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Even the smallest of businesses today has IT systems that capture structured data.
However, the primary use of business data has been in measuring, reporting, forecasting and planning - in short, to optimize business operations.
Further, different business systems have captured data in silos, with little or no correlation or intelligence applied. Businesses have struggled to extract value from data beyond the obvious uses stated above.
From a table of numbers or mere statistics on a PowerPoint slide, data today has become the most important strategic asset for an enterprise, as evidenced by the large number of businesses that have been built on their ability to harness data.
In a similar vein, Facebook provides brands the ability to reach out to a very targeted base of prospects, resulting in conversion ratios unheard of with traditional advertising models.
The ability to capture big data - vast amounts of unstructured data such as social media feeds, location data, photos and videos, along with real time data from IOT enabled sensors and the ability to analyse it with massive computing power available in the cloud has spearheaded this revolution.
Digital businesses are moving away from expert, ‘gut-feel’ decision making to data driven decision making, and this has yielded tremendous, often mind-boggling insights that have helped not just to save enormous costs, but also to build massive businesses from scratch.
AI, natural language processing and image recognition are making the impossible, possible. Algorithms are today driving more sales and revenue than ever before. More than a third – north of 50 billion USD - of Amazon’s global e-commerce revenue comes from personalized recommendations. Precise customer segmentation is allowing businesses to get closer and deliver incredibly personalized experiences to their customers, resulting in increased revenue and repeat purchases.
Through concepts such as Customer Lifetime Value, data can be used to identify the most important customers for a business. Loyalty programs can help capture vast amounts of data that can yield remarkable insights about latent customer preferences and drive development of new revenue models.
Technology can help transform customer data into business value. It reveals invisible insights about customer needs and preferences.
It spurs innovation and enables higher ROI through targeted sales and marketing efforts. The right technology platform can help to bridge silos and share data without compromising on security and privacy.
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Even the smallest of businesses today has IT systems that capture structured data. However, the primary use of business data has been in measuring, reporting, forecasting and planning...
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