Enterprises focus on leading the business competitive landscape by leveraging powerful digital data and predictive analytics, through an amalgamation of digital intelligence and thought leadership.

What Analytics lived to be

Traditional IT infrastructure in the annals of analytics approach, was not meant for the deluge of data information from various sources. It was not designed to handle the extensive channels, devices, volume, and speed that fuel current digital interactions. The gap can be seen in the proliferation of analysis tools, the explosion of data warehouse projects, and the struggle to translate analytic into actionable insights.

Market scenario of data analytics

According to 451 Research, the total data market is expected to grow from $70bn in revenue in 2015 to a massive $132bn in 2020.

The major forces driving the managed services market include flexibility to match custom requirements, continuous upsurge in dependency over heterogeneous networks, and persistent rise in the complexity of technological solutions.

Visualizing the surge in data, the business challenge will be to overcome the multichannel analytic limitations of aggregated data collection methods used by traditional web analytics.
It is now, that Digital Intelligence provides a big opportunity for business to leverage big data and predictive analytics in their IT infrastructure.

Inject Digital Intelligence to your IT infrastructure

Digital Intelligence is defined as the collection, analysis, and management of customer data to provide an all-inclusive view of their digital experience. It drives the measurement, optimization, and execution of their digital customer interactions. IT infrastructure can leverage predictive analytics as part of their digital intelligence tactics to focus on customer experience for taking business and market decisions.

One way to avoid being inundated by poor customer experiences, irrelevant business reporting, and siloed customer insights, is by employing advanced digital analytics approaches such as predictive analytics. This acts as an enabler for businesses to rethink how to collect digital behavioral data while considering larger downstream business applications.

Individual Customer-Level Digital Data Is an Asset

Gearing up for the competitive business landscape involves modernizing their existing IT infrastructure environment with advanced analytics and digital intelligence strategies. Collected at the individual customer level, the data volume, velocity, and variety present the predictive analytics tools with structured and unstructured data from both traditional and digital data sources, to provide valuable business and actionable insights.

Organizations essentially need to facilitate an IT infrastructure that automatically scales, adapts to market forces, and provides a competitive advantage. The focus should be on these three digital intelligence tactics:

  1. Cloud- and Mobile-first strategy:Millennium customers expect to work or interact with applications on a mobile interface, with instant connectivity and accessibility. The emphasis on positive customer experience is motivating businesses to shift towards cloud platform that allows effective management of the huge data influx from the growing interconnectivity of devices. Easy scalability, availability, and cost-effective benefits are making business leaders rethink on how their IT infrastructure is ready for this cloud shift.
  2. Predictive and self-healing systemsIncorporating predictive analytics for IT systems allow them to detect and predict events that may deter business productivity and effectiveness. Using appropriate API’s that serve as a backend for services, businesses can help build systems that can protect and serve the customers.
  3. Production of prolific intelligenceCIOs will need the right answers to the right questions to evoke appropriate actions. The rising dominance of big data mandates that businesses leverage analytics to correlate the necessary data and act on that intelligence faster than their competitors.

Organizations are inundated with big data from the web, social and mobile app sessions across devices, browsers, and multiple domains. Utilizing the predictive analytics tools with the existing first-party (or company-owned) customer data, the business leaders can correctly interpret the churned data to make informed decisions.

Analytic visualization is the subsequent process that presents a visual representation of the churned digital data as graphs, dashboards, or charts for the business leaders to make knowledgeable decisions.

Organizations are now intended to optimize their IT infrastructure using digital intelligence and convert opportunity into value-add business revenue generating avenues.

GAVS has expertise in next generation technologies like advanced predictive analytics and analytic visualization to transform businesses and optimize their IT infrastructure to stay competitive and meet customer demands.