Vijan.AI
Case StudiesTelecom & MediaCampaign Personalization

Telecom & Media

Content & Campaign Personalization

4 autonomous agents personalize content and campaigns for each subscriber. 4x engagement improvement.

4 Autonomous Agents4x Engagement
Get in touch

Agentic AI Workflow

4 autonomous agents segment, target, and convert subscribers with personalized campaigns

The Challenge

Generic promotional blasts were training subscribers to ignore marketing messages

A telecom operator sending 120M promotional messages monthly had engagement rates of 2.1% — below the 4% industry average. Subscribers received identical offers regardless of their usage patterns, preferences, or lifecycle stage.

The marketing team spent 80% of their time on manual segmentation and content selection. Campaign results took 2 weeks to analyze, preventing real-time optimization. Opt-out rates had increased 25% year-over-year as subscribers grew frustrated with irrelevant messages.

The operator needed hyper-personalized campaigns that delivered the right content to the right subscriber at the right time.

The Solution

Agents that segment audiences, match content, optimize delivery, and track performance

Vijan.AI deployed 4 agents. The Audience Builder segments subscribers using 40+ behavioral and demographic attributes, creating micro-segments of 1 (individual personalization). The Content Matcher recommends offers, plans, add-ons, and content from the catalog based on each subscriber's profile and predicted next-best-action. The Delivery Optimizer selects optimal timing, channel (SMS, push, in-app, email), and frequency per subscriber. The Performance Tracker measures engagement in real-time and adjusts campaign strategy through continuous feedback loops.

Autonomous Agents

How each agent reasons, decides, and acts

Step 1 · Segmentation

Subscriber Segmentation Agent

Behavioral Segmentation & Audience Building

Segments subscribers and prospects by usage, demographics, and predicted LTV, autonomously identifying high-value audiences for targeted marketing and retention campaigns.

Input

Usage data, demographics, purchase history, predictive models

Output

Segment definitions, audience lists, LTV scores, campaign targets

  • Calls analytics database to aggregate behavior, tenure, and ARPU by cohort
  • Calls segmentation rules engine to classify subscribers into acquisition, growth, and retention tiers
  • Autonomous decision: target high-LTV, suppress low-engagement, or test new segments
  • Routes audience lists to Campaign Manager and Acquisition agents

Step 2 · Campaign

Launch Campaign Agent

Multi-Channel Campaign Orchestration

Designs and launches email, SMS, and digital ad campaigns with personalized offers, autonomously A/B testing messaging and optimizing send times for maximum engagement.

Input

Audience segments, creative assets, offer catalogs, channel preferences

Output

Campaign launches, A/B test results, engagement metrics, conversion reports

  • Calls marketing automation platform to schedule and send personalized messages
  • Calls A/B testing engine to split traffic and measure performance by creative variant
  • Autonomous decision: scale winning variants, pause underperformers, or adjust send times
  • Routes conversion data to Acquisition and Bundle agents for offer optimization

Step 3 · Acquisition

Subscriber Acquisition Agent

Lead Qualification & Subscriber Activation

Qualifies inbound leads using credit checks and coverage validation, autonomously approving activations, provisioning devices, and onboarding new subscribers.

Input

Inbound leads, credit scores, coverage maps, device inventory

Output

Activation approvals, SIM provisions, device shipments, onboarding workflows

  • Calls lead database to retrieve contact info and campaign source
  • Calls credit check API to score applicants and set deposit/plan eligibility
  • Autonomous decision: approve activation, require deposit, or decline due to credit/coverage
  • Routes approved activations to Bundle Optimizer for plan recommendations

Step 4 · Bundle

Bundle Optimizer

Personalized Plan & Add-On Recommendations

Recommends optimal bundles and add-ons based on predicted usage and campaign context, autonomously configuring plans to maximize ARPU and minimize churn risk.

Input

Campaign context, predicted usage, pricing catalogs, competitor offers

Output

Plan recommendations, bundle configurations, upsell offers, ARPU forecasts

  • Calls pricing engine to model plan costs and bundle savings by usage profile
  • Calls offer database to match campaign promotions with plan eligibility
  • Autonomous decision: recommend base plan, upsell premium bundle, or add device financing
  • Routes plan assignments back to Acquisition agent for final activation

Results

Measurable impact within 90 days of deployment

4x

Engagement Rate

Campaign engagement improved from 2.1% to 8.4% through individual-level personalization.

$18M

Incremental ARPU

Annual incremental revenue from higher plan upgrades, add-on adoption, and reduced promotional waste.

60%

Lower Opt-Out

Opt-out rates decreased 60% as subscribers receive only relevant offers at appropriate frequency.

Real-time

Campaign Optimization

Campaign performance visible in real-time. Underperforming variants replaced within hours, not weeks.

Implementation

From pilot to production in 12 weeks

Week 1-4

Agent Design & Tool Integration

Defined agent capabilities, connected ML model, rules engine, graph DB, and chargeback API tools. Configured orchestrator routing logic.

Week 5-8

Shadow Mode & Autonomous Tuning

Agents ran in shadow mode on 10% of transactions. Tuned decision thresholds, tool call parameters, and feedback loop retraining frequency.

Week 9-12

Full Autonomous Deployment

Production rollout across all channels. Agents operating fully autonomously with human-in-the-loop for critical escalations only.

Ready to deploy autonomous agents for your use case?

Let's design an agentic AI solution tailored to your organization's workflows.