What Are The Important Reasons to Consider Analytics as a Service For A Business ?

 

The rise of social media platforms, wearables, smart devices, and contemporary data sources has led to abundant data. Most companies have grown in the last few decades and were clever enough to convert this explosion of data into business insights. A recent study found that 85 percent of enterprises view intelligent analytics as pertinent to success, and less than 1 out of 5 leading enterprises felt that they could handle data analytics on a large scale. The most beneficial option is to leverage the benefits of analytics as a service.

• Results of Analytics-as-a-Service

With access to tools, technology, and skilled resources, analytics as a service is an efficient process through which a large volume of data can be processed and transformed into actionable insights. The cost can be a driving force in choosing an analytics solution. Costs can be a driving factor in determining an analytics solution; always consider the impact that analytics as a service has on the key areas.

• Access to insights for C-Suites

With the rapid change in the macroeconomic environment, regulations, market dynamics, and customer preferences, the top executives of companies need exceptional skills to use all this information to their benefit. It is difficult to respond to every shift in the market, failure to keep up with the subtle changes can sometimes prove costly. C-suites should adopt a data-driven culture. They can make critical decisions by combining key insights and trends. Building these capabilities in-house appears to be expensive and time-consuming at the same time. With the aid of analytics as a service, management teams are well-equipped with live market insights while maintaining a low cost of ownership.

• Crafting customer experiences using customer data analytics

Customer satisfaction, customer experience, and the associated return on investments engage C-suite leaders across industries. With the rise of digital technology, customer touchpoints have increased. It provides us with a micro-level view of customer preferences and trends like never before. Most organizations fail to uphold their customers’s data. They get a fragmented idea of the customers, leaving them far behind their competitors in their bid to provide personalized services. Organizations are now using analytics as a service to overcome issues like data silos and tell a unique story in a scalable manner. It enhances the customer experience with analytics-driven solutions.

• Empowers Employees with Data

Predictive analytics enables organizations at all levels to respond to market events with a higher level of precision. From intelligent order management for the retail industry to resource allocation for hospitals based on demand to customized marketing campaigns, the use cases are endless. Some organizations can provide their employees with access to predictive insights. It affects the ability of employees to deliver value as they save time mining and analyzing data on spreadsheets. With analytics as a service provider, organizations worldwide can make intelligent insights accessible to every decision-maker, thus fostering transformation at all levels.

Organizations that lack the bandwidth to create an analytical function with all the necessary supporting elements should consider analytics as a service as the only solution to stay alive in this competitive world. Analytics as a service becomes a champion model when equipped with industry-leading tools, technologies, and domain expertise covering every aspect of an organization. Through this tool, you can reach out and cater to the requirements of different personas. With a self-service model, various customers of different organizations can obtain customized reports while utilizing minimal effort and time. 

In conclusion, through data analytics as a service, you can provide superior customer service to your benevolent customers every time. Even C-suite executives of these companies are not blindsided and can make strategic decisions based on real-time insights.