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Telecom analytics is the process of analyzing large volumes of data generated within the telecommunications ecosystem to extract valuable insights. This data can come from various sources including network infrastructure, billing systems, and more.

Modern telecom analytics platforms unify this data and offer flexible ways to explore it, from visualizations that business users can explore without SQL knowledge to in-depth analysis in an analyst’s preferred language.

Media analytics is the process of collecting, analyzing, and interpreting data across media platforms and backend systems. This data can include viewer engagement, ad impressions, subscription activity, social media sentiment, and more.

Modern media analytics platforms consolidate this data and provide flexible ways to explore it, from visualizations that business users can explore without SQL knowledge to in-depth analysis in an analyst’s preferred language.

Telecom leaders use analytics to optimize network performance, reduce outages, and make smarter business decisions. By analyzing usage data, traffic patterns, and signal quality, they can proactively resolve service issues, forecast demand, and plan infrastructure investments. Predictive analytics helps prevent network failures, while data governance ensures regulatory compliance. Telecom analytics also supports market analysis, guiding product development, marketing strategies, and customer retention initiatives.

Media companies use analytics to understand audiences, optimize content performance, and maximize ad revenue. They track viewer behavior, engagement metrics, and platform usage in real time, using it to personalize recommendations, improve retention, and identify high-performing content. Analytics helps ad operations teams increase inventory yield, reduce waste, and improve campaign performance across channels. Additionally, media leaders use predictive insights to forecast demand, guide programming strategy, and respond quickly to shifting viewer preferences and market trends.

Telecom and media professionals today need analytics platforms that drive real business value by improving customer experiences, increasing operational efficiency, and unlocking new revenue opportunities across networks, platforms, and channels.

Unlike traditional BI tools, modern analytics platforms help unify data across fragmented systems—whether that’s OSS/BSS and CRM in telecom, or ad servers, content platforms, and subscription systems in media. The most effective platforms offer built-in integrations and APIs that connect data from across the business, creating a single source of truth for every team to work from.

A key capability is self-service analytics—tools that allow non-technical users to explore real-time data, track KPIs, and answer ad hoc questions without relying on analysts. This not only speeds up decision-making but also frees up data teams to focus on strategic work.

Another major shift is the rise of agentic AI, which uses large language models (LLMs) and machine learning to simplify complex analysis. Instead of building SQL queries or dashboards, users can now ask natural language questions like “Where did we see the most network congestion this week?” or “Which content drove the highest engagement among Gen Z?” and get fast, explainable answers.

Today’s leading analytics platforms replace static dashboards with dynamic, personalized insights that adapt to the needs of every team—whether that’s optimizing 5G performance or improving OTT monetization. By embedding AI-powered intelligence directly into the tools and workflows teams already use, these platforms help telecom and media companies deliver smarter, faster decisions without overwhelming engineering and data teams.

ThoughtSpot combines powerful AI capabilities with an intuitive interface that makes it easy for telecom and media teams to explore their data and make smarter decisions—no analyst skills required.

Data teams use the platform to unify fragmented data across critical systems like OSS/BSS, ad servers, content management platforms, CRMs, and subscriber portals. They build scalable analytics solutions that internal stakeholders—from network operations to ad sales—can explore and act on independently using natural language search and AI-driven insights.

These stakeholders span many teams and business lines. In telecoms, operations teams use self-serve analytics to monitor real-time network performance and resolve service issues quickly. CX and marketing teams track churn signals and provide perfectly-timed resolution paths or special offers to customers. In media, ad ops teams improve conversion rates while content strategists monitor viewer engagement to guide programming and licensing decisions.

Executives and strategy leaders gain a holistic view of business performance—across audience behavior, monetization, service quality, and infrastructure—enabling faster, more confident decisions that align with revenue and customer experience goals.

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