siliconindia | | OCTOBER 202219to their data type and objectives, such as market access and interests, primary or secondary research, deliverable creation from that data, and sales and monetization. Quite a few businesses across industries happen to own a lot of data that can be monetized after removing company identifiers. A good example would be user pattern analysis or geo-location data that can be applied to tasks such as traffic forecasts on street maps.By removing indicators that could lead to potential user privacy infringement, many big-name companies happily generate revenue from their data, enriched with raw information regarding consumer behavior and habits. (Spotify and YouTube are notable examples of this monetization model). Generalized or anonymous data is usually unstructured and consequently difficult to process. Extracting monetary value-- pitching it to businesses--is suspect unless coupled with tools to structure or compile it into usable forms.The Resulting Data-driven Culture has the Following Attributes:· Enhance data curiosity and explorative ventures.· Encourage data reuse and promote interoperability, collaboration, and transparency.· Embed internal systems with tools to derive value from data.The indirect monetization model can save costs and add value to data collected internally. This practice is predominantly evident in services that serve data as a product, for example, business intelligence deployed on the enterprise intranet. Companies can make more informed decisions on resource planning and allocation based on utilization insights and return on investment when they gather, analyze, and process internal data. Apps planted strategically across enterprise systems generate contextual data that is processed through hyper-intelligent systems to gain insights on process efficiencies and, in many cases, predictive and prescriptive insights. Modern technology such as artificial intelligence and machine learning lead a company's indirect data monetization model. Multifaceted automated tasking enables cost savings and adds value to the end products of a business. Key Business Processes, as Follows, are also Streamlined:· Sales, marketing, and customer experience.· Predictive, cognitive, conversational, diagnostic, descriptive, augmentative, and prescriptive analytics.· Data exploration and sale to third parties.Many of today's digital-era necessities require businesses to improvise and be more agile. This trend drives the data exodus from legacy, hardwired systems into the Cloud--another indirect data monetization strategy. Cloud functionality assists companies to catalog unstructured data with semantic data layers, metadata, data lineage, and other organizing methods, which are available on a pay-as-you-go basis. We knew already that data holds power. However, as the world evolves around technology, information is being increasingly commoditized. Are you positioned correctly to profit from your data? If not, now is the time. Each market research firm's strategies evolve and align to their data type and objectives, such as market access and interests, primary or secondary research, deliverable creation from that data, and sales and monetization
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