Effective CRM Solutions through Data Science

By CIOReview | Monday, June 8, 2015
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FREMONT, CA: A recent research by the IDC predicts that by 2020, there will be nearly as many digital bits as there are stars in the universe, and the data created and copied will reach upto 44 zettabytes (44 trillion gigabytes).

With the growth of technology, information output has become massive. Uncountable devices, systems, and more are being interconnected each passing minute across the globe leading to the generation of enormous amount of valuable data. All this has made, Big Data the most sought after concept of the twenty first century.

One of the primary ways to capitalize on this opportunity is the new generation of tools that can sort and organize the knowledge into a pertinent and applicable vision. For the companies deploying CRM solutions, the potential is greater. Smarter devices and more strategic analyses are making customer relationships stronger and more efficient. 

Due to innovative technologies, harnessing huge volumes of data is not a problem anymore. Big Data then, can be leveraged to make judicious CRM solution. Processing Big Data on the cloud puts the power of advanced analytics within reach of those who cannot afford to install expensive hardware and software.

Tokara Solutions, a CRM certified consultant believes that the key to successfully solving the data science equation is seamlessly integrating such intelligence into existing systems, an approach seen in Salesforce’s recent addition of data science capabilities to its Service Cloud and Marketing Cloud. The Service Cloud tries to automate select customer service tasks by assigning requests to agents based on skill set, case history, and other factors, while Marketing Cloud is designed to drive more direct predictive intelligence and marketing outreach efforts.

By leveraging customer data across the enterprise, these tools can help turn the Big Data into a goldmine of opportunity for engagement, one zettabyte at a time.

The IDC also predicts that by 2020, 37 percent of tagged and analyzed data will be useful, compared to only 22 percent in 2013.