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Data Monetization Services
Transform your business by identifying new opportunities with data analytics.
Understanding your data value and potential monetization strategies
Your data holds insightful information on your customers, your business, and your industry, though many enterprises fail to realize the full-scale potential of their existing data. Along with providing insights to guide business decisions, you can also generate significant data revenue from your datasets.
At Trianz, we understand how to extract maximum value from your data while still complying with data protection regulations. Our data monetization services aim to convert at-rest data into valuable industry or business insights that can be used internally or externally to generate data revenue.
Leverage best practices in data monetization
Trianz has invested in creating Trasers, one of the world’s largest databases on digital transformations with data from over 5,000 companies around the world. We combine a data-driven approach with practical experience in data monetization to generate results.
“Business teams for Industry Digital Champions leverage data monetization more than 3X of their competition.”
Source: Trasers Global Digital Transformation Survey
Types of data monetization
Here are the various types of data monetization vehicles:
Direct Data Monetization - resell data to interested third parties while respecting data privacy regulations
Data-Driven Business Models - Identify brand- new business models to deliver your existing products and services
Data-Driven Product/Service Improvements - Enhance products and services by analyzing user behavior and competitive offerings
Embedded Analytics for Cross-Sell and Upsell - Increase share-of-the-wallet by offering associated products and services during live customer engagements.
clients we serve
We help deploy analytics capabilities for monetization
Successful data monetization requires a robust, reliable and holistic data foundation. This encompasses cloud data-lakes that contain all necessary internal and external data, as well as powerful visualization platforms to help analyze the data specifically for monetization.
Visualized Insight to Improve Accessibility
Traditionally, data has been structured and alphanumeric, making it difficult to read and understand for employees unfamiliar with data analysis. It also doesn’t tell us the complete story. We remove this barrier by implementing data visualization platforms, such as with our partner Looker.
Platforms like Looker convert alphanumeric plain text data into visually pleasing graphs and charts, lowering the barrier of entry for non-technical professionals. In short, the need for highly trained data professionals is reduced, allowing any employee in any department to generate insights for your business. This is an example of converting data to operational efficiencies by increasing enterprise-wide accessibility to insights.
Orchestrating Multi-Cloud Data Analytics
Platform-agnostic data analytics solutions are essential when using a multi-cloud deployment. Without orchestration, the result is data siloes that limit the velocity and quantity of insight generation. Our partner Tableau is fully cloud agnostic, supporting Amazon Redshift, Google BigQuery, Microsoft Azure SQL, and Snowflake. These platforms are incredibly popular, and by leveraging Tableau with our data monetization services, we can help you to generate data revenue regardless of which cloud provider you use.
The value of your data is dependent on your level of data maturity. By storing large quantities of redundant data, your business is wasting money on data storage while simultaneously decreasing the validity and relevance of insights.
If you want to monetize and generate data revenue, the value will improve if you regularly cleanse your datasets. Trianz experts can help you to remove inaccuracies and duplicate entries, as well as to populate incomplete data fields that improve the quality of your stored data.
Democratization and Data as a Service
Sometimes simply providing data and visualization enablers to specialists in products and services creates the path to monetization. When different departments use different tools to achieve business objectives, data siloes are created that prevent unified and holistic views.
While specialized software can be beneficial, a unified platform significantly improves enterprise-wide accessibility to data. Software packages may use proprietary data formatting or offer limited support for exporting and importing, or lack integration with other business services. These all greatly reduce your data agility.
Orchestrating the transformation with Trianz
Customer Value and Competitive Research
Understanding changing customer behavior and priorities, and the competitive landscape, are essential to data monetization. Trianz has access to one of the world’s largest databases on digital transformation, in the form of Trasers , and we carry in-depth custom research capabilities. This allows us to uncover emerging customer needs and competitive trends, comparing them to your offerings to identify new opportunities through data.
Monetization Analytics Implementations
While there are different types of business analytics, monetization analytics helps drive a focus on leveraging data for direct, business model, product-service improvement or embedded analytics-based monetization opportunities. We help clients extract insights to generate data revenue across customer relationship management (CRM) platforms, social media analytics, sales and distribution, marketing, service, and finance. Our approach includes data science, data mining, and predictive analytics, helping you convert data into operational efficiencies and creating a competitive advantage for your business.
Monetization Strategy
Through monetization analytics, we help discover the possibilities and classify them into direct monetization, new business models, product-service improvements and embedded analytics for cross-sell. Analytics of product, service, customers, channels, sales and marketing data helps us uncover the entire lineage of such opportunities, and leads us to strategies and actions for monetization. We provide our clients a ‘tree-of-monetization opportunity’ from which leadership can prioritize opportunities for near-term gains or strategic opportunities.
Managed Data Monetization Operations
It is one thing to view data monetization as a project, and it is a whole other level of maturity to continuously mine data for monetization opportunities. The latter requires continuous monitoring and cleansing of data and the implementation of specific flags, alerts, and reports in data-lakes to identify new opportunities. Our data scientists and engineers will be your extended arm for data mining and identification of opportunities.
Understanding your data value and potential monetization strategies
Your data holds insightful information on your customers, your business, and your industry, though many enterprises fail to realize the full-scale potential of their existing data. Along with providing insights to guide business decisions, you can also generate significant data revenue from your datasets.
At Trianz, we understand how to extract maximum value from your data while still complying with data protection regulations. Our data monetization services aim to convert at-rest data into valuable industry or business insights that can be used internally or externally to generate data revenue.
Leverage best practices in data monetization
Trianz has invested in creating Trasers, one of the world’s largest databases on digital transformations with data from over 5,000 companies around the world. We combine a data-driven approach with practical experience in data monetization to generate results.
“Business teams for Industry Digital Champions leverage data monetization more than 3X of their competition.”
Source: Trasers Global Digital Transformation Survey
Types of data monetization
Here are the various types of data monetization vehicles:
Direct Data Monetization - resell data to interested third parties while respecting data privacy regulations
Data-Driven Business Models - Identify brand- new business models to deliver your existing products and services
Data-Driven Product/Service Improvements - Enhance products and services by analyzing user behavior and competitive offerings
Embedded Analytics for Cross-Sell and Upsell - Increase share-of-the-wallet by offering associated products and services during live customer engagements.
clients we serve
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