Analytics for Media & Telecom

Media & Telecom service providers are sitting on a pile of data. Most are considering monetization of network data and content that can provide valuable insights and create a platform for improved services and next best offers (NBO) to enhance revenue and optimize costs. Due to the exponential growth of communication channels, content and consumer touch points Media & Telecom organizations need to leverage analytics to capture consumers’ attention. 

How Wipro Helps

Rapidly evolving technology, diverse customer needs and new disruptors (OTT, LTE) in communication and media space are adding to the challenges of customer churn and declining ARPU.

Using advanced analytics, Wipro offers business solutions that will help you achieve actionable insights to improve customer, network, operational and financial intelligence.

Our solutions help you:

  • Deliver next generation customer experience
  • Improve operational efficiencies
  • Speed up growth
  • Arrest customer churn
  • Manage the digital ecosystem
  • Have continuous business innovation

Our Analytics solutions aid in your transformation from a traditional BI environment to actionable insights-led predictive/prescriptive BI environment.

Our Analytics solutions help you to evaluate customers patterns and behaviors in order to forecast a long-term value and brand loyalty.

Our Analytics offerings for Media & Telecom include:

  • Analytics Lab On Hire: This is an innovative, Managed Service model that will help evaluate a Proof of Concept (PoC), carry out a beta test on a specific methodology or even research on certain analytics implementations without making an upfront investment in technology or hardware. Validated methodologies are then applied to real business situations and deployed to processes. Once the PoC or beta test yield expected results, it is scaled up and replicated across the organization
  • Social Media Analytics (SMA): SMA provides a multichannel solution to improve customer experience management, marketing offers management and two-way dialogues. It is used to achieve the highest degree of customer engagement, broader brand presence and improved reachability across platforms
  • Next best offer (NBO): NBO is a process that uses a combination of predictive models, information from various sources, business rules and set of arbitration logic to arrive at optimized customer and business-centric offers selection. It is used to get customer insights, and understanding campaign performance with details on segmentation and model library

Our Media specific solutions include:

  • Attribution Modeling: This solution offers channel specific ad-budget optimization for digital ads based on click stream data
  • Pay per view (PPV) Ad Optimization: The solution provides you with insights for pay-per-view ad placements to maximize ROI from ad spend
  • Viewer Analytics: It analyzes the data generated by set-top boxes (STBs) to provide insights into viewer preferences. This data is used to improve content alignment or customized offers for an enhanced viewing experience
  • Web Analytics: It measures the performance of Websites that can help in content and marketing optimization. The data is typically compared against key performance indicators and used to enhance the website or marketing campaign's audience response
  • Wipro ATHENA: It is an advanced multi-platform advertising solution that enables you to add premium value to your advertising offerings through addressability, interactivity and state- of-the-art campaign management

Our Telecom specific solutions include:

  • Telecom Insights (TI): Our TI Solution helps you achieve effective Intelligence so business goals of growth and operational efficiencies are realized. read more...
  • Event Based Marketing (EBM): EBM Analytics Solution leverages network data collected from network elements in near real time. The solution enables you to optimize marketing campaigns, reduce churn, boost revenues and enhance customer experience
  • Churn Modeling: It relates to the various network data variables to estimate customer churn propensity