Telecom
How the telecom industry works, and the finance, marketing, data and AI that run it.
The programs
Five programs, one per domain of the Telecom sector. Every one is readable straight away, without an account, and you can gauge your level on any of them whenever you want.
Telecom
Telecom is a capital-intensive, network-driven sector where infrastructure economics, spectrum policy, and regulation shape competitive outcomes as much as consumer demand.
18 lessons · about 4h
- Map the telecom value chain from network infrastructure to end-user services and identify where margin concentrates
- Analyze competitive dynamics between incumbents, challengers, MVNOs, and equipment suppliers in a given market
- Identify which regulations and regulatory bodies govern a telecom decision (spectrum, pricing, interconnection, privacy) and what compliance they require
Finance for Telecom
This block builds financial fluency specific to the telecom sector, where capital intensity, long-lived network assets, and subscription revenue models shape every decision.
31 lessons · about 6h
- Map the telecom value chain from network infrastructure to end-user services and identify where margin concentrates
- Analyze competitive dynamics between incumbents, challengers, MVNOs, and equipment suppliers in a given market
- Identify which regulations and regulatory bodies govern a telecom decision (spectrum, pricing, interconnection, privacy) and what compliance they require
Marketing for Telecom
Telecom marketing operates in a saturated, contract-driven market where customer acquisition is expensive and switching costs shape retention strategy.
31 lessons · about 6h
- Map the telecom value chain from network infrastructure to end-user services and identify where margin concentrates
- Analyze competitive dynamics between incumbents, challengers, MVNOs, and equipment suppliers in a given market
- Identify which regulations and regulatory bodies govern a telecom decision (spectrum, pricing, interconnection, privacy) and what compliance they require
Data for Telecom
Telecom generates some of the densest, most continuous data in any industry: network signaling, CDRs, geolocation, device telemetry, and billing events at massive scale.
31 lessons · about 6h
- Map the telecom value chain from network infrastructure to end-user services and identify where margin concentrates
- Analyze competitive dynamics between incumbents, challengers, MVNOs, and equipment suppliers in a given market
- Identify which regulations and regulatory bodies govern a telecom decision (spectrum, pricing, interconnection, privacy) and what compliance they require
AI for Telecom
AI is now embedded across telecom operations, from network management to customer experience.
31 lessons · about 6h
- Map the telecom value chain from network infrastructure to end-user services and identify where margin concentrates
- Analyze competitive dynamics between incumbents, challengers, MVNOs, and equipment suppliers in a given market
- Identify which regulations and regulatory bodies govern a telecom decision (spectrum, pricing, interconnection, privacy) and what compliance they require
Telecom builds and runs the networks everything else depends on: enormous fixed costs, heavy regulation, and a constant fight against commoditization. This vertical gives you the big picture, then finance, marketing, data and AI applied inside it.
Key terms
Why specialize in Telecom?
Cross-cutting skills are not enough in the Telecom sector. It plays by its own rules: a distinct value chain, specific players and balance of power, dense regulation, and key figures you won't find anywhere else. This vertical gives you that sector fluency: first the big picture, then finance, marketing, data and AI applied concretely to Telecom, with the calculations, benchmarks and checklists you actually need on the ground.
What you'll be able to do
- Understand how the Telecom sector works: value chain, key players and balance of power
- Know the major regulations and laws, the sector's acronyms and vocabulary
- Run the key calculations and read the benchmarks specific to Telecom (US and Europe markets)
- Apply finance, marketing, data and AI to the realities of Telecom
- Gauge your level with 5 sector assessments and a competency radar
70 lessons across 16 modules and 5 blocks, with a test per lens and a sector competency radar. Free to read, no account required.
The curriculum in detail
Telecom: how the sector works
Generalhow telecom works: building and running networks, the enormous fixed-cost model, spectrum and regulation, and the fight against becoming a dumb pipe.
4 Modules · 18 Lessons
Finance in telecom
Financetelecom finance: ARPU and churn, massive capex and spectrum costs, infrastructure sharing, and the cash-flow profile of a network business.
3 Modules · 13 Lessons
Marketing in telecom
Marketingtelecom marketing: acquisition and churn in a saturated market, bundling and pricing, network as brand, and retention economics.
3 Modules · 13 Lessons
Data in telecom
Datatelecom data: network and usage data, customer analytics and churn prediction, and privacy/regulatory constraints on rich data.
3 Modules · 13 Lessons
AI in telecom
AIAI in telecom: network optimization and predictive maintenance, churn and personalization, service automation, and capacity planning.
3 Modules · 13 Lessons
Prefer to place yourself first?
Five short assessments, one per domain of the Telecom sector. Ten questions each, three minutes, and a competency radar once you have taken more than one.
All sector assessmentsLatest articles
What the blog publishes on Telecom, across every discipline.
- DataHow did Telefónica build a churn model that actually moved retention numbers?Telefónica's data teams spent years accumulating subscriber signals before their churn models started producing revenue-grade predictions. The mechanics of what they built, and where other telcos consistently fall short, carry direct lessons for any CDO running a retention program in 2026.
- Finance$800mn at an $8bn floor: what Airtel Money's London IPO demands from an African fintech CFOAirtel Money is preparing to file prospectus documents for what could be one of London's largest listings in recent years, targeting $800mn in proceeds at a valuation of $8bn to $9bn. The preparation required to reach that point tells CFOs more about IPO readiness than any generic checklist.
- MarketingChurn economics and retention ROI: what the numbers actually say for postpaid CMOsReducing postpaid churn by even half a percentage point can be worth more to a telecom operator than winning thousands of new subscribers, once you account for acquisition cost and margin dilution. This article breaks down the mechanics of churn economics so you can make the case for retention investment with the precision your CFO expects.
- DataClean rooms in practice: a CDO playbook for data collaboration that actually worksData clean rooms offer a principled path to collaborative analytics without exposing raw customer data, but most implementations stall on governance gaps and misaligned incentives. This playbook gives CDOs a concrete sequence to stand up a clean room partnership, avoid the common failures, and extract value quickly.
- MarketingRetention as a growth lever: the mechanics CMOs need to masterMost growth models are built around acquisition, yet the economics of retention consistently outperform it. This article breaks down exactly how lifecycle marketing works as a primary growth driver, and where CMOs tend to get it wrong.
Frequently asked questions
What does the Telecom vertical cover?
It covers how the telecom industry works, then finance, marketing, data and AI applied inside it. Five blocks in total: a general one on building and running networks, spectrum and regulation, plus one block per discipline. The thread running through all of them is the same: enormous fixed costs, heavy regulation, and the constant fight against commoditization.
Who is this useful for if I don't work for an operator?
Anyone selling to, partnering with or investing in telecom operators. Understanding why capex and spectrum dominate an operator's decisions, and why churn matters more than acquisition in a saturated market, changes how you read their priorities. Equipment vendors, software providers and analysts all deal with the same economics.
Where should I start if I'm new to the sector?
Start with the general block on how telecom works: networks, the fixed-cost model, spectrum and regulation. The finance, marketing, data and AI blocks all assume you know why a network business behaves differently from a normal company. Once that's clear, take the blocks in whatever order matches your job.
What does "dumb pipe" mean and why do operators fear it?
A dumb pipe is an operator reduced to selling raw connectivity while the value, and the customer relationship, sits with the services running on top. It matters because connectivity gets cheaper every year while the network still has to be paid for, so margins compress. The general Telecom block covers how operators fight this through bundling, services and content.
What's the difference between ARPU and churn as performance measures?
ARPU measures how much revenue each customer generates; churn measures how many customers you lose. Together they set the value of the base: a rising ARPU means little if churn is eating the subscribers behind it. Both are treated in the Finance in telecom block, alongside retention economics in the marketing block.
Why does telecom marketing focus so much on retention rather than acquisition?
Because most telecom markets are saturated: nearly everyone already has a line, so growth comes from taking customers from competitors or keeping your own. Acquisition in that context is expensive and often just swaps subscribers between operators. The Marketing in telecom block covers acquisition and churn in a saturated market, bundling, pricing and retention economics.
Operators hold very rich data. What limits what they can do with it?
Privacy rules and sector regulation. Network and usage data reveals location, behaviour and contacts, which puts it under strict constraints on collection, retention and reuse, well beyond what most industries face. The Data in telecom block covers network and usage data, customer analytics and churn prediction, and exactly these regulatory limits.
What are the concrete AI use cases in a network business?
Four, covered in the AI in telecom block: network optimization, predictive maintenance on equipment, churn prediction and personalization, and service automation, plus capacity planning. The common point is that they all exploit continuous streams of network and customer data an operator already generates. That is what makes telecom one of the sectors where AI has a direct effect on cost per gigabyte and on the subscriber base.