Individual tasks for the player's profile

Personal tasks increase response and retention because they take into account the player's preferences, time, risk profile and goals. Important: personalization does not change RTP and RNG, does not push up rates and works within voluntary limits. Below is a practical diagram from data and rules to UX, RG and metrics.

1) Personalization goals

Relevance: the task is the same as your favorite providers/session times/formats.

Safety: RG compliance, soft mouthguards and "breaks" are sewn into the logic.

Fairness: The chances of success are independent of the size of the bet.

Economic manageability: predictable RewardRate, no "overfeeding."

Transparency: simple rules and understandable progress.

2) Profile data and features (minimum sufficient)

Gaming habits: favorite providers/slots, average length and frequency of sessions, typical prime time.

Bet profile: bet distribution (quantile), average multiplier of winnings.

Content diversity: How many unique providers/week.

Reaction to tasks: completion, time to start, fail patterns.

RG signals: active limits, self-regulation, breaks.

Technical signals: device, network (for timings), local/time zone.

💡 Privacy: use pseudonymous IDs, store aggregates (quantiles/flags), exclude PII from scoring.

3) Segmentation and targeting

By prime time: Morning/Day/Evening/Night → give out windows for the usual slot.

By content: "Collector" (loves new providers) vs "Main-slotter" (plays 1-2 games) → different tasks for variety.

According to the risk profile: L/M/H-bet quantiles (not to be confused with "luck") → the same chances of success in any bets.

By engagement: Onboarding → Activation → Habit → Return (winback).

By Social Game: Soloist/Team - Add Team Goals (Sum Top-M).

4) Personal task designer

Field Template:

Goal: a specific trigger (for example, "achieve a factor of ≥ x12 twice in 2 providers").
Window: recommended time (under prime time) + "grace 1-3 min."
Scoring: formula without pay-to-win (see below).
Limits: N best attempts/window, cap per spin/day, exceptions for bonus funds.
Reward: cosmetics/frame/XP/freespins fix. nominal value (controlled variance), claim terms.
RG Guardrails: points only within active limits; break reminders.
Explain: 1-2 lines on the card - what to do and how it is considered.

5) Fair formulas and limits

Base (recommended):

'Score = round (100 log2 (Win/Bet + 1)) '- rewards relative luck rather than bet size.

Anti-grind:

Offset of the N best events for the window/day (sprint: N = 10-15; day/hour: N = 20).
Sprints: total = median of the best three 5-minutes (resistant to the "miracle back").
Variety: '+ B' points for the first 'M' unique providers/day (for example, 'B = 50', 'M = 3').
Bonus funds: coefficient'coef _ bonus ∈ [0; 0. 5] 'or' 0' for public finals.
Tie-breaks: 1) earlier reached, 2) greater variety, 3) deterministic seed.

6) Economics and P&L

RewardRate (Target Corridor): 0. 2–0. 8% of the GGR cohort involved.

Prize structure 60/30/10:

60% - cosmetics/statuses/frames/banners, 30% - freespins fix. face value or bonus loans (vager x20-x35), 10% - access (early releases/private events).
Payout width: 30-50% successfully completed.
Anti-cannibalization: Frispins on dispersion-driven slots; stretched issuance (checkpoints + final of the week).

7) UX personalization

"For you" card: goal, window, remaining attempts, progress bar, short explanation of the formula.

Recommendations for habits: "Window 19: 00-20: 00 - just your prime time."

Micro-feedback: "+ 40 points for x3," "2 out of 15 attempts left."

Alternative choice: 1-2 "flipping" tasks/week without penalty (anti-frustration).

A11y and localization: large numbers, contrast, subtitles, local time; the server is UTC.

8) RG and ethics by default

Accruals only within voluntary time/deposit/loss limits.

Long session break reminders, soft participation mouthguards/day.

Neutral tone (anti-FOMO), transparent T&C: timing, exceptions, vagers, age/geo.

RG quests as a task: "Set a limit" → an instant cosmetic reward.

9) Anti-fraud and honesty

Event idempotency: 'event _ uuid', journal "seen," retrays are safe.

Anti-bot: challenges in the final minutes of the sprints; "even interval" filter.

Connection graph: common devices/IP/payments → reward hold to KYC (where required).

Caps/quotas: 'Cap _ per _ spin', 'Cap _ per _ day', quota for one slot/provider.

Deadlines: UTC-true and "grace" 1-3 minutes; marking "adjusted" for late events.

10) Real-time architecture and orchestration

Пайплайн: Client → Event Ingest → Scoring → Personal Mission Engine → Progress/Leaderboards (опц.) → Rewards → Comms/CRM

Фоново: Profiles/Features, Eligibility/RG, Anti-Fraud, Snapshotter, Analytics & A/B, Audit.

SLA: progress update ≤ 200-300 ms, claim ≤ 72 hours, uptime ≥ 99. 9%.

Eligibility: tolerance rules (geo/age/RG/license).

Rotation of tasks: no more than 1-2/day per player; "cooling" between similar tasks.

Explainability: decision log (why this particular task is shown).

11) KPI and dashboards

Fairness/Justice

ρ correlation (Score, Bet) by segment ≤ 0. 2; Gini points ≤ 0. 5.

Engagement

Open→Start card rate, Start→Complete, average attempts scored/window, percentage of players with ≥1 event scored/day.

Economy

RewardRate in corridor 0. 2–0. 8%; Claim-rate 72ч ≥ 85%; ARPDAU/ARPPU uplift vs control.

Ops/SLA

p95 log "event → UI" ≤ 300 ms; late-rate ≤ 3%; duplicates ≤ 0. 3%.

RG/Experience

Complaints/10k ≤ 8-10; self-regulation is not impaired vs control.

12) A/B approach and hypotheses

Time windows: personal (prime time) vs fixed.

N best: 10 vs 15 (sprint), 15 vs 20 (hour/day)

Diversity Bonus: B = 0/50/100; M=2/3.

Job rollover: 0 vs 2/week.

Communications: push 15 min before the window vs in-app nuji.

Guardrails: RTP, complaints/10k, RG signals - not worse than control; duration - minimum full cycle (week).

13) Ready-made playbooks

A) Onboarding "3 × 3 personal"

Day 1: mini-mission to your favorite provider (by profile) + RG quest (limit).

Day 2: "explore 2 new providers" (VarietyBonus)

Day 3:20 min sprint in prime time; the result is the median of the best 3 segments.

B) Habit (week arc)

4 light windows of 60 minutes, N = 20/window, 'Score = log2 (Win/Bet + 1)'.

1 "task transfer" without penalty; 60% of the awards are checkpoints, 40% are finals.

C) Winback 30-90 days

Card "you loved X, let's come back softly": window 30 min, N = 10, B = 30 for 2 providers.

Award - Cosmetics/Access; claim ≤ 72 hours.

D) Command version

Personal Score - as above; team - 'TeamScore (day) = Sum (Top 10 Score)'; min contribution ≥5 counted events/day.

14) Rule templates (copy to T&C)

Template 1 - Personal sprint 20 minutes

Очки: `Score = round(100 log2(Win/Bet + 1))`.

Cap tries: 'N = 15'. Bottom line = median of the best three 5-minutes.

Bonus funds: 'coef _ bonus = 0. 3`; `Cap_per_spin=700`.

Tie-break: early achievement → variety → seed.

Template 2 - Day Mission "for you"

Offset: 'N = 20' best events; '+ 50' for the first 'M = 3' unique providers/day.

Claim ≤ 72 hours; points only within active RG limits.

Template 3 - Command Personal Window

Personal account - as in Template 1.

Team: 'TeamScore = Sum (Top 10 Score)'.

Minimum contribution - ≥5 counted attempts/window.

15) Privacy and compliance

Data-minimization: store aggregates and quantiles, not PII.

Explainability: log "why this job is selected."

Storage control: retention periods, anonymization; least rights access.

Jurisdictions: geo-blocks, age, advertising restrictions; Document rule versions.

16) Checklist for launching personal tasks

Rules and economics

'log2 (Win/Bet + 1)', N best, mouthguards per spin/day; VarietyBonus.
RewardRate 0. 2–0. 8%, payout width 30-50%, 60/30/10 structure.

Data and privacy

Aliased profiles, aggregates/quantiles, explain logic.
Retention policy, accesses, auditing.

RG/Anti-fraud

Accruals within limits; Reminders anti-bot/linkage graph; late-window.

Equipment

SLA ≤ 300 ms; Snapshotter; Health/Status API; stop button.

UX/CRM

Card "For you," localization of time, A11y; 1-2 flips/week.
Push 10-15 minutes before the window; post-event highlights.

Data/A/B

Fairness/ops/RG dashboards; design of experiments; guardrails.

17) Typical errors and quick fixes

1. Pay-to-win/grind → add'N best ', log-normalization, caps per spin/day.

2. Personalization "past" → targeting prime time and favorite providers; allow "overrun."

3. Overfeed with prizes → keep RewardRate in the corridor; switch to 60/30/10.

4. Hidden conditions → 1 screen with formula/caps/timers + full T & C.

5. Ignore RG → points within limits, soft reminders, RG quest.

6. Slow feedback → real-time updates ≤ 300 ms; "bronze mode" at G-load.

Individual tasks work when they:

1. relevant to the player's habits (content/time), 2. honest (multiplier + best N, mouthguards, no bet stimulation), 3. economically moderate (RewardRate 0. 2–0. 8%, 60/30/10, wide payments), 4. ethical and safe (RG/anti-fraud/privacy), 5. operational discipline (real-time, SLA, audit), 6. measured via A/B and fairness dashboards.

So personalization becomes a Retention and LTV amplifier - without pressure on the player and without interfering with the basic mathematics of games.