Telecoms

Traditional, correlational, Machine Learning approaches are often not sufficiently trusted or capable enough to address some of the biggest challenges across marketing, customer journey, pricing, network optimisation as well as centralized planning & strategy

Traditional machine learning approaches often fail to address critical business questions

Correlation, not causation

Spurious correlations lead to bad decisions

They struggle to answer why

And are often perceived as “black boxes”

Prediction only, not next best action

For example, they can predict if a customer will churn or not but can’t recommend the optimal next best action to retain the customer

Do these questions sound familiar?

Telecommunications run on causal questions

Marketing Optimization

What are the causal drivers of campaign performance?
How do I attribute customers to the right channels while accounting for confounders in the data?
What are the next best actions (interventions) to improve campaign performance?
What is the incremental impact of increasing spend on a given channel?
What is the optimal investment across channels for a given budget? (e.g.: digital, out-of-home, mail etc)

Pricing & Promotions

What are the causal drivers of conversions?
What actions (interventions) should make in my promotion strategy to optimize for customer LTV?
What impact does competitor pricing have on my customer’s decisions?
What are my products’ price elasticities?

Network Optimization & Maintenance

What are the root causes of outages or inefficiencies?
What actions can I take to prevent future network issues?
Where should I invest to improve network quality?
How should I prioritize customer support enquiries?
To what extent does poor network experience cause customers to complain or churn?

Centralized planning & strategy

What investments will help me achieve my sales and profit targets while improving customer experience?
How will the competitive, market, and macro dynamics impact my PnL?
How will decisions in pricing, marketing or supply chain impact the rest of the business? (e.g will pricing decisions disrupt the supply chain?)

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Leverage decisionOS

the first operating system for decision making powered by Causal AI, to address all those causal questions

Causal AI

To move beyond traditional ML and into a world where you can provide actionable recommendations by leveraging state of the Causal AI tools and methods.

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DecisionApp Building

Seamlessly surface recommendations to your business partners as expressive, tailored and interactive applications focused on decision-making.

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DecisionOps

For the deployment and monitoring of decision workflow, trusting those workflows in production and measuring the causal impact of your decision-making.

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