SubscribersHow many subscribers the channel has now. The wave shows subscribers at each point of the period. The change is against the start of the period.60.0 %+0 for the period
ViewsHow many views the posts published in the period have now. These are not views per day: MAX does not report how many views there were yesterday. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.7▼ 56.9 %was 17
ReactionsHow many reactions the posts published in the period have. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.2▼ 30.2 %was 3
MentionsHow many times other channels mentioned the channel: links and reposts, excluding advertising posts. The bigger the circle, the more mentions at that point of the period. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.61▼ 18.9 %was 76with a subscription
RepostsHow many times other channels reposted this channel's posts (excluding advertising posts). Reposts are also counted as mentions. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.28▲ 13.2 %was 25after signing in
Average post reachHow many views one post gets on average. Only posts older than two days are counted: views of fresh posts are still growing. Points with fresh posts are dashed with hollow dots: the reach of all posts right now, it will still grow.5 497▲ 4.2 %was 5 274after signing in
ERRWhat share of subscribers sees an average post: average reach ÷ subscribers × 100 %. The line shows ERR at each point of the period, the dashed line — ERR of the previous period of the same length. Points with posts younger than two days are hollow dots on the dashed end of the line.28.6 %▲ 0.7 ppdashed line — was 27.9 %after signing in
Engagement ERHow often readers react to posts: reactions ÷ views × 100 %. The tick on the bar is the previous period.2.87 %▼ 0.2 pp
Posts per dayHow many posts are published per day on average. Each cell is a point of the period: the darker, the more posts per day. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.4.1▼ 14.9 %was 4.9after signing in
Ad shareWhat share of the period's posts looks like advertising: erid labeling, ad links and other signs. The scale shows the ad load by the quality index thresholds: up to 10 % — low, up to 25 % — moderate, up to 50 % — high, above — very high. A growing share is marked red.2.4 %▼ 2.4 pp
TrendTop — subscribers at the end of each point of the period; bottom — growth per point: green means more subscribers, red means fewer. Above the growth chart — the biggest gain and the biggest loss. MAX does not report how many people subscribed and unsubscribed separately.
Audience growth
0subscribers in the period
The number of subscribers did not change in the period
Channel scoreA channel score from 0 to 100 made of five parts: audience, growth integrity, ad load, trust and calculation reliability. Each bar shows how many points the part earned out of its maximum. The index is recalculated every night; channels are compared with similar ones of the same category and size.
ReachHow many views the posts published at each point of the period have now (not views per day). The record is labeled; the point with today is paler — the day is not over yet. Average post reach — posts older than two days.
Views and reach
678 845views in the period▼ 10.9 %
Average post reach — 5 497 views (posts older than two days).
EngagementER — reactions divided by views, in percent — for the posts of each point of the period. The dashed line is ER for the whole period. The change is in percentage points against the previous period of the same length.
CitationsThe citation index (CI) shows how often and by which channels this channel is mentioned over the last 30 days, excluding advertising posts. The level is its place among similar channels. The line shows CI at each point of the period (for a week or month — the average over its days).
RhythmHow many posts are published on average in each hour of each weekday, Moscow time: the darker the cell, the more posts. “Best time” — the hours when posts older than two days have the highest average reach.
When and how much it posts
MonTueWedThuFriSatSun
036912151821
Best time:09:0018:00hours when posts get the highest average reach
FormatsWhat the feed is made of. Each post has one format, by priority: repost, video, photo, link, text. The bar and percentages show the share of posts of each format; on the right — average reach of one post of the format (posts older than two days), the small bar compares it with the most viewed format.
Post formats
100 posts
Reposts99 %6 168
Video2121 %7 513
Photos3838 %5 699
Links1212 %5 239
Text2020 %7 626
On the right — average reach of one post of the format.
PostsEach dot is a post in the period: horizontally — publication date, vertically — views, dot size — reactions, color — format. This shows hits, flops and how reach changes. For large channels, the 100 most viewed posts and an even sample of the rest are shown — no more than 1,500 dots.
Every post is a dot
Higher means more views, bigger means more reactions. Click a dot to open the post.
VideoPhotosOthersize — reactionsZoom with the + and − buttons, a pinch or Ctrl + mouse wheel; drag a zoomed chart to move it
SummaryTotals for the selected period: how many posts were published, how many views and reactions they have now and the average post reach. Views are the current views of posts published on those days, not views per day. The change is against the same span before the period, if statistics cover it.
Period totals
Click a metric to see it across the period below
Viewstoday — the day is not over yetPoints with posts younger than two days are pale and dashed: their views are still growing.
AdsWhat share of the period's posts looks like advertising: erid labeling, ad links and other signs. The detector is cautious, so the real share is usually higher. The scale shows the ad load by the quality index thresholds. Below — the average reach of an ad post and a regular post, and who the channel advertises (sites that ad links lead to).
What worksPosts of the period with the most views. The bar shows views relative to first place. The preview is the post's image; for a post without an image — the channel avatar. Views are the post's current count.
RhythmHow many posts were published each day of the period (pale bars) and the 7-day average (line): you can see whether the channel is speeding up or slowing down. Today is not over yet, so its average is calculated up to yesterday.
Posts by day
Pale bars are days, the line is the 7-day average: you can see whether the channel is speeding up or slowing down
Posts per day7-day average
Data updated at 16:26 Moscow time. Views are the current counts of posts published on those days; average reach counts posts older than two days.
How the quality index is calculated
«Кейс: как мы перераспределили трафик между кампаниями и снизили CPA на 23%» Это анонимный кейс без чувствительных данных — зато с рабочими шагами, которые можно применить в любом проекте. Проблема. В одном из проектов CPA стабильно рос 3 недели подряд, несмотря на сохранение ставок и бюджетов. Кампании были разделены по гео и устройствам, но общий CPA уже выходил за KPI. При этом отдельные кампании показывали разную эффективность, а ручной контроль не успевал за динамикой. Гипотезы. Часть площадок и устройств «тянут» CPA вверх из‑за низкой конверсионности. Бюджет распределяется неоптимально: эффективные кампании упираются в лимит, а неэффективные продолжают тратить деньги. Ставки не учитывают время суток: ночью конверсии ниже, а цена клика остаётся прежней. Шаги. Собрали данные за 21 день по кампаниям: CPA, CR, CPC, количество конверсий, разбивка по устройствам и площадкам. Выделили «лидеров» и «аутсайдеров»: кампании с CPA ниже целевого на 15–30% и те, где CPA превышал цель более чем на 30%. Перераспределили бюджет в пользу эффективных кампаний: +30% бюджета на топ‑кампании, −40% на аутсайдеры. Отключили низкоконверсионные площадки (отдельные сайты в РСЯ) и снизили ставки на мобильные устройства в ночное время (23:00–06:00). Настроили авто-правило в интерфейсе Директа: если CPA > целевого более чем на 25% в течение 3 дней — снижать ставку на 10% и ставить алерт. Результат. За 14 дней CPA снизился на 23%, при этом количество конверсий выросло на 8% за счёт перераспределения трафика на более эффективные кампании и площадки. Бюджет остался прежним. 3 рекомендации, которые работают в любом проекте: Разделяй кампании по ключевым сегментам (гео, устройства, тип аудитории) — так проще точечно перераспределять бюджет и отключать неэффективное. Не держи «слабые» площадки и сегменты «на всякий случай»: если сегмент стабильно даёт CPA выше цели на 30%+, лучше отключить его или сильно снизить ставки. Автоматизируй базовые правила (снижение ставок при росте CPA, алерт при остановке/отклонении объявлений) — это экономит время и снижает человеческий фактор.
«Автоматизация рутины в рекламе: какие задачи можно делегировать и чем» Если у тебя 5+ проектов и в каждом по 3–4 рекламных кампании, рутина быстро съедает время, которое лучше потратить на стратегию и новые проекты. Ниже — 4 типовые задачи, которые реально автоматизировать, плюс инструменты и сколько времени это экономит. Сбор минус‑слов из поисковых запросов с низким CTR и конверсией. Вместо ручной выгрузки и разбора отчётов можно использовать выгрузку из Яндекс Метрики, а дальше — простой скрипт на Python либо формулы в Excel/Google Sheets, чтобы отфильтровать нерелевантные запросы. Это экономит до 3–4 часов в неделю на один проект, а на пяти проектах — уже 15–20 часов. То есть почти полноценную рабочую смену. Проверка статусов объявлений: остановлены, отклонены, на модерации. Ручной мониторинг легко заменить: через API Яндекс Директа или готовые интеграции в no‑code конструкторах можно настроить автоматические проверки и алерты в Telegram или на почту. Вместо 30–60 минут ежедневного мониторинга остаётся 5–10 минут на проверку уведомлений — остальное делает система. Регулярная выгрузка отчётов по кампаниям. Показы, клики, CPA, конверсии — всё это не обязательно собирать вручную. В Яндекс Метрике есть планировщик отчётов с автоматической отправкой на почту или в Google Sheets. Либо можно подключить коннектор к BI‑инструменту. Так экономится 1–2 часа в неделю на формирование сводной таблицы — и эта работа уходит полностью. Проведение A/B‑тестов объявлений. Когда параллельно крутятся разные заголовки и тексты, ручной анализ и переключение вариантов съедают время. Здесь выручают встроенные сплит‑тесты в Яндекс Директе плюс авто‑правила или скрипты, которые отключают варианты с худшими метриками. Это даёт экономию до 2–3 часов в неделю на проект — и снижает риск субъективных решений. Что в итоге. Даже частичная автоматизация этих четырёх задач даёт больше 20 часов свободного времени в неделю. Это не про «меньше работать», а про то, чтобы тратить освободившиеся часы на масштабирование, новые проекты и рост KPI. Если скажешь, какой стек тебе ближе (Excel, скрипты, no‑code, готовые сервисы), подскажу конкретный план внедрения под твои текущие проекты — с приоритетами и первыми шагами.
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