Skip to Content

See what you missed at the Causal AI conference

View site

Transforming Telecommunications with Causal AI

Unlock new levels of efficiency and effectiveness in your Telecommunications organization, across network optimization, customer experience, pricing, promotions, service delivery, planning & strategy, and more.

Trusted by leading organizations

Do these questions sound familiar?

How can we improve network quality and reduce customer churn?

The Causal AI approach: Causal AI identifies the root causes of network outages and inefficiencies, allowing for precise interventions to prevent future issues. It helps prioritize customer support inquiries and determines the optimal investment areas to enhance network quality. Additionally, it assesses the impact of poor network experiences on customer complaints and churn.

Why this matters: Understanding the root causes of network issues and their effects on customer satisfaction is crucial for maintaining a competitive edge. By leveraging Causal AI, telecommunications providers can make informed decisions to improve network performance, reduce churn, and ensure a better overall customer experience.

How can we optimize conversion and customer lifetime value?

The Causal AI approach: Causal AI identifies the causal drivers of conversions and evaluates the impact of competitor pricing on customer decisions. It helps determine the price elasticities of products and suggests precise interventions in promotion strategies to optimize for customer lifetime value (LTV).

Why this matters: Understanding the causal drivers of conversions and customer decisions is crucial for maximizing revenue. By leveraging Causal AI, businesses can implement targeted actions to optimize pricing, enhance promotion strategies, and improve customer LTV, leading to sustained growth and competitive advantage.

How can we optimize marketing campaign performance across channels?

The Causal AI approach: Causal AI identifies the causal drivers of campaign performance, attributing customers to channels while accounting for confounders. It enables interventions and determines the incremental impact of increased spend on each channel, helping allocate the optimal investment across channels within a given budget.

Why this matters: Understanding the causal drivers of campaign performance is crucial for maximizing marketing ROI. By leveraging Causal AI, businesses can make informed decisions, optimize channel investments, and improve overall campaign effectiveness, leading to better customer engagement and higher revenue.

How can we achieve sales targets and improve customer experience?

The Causal AI approach: Causal AI identifies the optimal investments to meet sales and profit targets while enhancing customer experience. It evaluates the impact of competitive, market, and macroeconomic dynamics on P&L and assesses how pricing, marketing, and supply chain decisions affect overall business performance, ensuring informed and balanced decision-making. Our platform does this by utilising your existing data and a structured causal model that you build in the discovery process.

Why this matters: Understanding the interplay between investments, market conditions, and internal strategies is crucial for achieving financial and customer experience KPIs. By leveraging Causal AI, businesses can make precise, data-driven decisions that drive growth, enhance customer satisfaction, and maintain operational harmony, ensuring sustainable success.

Get answers to your business-critical questions

True Causal Understanding

Causal AI goes beyond correlation to uncover true cause-and-effect relationships.

Learn more

Scenario Building & Analysis

Utilize causal structural models to create scenarios, perform historical ‘what-if’ analyses, and conduct comprehensive root cause analysis.

Learn more

Workflow Integration

Data engineering > Causal discovery > Causal Modeling > Intelligence engineering > Decision enablment. All in one platform.

Learn more

Proven Use Cases in Telecommunications

Explore proven use cases in retail and ask us about how you can replicate this success.

Causal AI at AT&T

Watch the talk from the Causal AI Conference 2024

Customer Success Stories

Customer Case Study: Client Retention

North American pension plan improved beneficiary satisfaction and increased retention by 17% using decisionOS powered by Causal AI

Customer Case Study: Marketing Mix Modeling

A leading Mobile App company sees a projected 15x ROI through a reduction of 5% in annual marketing spend using…

Customer Case Study: Manufacturing Root Cause Analysis

$15M annual value unlocked through reduced downtime for a leading commodity manufacturer

Start Your Causal AI Journey

Get your free trial