Telecom

Decisions in the rapidly changing telecom world needs to be fast and based on data and facts. Telecom companies have huge volume of data in their organizations but these are residing in silos. Insights from structured and unstructured data should be actionable in order to drive revenue, arrest customer attrition and improve performance.

Business Brio uses analytics and data science techniques to identify hidden patterns in volumes of data – be it customer, channel or assets – to derive business benefits. The company is performing customer analytics for one of the largest telecom providers in EMEA region since 2015. Advanced analytics and dashboard help the client to understand their competitive advantages, pricing models and mitigation strategies around the challenges in the market. Actionables around demographics and service areas have improved the NPS score over subsequent waves in last couple of years and hence increased penetration in the market.

Business Brio is partnering with telecom clients to improve channel and customer strategy and expand geographical spread.

Forecasting

At Business Brio, we have used Single Exponential Smooth, Double Exponential Smooth, ARIMA and back-propagation neural network. We did find Neural network to have better forecasting performance than the classical forecasting algorithms in case of wind energy forecasting for a particular project and won the NASSCOM Analytics Innovation award in 2015 for effectively using the same for business.

Optimization

Methods like Goal Node, Integer Linear Program, Simplex Method and Interior Point Method are used depending on the context and relevance. At Business Brio we use Lindo as a tool for optimization.

Machine Learning

Unsupervised and supervised learning methods like regression, support vector machines (SVM),KNN, K-means, PCA are used to recognize patterns and make data-driven predictions or decision outputs. We extensively use Python and R for applying the algorithms.

Decision Trees

CART, CHAID, Random Forests, mathematical and computational techniques are used to aid the categorization and classification of a given data information. Apart from programming tools, we also use WEKA for decision trees.

Sentiment Analysis

Opinion mining or emotion AI refers to the use of natural language processing, text analysis, and computational linguistics to systematically identify, extract, quantify, and study affective states and subjective information. In past projects, we have heavily used LSE, HSA, text mining for semantic algorithms.

Forecasting

IoT/Sensor analytics/AI

Our IoT and sensor analytics services utilize advanced algorithms to transform raw data into actionable insights, enabling smarter decision-making and optimized operations. By deploying sophisticated machine learning algorithms, we ensure that your sensor data is analyzed in real-time for enhanced predictive maintenance and operational efficiency. Leverage our expertise in algorithms to harness the full potential of your IoT infrastructure and drive innovation.

Machine Learning

Recommendation Engine

Our recommendation engine services leverage advanced algorithms to deliver highly personalized product suggestions that enhance user engagement and drive sales. By integrating cutting-edge machine learning models, we ensure that our algorithms continuously adapt to changing user preferences and market trends. Experience the power of intelligent recommendations that optimize customer satisfaction and boost your business’s growth potential.

GenAI/LLM

Our GenAI/LLM services harness sophisticated algorithms to provide powerful language model architecture that understand and generate human-like text with high accuracy and least hallucination. We ensure that our solutions can handle complex queries, generate insightful content, and facilitate meaningful interactions.

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Comprehend volumes of data to strengthen telecom network and improve customer experience.

Social Media Analytics

Competitive benchmarking of telecom service providers, service issues and grievances as well as sentiment on brand is measured using social media feeds by creating a machine learning based IT application which comprises data cleaning, analytics engine for topic modeling, classification and view in browser and mobile devices.

Predictive Asset maintenance

Analyze infrastructure performance, usage and bottlenecks to predict maintenance and improve utilization of network infrastructure

Channel Performance

Capture real-time data of telecom channel partners and service providers, map geographical coverage and performance using our proprietary tool and drive outreach programs. Develop short term and long term strategy based on customer data, billing and usage data, channel performance data for strengthening network, increasing geographical coverage as well as customer base.

Customer Value Analytics

Enable understanding and improvement of customer experience across different touch points – network, voice, data – usage pattern, share of wallet, competitive performance by defining the right metrics and interactive dashboard.

Churn Prediction

Reduce churn by building predictive models by using demographics, service parameters – plan and performance, usage and billing pattern and reduce lost revenue from customers

Applications

Advantages

View how our technology works

Scalable solutions for future for seamless upgrades of features and integration with other IT system/data sources for upstream and downstream linkages

In-depth process study to understand the nuances of specific project scope for your product/service

As most of the analytics/data science projects have research based probabilistic outcome and is not as deterministic as other IT projects, understanding and setting a process/benchmark for such projects are very important