editorial cadence tab is set to.
- Cadence counts distinct send days, so burst senders are undercounted; Per Week and Per Month divide by the filter window rather than the brand's active span; a To date in the past makes every brand look Silent because days since last send are counted from today.
- Unless a workspace is selected, the Compare brands tab can include the same brand's newsletters collected by other accounts. Its Effectiveness score row is usually 0/100 because the analysis does not currently produce that value.
- Figures here can lag a freshly analysed newsletter by a few minutes, and a brand you have only just started tracking takes about ten minutes to appear in the brand list and a little longer in the cadence brand filter.
FAQ
Why are Est. Open Rate and Est. CTR different from what my email platform reports?
They are not measured. Both are produced by the AI analysis of each email's content and then averaged per brand. Newsletrix receives competitor newsletters as an ordinary subscriber and never sees a sender's real opens or clicks, so use these columns to rank brands against each other, not as reported performance. The Industry chip next to each header is a fixed Mailchimp 2024 average for the industry chosen in your benchmark settings, not your data, and it shows a warning triangle because that source is more than 18 months old.
A brand shows a dash in the Avg. Score or Promotion % column. Is that missing data or zero?
Usually missing data, but the two look identical: an average of exactly 0 also prints a dash, and an average size of exactly 0 prints N/A. Spam Score is the one column that tells them apart, because a real 0 prints as 0 and only missing data prints a dash. If the DNS Auth cell reads 0/0 for that brand, no header metrics exist for it at all, and every column built from header metrics is genuinely missing.
Why does a brand appear in the Overview table but not in the Compare brands picker?
The Overview table lists every brand name that appears on an analysed newsletter. The picker and the Compare brands tab list only the brands in your brand list. A newsletter carrying a name with no matching brand entry shows up in one place and not the other, so the two lists can differ.
What exactly makes a brand Quiet or Silent?
Both are measured against the brand's own rhythm, not a fixed number of days. Quiet means the days since its last send have passed its average interval plus one standard deviation; Silent means they have passed the average plus two standard deviations. A floor of half a day is applied to the standard deviation so very regular senders can still be flagged. A brand with fewer than two distinct send days in the window is never flagged. The hint on the Silent tile mentions three times the usual interval, which does not match this rule.
Can I compare more than 5 brands at once?
No. The picker stops accepting brands at 5 and the compare button stays disabled below 2. Save several watchlists of up to 5 brands instead and reapply them in one click. Watchlists are stored in your browser only, so they do not follow you to another device or sync to your team.
Why is the Overlap card empty even though the brands clearly share themes?
Overlap shows only what sits in every selected brand's own top list, and those lists are short. Each brand contributes its top 5 subject keywords, its top 5 product categories and its top 8 CTA phrases. A theme that ranks sixth for one brand drops out for all of them. Comparing fewer brands, or widening the tracked period so the top lists settle, usually brings the shared rows back.