How AI forms personalized mailings on Telegram

Telegram is one of the fastest channels for denouncing meaning: push notifications, buttons, polls, mini-applications, reactive bots. With AI, the newsletter ceases to be "one for all" and turns into a personal guide: to whom what, when and how to show to help, and not to spam.

1) What is considered "personalization" in Telegram

Personalization layers:

1. Segment (s): Language, Region/Prime Time, Experience Level (Beginner/Researcher/Creator), Interests (Genres/Themes).

2. Content (what): selection of topics, depth of explanations, format (card/carousel/video/guide).

3. Moment (when): the optimal send-time according to the user's habits.

4. Interaction channel (how): message to the channel, personal message from the bot, inline buttons, mini-app, polling.

5. Tone (in what voice): short/detailed, friendly/business, neutral/emotional.

2) What data is needed (and how to take it ethically)

Explicit: language, time zone/region, selected topics, frequency of notifications (often/normal/rare).

Behavioral: clicks on buttons, viewing/hiding, participation in surveys, favorite formats.

Content: what topics are read/saved, the "tail" of engagement (day 1/3/7).

Contextual: device (mob/desktop), prime time activity, transitions from other channels.

Principles: voluntary consent, minimum data, understandable settings "pause/unsubscribe/less often," storage of aggregates instead of "raw" logs, transparent policy.

3) AI distribution architecture (skeleton)

1. Signal collection: bot/microservices → events (subscription, clicks, polls).

2. User Profile: Interests, Language, Prime Time, Experience Level, Recent Activities.

3. Content Lake: Guides, previews, video, FAQ, promo base, changelog, UGC.

4. Model layer:

RAG/knowledgebase search (to insert texture, not "water"), recommendation model (user × item), key/intent (for correct CTA), send-time optimization (time series), deduplication/anti-spam (rules + anomalies).
5. Campaign orchestrator: scripts, A/B, frequency limits, mass/trigger separation.
6. Delivery: channel/bot/RM, buttons, polls, deep-links/mini-apps.
7. Measurement: ER, CTR, retention, unsubscribe, "follow-up" (poll/event/hyde), contribution to goals.

4) What models and why

Recommendation (CF/gradient boosting): "similar to you read" + personal topics of the week.

Intent/theme classification: to collect a card "for you": guide vs announcement vs reminder.

Tonality/emotion: soft language under sensitive themes, neat CTAs.

Send-time optimization: Prophet/gradient boosting by time series → individual sending windows.

Reright module: adaptation of length/tone (≤ 300 characters per character, ≤ 900 per channel, TL; DR variant).

Anti-spam/frequency manager: limits per week/day, campaign conflict rules, "do not touch at night."

5) Distribution scenarios (mass and trigger)

Mass (with personal layers):

"Plan of the week" in your topic + local time of events.
Digest UGC/guides, but only for selected interests.
"What's new": releases/fixes → in the right depth (short/expanded).

Trigger (1-to-1):

"Welcome": 3 personal first steps + two guide buttons.
"You missed X": soft resume + less-often/pause button.
"Similar content is out": similar theme/format.
"Survey on a topic you are interested in": 3 questions, answer - TL; DR with solved items.
"Feedback after the event/guide": 2 clicks, then personal recommendations.

6) Message format: what a smart card consists of

Header ≤ 60-70 characters (without clickbait; one sense trigger).

TL; DR in 1-2 sentences.

1-3 bullet "what you get."

Buttons: "Read," "Save," "Participate," "Frequency settings."

Optional: mini-survey (1 question), reaction (/), disclaimer (if sensitive topic).

Fall-back: short text without a medium if the communication channel is bad.

Template (copy):

💡 [Topic of the week]: short analysis
TL; DR: [in 1-2 sentences, no water].
[Item 1] [Item 2] [Item 3]
[Button: Read] [Save] [Adjust Frequency]

7) A/B/multivariable tests: discipline of experiments

No more than 2-3 hypotheses at a time (header, format, time slot).

Define the target metric (CTR/inspection/survey response).

Duration/size: At least one full prime time cycle.

Post-mortem: what we transfer to constancy, what to the "archive of ideas."

8) Metrics: What to watch daily/weekly

Daily:

Deliverability, CTR, button press, segment silence.
Unsubscribes/memos/complaints, bot errors, delays.
Reactions to surveys/mini-forms; response time.

Weekly:

Retention readers, the proportion returning to rituals.
Share of "follow-up": transition to guide/event/survey.
Send-time: uplift effect to baseline.
Personalization quality: increase in CTR vs "universal" version, decrease in unsubscriptions.

9) 90-day road map

Days 1-30 - Foundation

Privacy/frequency policy, "notification settings" screen (often/norm/rarely/pause).

Collection of explicit preferences (language, themes, format), basic segments.

Connecting a content lake (guides, announcements, UGC), RAG search.

Basic campaigns: "Welcome," "Plan of the Week," "Digest."

Days 31-60 - Personalization

User × item on clicks/saves.

Send-time per user (2-3 windows) and frequency limits.

Personal "Plan of the Week "/digest + 1-2 triggers ("You missed, "" Survey ").

Start of A/B headers/formats; dashboard metrics.

Days 61-90 - Scale and Robustness

Multi-layer personalization (interest × experience level × language).

Mini-template catalogs: short/expanded, friendly/business.

Anti-spam contour: conflict campaigns, do not push at night, gray areas.

Quarterly report: uplift CTR/retention, unsubscribing, "follow-up."

10) Launch checklists

Ethics and experience

There is a frequency and pause screen.
Explicit consent and simple unsubscribe.
Data minimization; we store units.
Transparent "how to use AI" disclaimer.

Technique and content

RAG is connected to the guide/FAQ/changelog database.
Short/long card and promo block templates.
CTA/Button Directory (Read/Save/Participate/Customize).
Anti-duplicates: one user - maximum N messages/week
Bot error logs and undeliverable report.

Analytics

Dashboard: deliverability, CTR, retention, unsubscribe, "follow-up."
Campaign and UTM tags for end-to-end attribution.
Post-mortem repository by test.

11) Ready-made promptas (for editor/bot)

a) Personal digest (short):

💡 "Collect 1-2 topics from the [X, Y] categories, taking into account the [ru] language and [beginner] level. Dai TL; DR ≤ 200 characters and 3 bullets of benefit. Add 2 buttons: Read, Adjust frequency"

b) Reright under the person:

💡 "Reduce this text to 280-300 characters, keep the meaning and one CTA, remove unnecessary introductory."

c) Send-time tip:

💡 "By user click history, offer 2 send windows on weekdays and 1 on weekends. Display in UTC + X with justification (reaction history)"

d) Reverse survey:

💡 "Create a mini-survey of 3 questions on the topic [], then generate a short summary of the results and one specific edit that we promise to make by [date]."

12) Frequent mistakes and how to avoid them

Spam instead of benefit. Solution: frequency limits, "pause," personal windows.

The same tone to everyone. Solution: mini-templates by styles and length, auto-rerite.

Campaign doubles. Solution: Conflict orchestrator (priorities/cooldowns).

There is no "follow-up." Solution: each mailing list has an understandable CTA and a measurable next-step.

Polls unchanged. Solution: Post TL; DR results and "what changed."

13) Responsible Personalization (RG/Compliance)

Do not push for risky behavior; CTA - "read/learn/set limits," not "play now."

Easy access to self-control tools: limits, timeout, self-exclusion.

Clear rules for promotions and appeals; no "hidden" condition in the personal.

Localization: language, cultural context, data laws in the region.

AI turns Telegram mailings into personal service messages that come at the right time, in the right language and with clear benefits. The architecture is simple: signals → profile → selection of content → the correct window for sending → measuring the result. Add ethics, transparent settings and test discipline - and the newsletter will be a channel of trust, not irritation.