CASE STUDY
/Telco
$49.8M
annual opportunity identified across prioritised initiatives
7.4x
average return projected for top-quartile use cases
82.1%
data infrastructure readiness — high execution probability
70%
faster delivery, 96% cost reduction versus traditional consulting
Multiple negative-ROI projects surfaced before deployment — protecting capital.
A regional telecommunications provider’s leadership team faced what every service provider confronts in the AI era: 42 competing use case proposals, each promising transformation. Marketing wanted customer lifetime value models. Operations demanded self-optimising networks. Customer service pushed for intelligent automation. Finance insisted on fraud detection.
Everyone had data. Nobody had priorities.
The real challenge wasn’t identifying opportunities — it was choosing which ones would actually move the business forward. Declining ARPU demanded revenue innovation. Digital-native competitors were capturing market share. 5G infrastructure sat underutilised, waiting for intelligent optimisation that justified massive capital investments.
Standard consulting methods — $100–250K, 12–16 weeks, subjective recommendations — couldn’t keep pace with market velocity.
The telecommunications provider deployed MountainsAI’s AI-native prioritisation tool, representing the industry’s pioneering deployment of machine learning-driven use case sequencing calibrated for service provider economics.
Revenue Journey Mapping — Analysed customer touchpoints across lifecycle stages to identify where lifetime value maximisation opportunities were being missed.
Telco-Calibrated Scoring — Applied telecommunications-specific algorithms balancing service reliability, technical feasibility, and financial returns particular to subscription business models.
Regulatory Compliance Frameworks — Built-in data privacy validation across multiple jurisdictions eliminated manual compliance verification overhead.
Accelerated Delivery — Six-week structured execution replaced traditional multi-month engagements.
THE INSIGHTS
From 42 proposals, clear investment priorities emerged — sequenced through the Net Prioritisation Score (NPS):
Customer Lifetime Value Prediction (NPS 80.6): Behavioural models forecasting individual subscriber economic worth. Direct attack on ARPU decline through sophisticated customer segmentation.
Self-Optimising Network (NPS 77.6): Cognitive automation continuously tuning 5G performance parameters. Minimises operational costs while improving coverage quality.
Next Best Offer (NPS 73.8): Real-time recommendation engine delivering personalised product suggestions across touchpoints.
AI Fraud Detection & Revenue Assurance (NPS 72.8): Pattern recognition monitoring transaction flows and usage behaviours. Identifies revenue leakage before financial impact escalates.
CONCLUSION
The telecommunications provider’s experience demonstrates what systematic, evidence-driven prioritisation delivers: strategic clarity replacing endless debate, investment decisions grounded in quantitative analysis rather than organisational politics, and resource concentration on initiatives with demonstrable value creation potential.
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