Subscriber 360 for a Telecom Operator
Typical problem: 6–8% monthly churn, marketing firing blind, support doesn't know the customer. Cause — subscriber data scattered across 5–7 systems and nobody sees the full picture. Solution — an integration layer, not a new system.
A typical telecom operator situation: 6–8% monthly churn, marketing bombarding everyone with the same SMS campaigns, support doesn’t know who’s calling or why. Data exists — in billing, CRM, network systems, contact logs. But it lives in different worlds.
Why does this happen? The marketer works with one extract, support with another, finance with a third. The same subscriber may be recorded differently across systems. Each department sees its piece of the picture, but nobody sees the whole. Without a complete profile you can’t predict who will leave, can’t offer the right tariff, can’t understand why a subscriber called five times and was still unhappy.
The right approach is not to implement a new system, but to connect existing ones. Build a unified warehouse, cleanse and deduplicate data, create a subscriber profile from 80+ attributes. Based on it — a churn prediction model and automated retention campaigns. This isn’t replacing CRM or billing — it’s an integration layer on top of them.
The critical phase that many underestimate is data quality. Without cleansing and deduplication all analytics is useless. Up to 6 weeks go into this, but it’s the investment that determines the success of the entire project.
What to expect: churn halves, ARPU grows 15% through personalized offers, marketing transitions for the first time from carpet-bombing to segmented campaigns. Support sees the complete profile in 3 seconds — every call becomes a retention opportunity, not an annoying repeat.
Typical Problem
The mobile operator is losing subscribers at a rate of 6–8% monthly. Marketing launches mass campaigns blindly — the same offers to everyone. Support doesn't see the contact history. A subscriber calls five times about the same problem, and on the sixth call leaves for a competitor. If this sounds like your situation — the problem is probably not in the people or the tariffs.
Why This Happens
In a typical telecom operator, subscriber data is scattered across 5–7 systems: billing, CRM, network, contacts, sales, loyalty. None provides a complete picture. The marketer doesn't know how many times the subscriber called support. Support doesn't know the tariff plan. The analyst can't connect churn to network quality. Each department sees its piece of the subscriber, but nobody sees the whole.
How We Diagnose It
In diagnostics we don't check individual systems — they usually work fine. We look for gaps between them. The key question: can anyone in the company see the complete picture of one subscriber — from tariff and consumption to contacts and network quality? If not — the problem is the absence of an integration layer and a unified data model. Without a complete picture, neither predicting churn nor personalizing retention is possible.
The Right Model
Three-layer model: (1) integration layer — collecting data from all systems into a unified warehouse with cleansing and deduplication; (2) analytics layer — unified subscriber profile, segmentation, predictive churn scoring; (3) operational layer — dashboards for marketing and support, automatic retention triggers. No new systems — connecting existing ones.
How We Implement It
A typical project takes 4–5 months. We build ETL from all sources, create a unified subscriber profile with 80+ attributes, develop a churn prediction model, integrate with CRM for automated retention campaigns, create a Subscriber 360 dashboard for support. The critical phase is data cleansing and deduplication: up to 6 weeks, but without it all analytics is useless.
How the Team Works
Projects like this run with a team of 6: 2 data engineers, 1 data analyst, 1 backend developer, 1 frontend developer, 1 tester. I define the warehouse architecture, data model, and integration strategy. The team implements ETL, interfaces, tests, and documents.
Results
If your operator is losing subscribers and marketing is firing blind — the problem isn't in the CRM or billing. The problem is that there's no connection between them. Connect your existing systems, show each department the full subscriber picture — and churn will halve without a single new system.
Key Lessons
- • Data quality is the foundation. Don't start analytics without deduplication — results will be meaningless.
- • A predictive model doesn't need to be perfect — 78% accuracy is already radically better than working blind. Don't wait for perfection, launch.
- • Support is a non-obvious but powerful retention channel. When the agent sees the full profile, every call becomes an opportunity.
- • Integrating multiple systems is not a technical project but an organizational one: you need to align data models across departments.
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