Businesses around the world are gathering a lot of data from customer interactions. Organizations are extracting value from their unstructured data. Its value increases upon being structured, evaluated, and used. Collecting data at the right time and using it strategically can increase its worth manifolds. Gartner predicts, nearly 35% of large organizations will either sell or buy data by 2022. Furthermore, these transactions will be facilitated through formal online data marketplaces.
All the data you collect can be used to boost either your own business or that of a complementary service provider. For instance, insights from customer conversations can be used to enhance customer experiences and improve service quality. Customer sentiment captured through surveys and feedback can be used for product and service innovation. From target marketing to upselling opportunities, you can monetize your data for various purposes.
Why you should monetize your AI models
You can understand data monetization as the process of generating measurable economic benefits from your data assets. Data and analytics combined with AI can help you predict prepare and respond proactively to the dynamics of your industry. It can be used to create superior products or services.
You can use it to:
-Innovate: Cross-industry insights can be used to identify disruptive indicators. It helps you in building new products that meet evolving customer needs. Identifying more business moments is the topmost priority for growing organizations.
-Optimize: Process optimization allows efficient use of resources and allows companies to do more in less time. Using data for exploration allows you to detect process lapses and address inefficiencies.
-Improve performance: Productivity can be increased using data. Studying data helps reduce downtime through predictive analysis. Remediating processes and identifying efficiency levers helps improve performance.
Or sell the data to other organizations looking to achieve similar goals.
How can you monetize your AI models?
Data monetization happens both internally and externally. You can use data for your own business or sell it to other organizations to:
- Create new digital services: Most organizations are concerned about streamlining data collection. AI can be used for collating data collected from various sources. Implementing advanced techniques such as Machine Learning (ML), Natural Language Processing (NLP), and Machine vision for using it effectively. AI-powered real-time data collection improves accuracy and eases the decision-making process.
- Reduce customer churn: Losing existing customers is costlier than acquiring new ones. AI models can process unstructured data collected during customer interactions to gain a deeper understanding of their preferences. Companies can use it to improve their customer service and drive more purposeful conversations.
- Unleash the potential of premium data: Premium data may be more trade-oriente but is equally worthless as unstructured data. AI helps in evaluating it to improve internal and regulatory processes. Augmented intelligence allows you to integrate this data with your CRM for ongoing process improvements. Implementing Deep Learning helps in processing it to exhibit analytics for informed decision making.
Data Monetization Business Models
When it comes to selling data, you can use the following approaches to build your data monetization models:
- Data as a Service: The simplest model for data monetization, Data-as-a-Service, is also known as Data syndication. It involves selling anonymous, aggregated data which is analyzed by the buyer through data mining. The data may be used for offering convenience and personalization based on customers’ habits and preferences.
- Insights as a Service: This model does not involve the actual selling of data. Under this model, internal and external data are assessed to derive valuable insights. The insights are sold under a decision-support model to help the dependent organization make a choice.
- Analytics-enabled platform as a Service: The most complex data monetization model that offers maximum value to consumers. It collects insights from your data and makes them available through a cloud-based platform. Multiple users can access the insights in real-time over the platform and bundle them with APIs to activate triggers.
Takeaway
Companies must realize the potential of their data and treat it as an asset. To maximize the internal and external monetization of your data, you can leverage AI technologies. Use it to automate data collection and analytics. Leverage AI techniques such as ML, NLP, RPA, and Machine Vision to extract value from your data. Besides value creation, you must also identify the right market for your insights. Putting in place a robust data monetization strategy may be time consuming but it helps you unlock immense financial value.
Madhav Bissa
Supriya Samuel
Raj Shekhar
Tarun Kumar
