5 steps to turn data into revenue

4 mins to read

Nowadays, businesses are already drowning in data and having greater difficulty making data truly accessible, accurate and usable for the purposes of critical actions, decisions and moreover revenue growth. The data that matters exists across disconnected silos, in a variety of formats. And much of the data is still unstructured or – more importantly –lost because it’s thought not to be usable.  While new predictive and advanced analytics tools and services are redefining businesses at an incredible speed, many companies are still not sure how to get started.


  • Is your company drive by data? 
  • Are there processes in place to democratize data across your enterprise so even non-technical teams like marketing, sales, and HR have real-time access?  Does your company treat data as a business asset with real financial value and prioritize projects accordingly?  Are your leaders investing in the right mix of technology, people, processes and training to make teams data-driven?

By streamlining the process of gathering and analyzing data for day-to-day business needs and long-term strategic and tactical decisions, you can improve performance and revenue across the organization.

1. Demolish silos and democratize data

With the staggering growth in data volume, sources and formats, companies need to leverage information across the enterprise and beyond. In the past, only a few employees like business analysts had access to all customer data. But to tap into the true value of your data, all your teams, across the organization, need access to comprehensive data insights, in real-time.


CXOx can to bridge gaps between teams and connect the data, tools, and insights that they use. A 360-degree customer view, combined with pooled resources and expertise helps companies implement faster data-to-insights-to-execution business practices.


Companies need to address the lack of critical data skills within their workforce. Leaders should identify “experts” across the organization to train others and customize tools, ensuring that employees have access to the information most relevant to them based on their role.


2. Use cognitive solutions to drive higher customer engagement

While cognitive computing is often associated with artificial intelligence, it’s also changing the way companies use enterprise search on a day-to-day basis. Cognitive systems are already interacting naturally with humans to accelerate expertise and positive business outcomes.


For example,  enable organizations to embed interpretive features like image recognition and natural language question-answering in their applications. These enhanced applications bring data, analytics, and cognitive insights together, at the scale and speed required by the growth in enterprise data. Companies are already using cognitive solutions to monetize data generated every second of every day from customer interactions.


The average employee spends more than 2.5 hours a day looking for information. you can give your sales, marketing, product development teams, finance leaders and customer service teams a unified view of each customer and product and real-time insights needed to detect patterns, understand customers and anticipate their behaviors and needs.


3. Leverage the power of the hybrid-data sources

Not every company is ready for cognitive computing solutions. You first need to a have reliable and secure cloud solution that allows you to link data across multiple cloud environments and combine external and internal data. Enterprises need the cloud to deploy applications quickly, with minimal configuration, in a cost-effective and scalable format.


4. Unleash the potential of all your unstructured data

Is your company deriving valuable insights hidden in documents, emails, chats, call center transcripts, social media content, customer feedback and industry reports? Gameday Decisions can analyze unstructured content to reveal trends, patterns, insights and relationships that help you better understand and grow your business.


While structured analytics provide the what, where and when of a business challenge, unstructured content analytics provides the why and how. This allows companies to anticipate and identify product development barriers, improve product design, resource management, and services, reduce churn, identify competitors and optimize marketing spend.


5. Start small, but make sure your success is scalable

To be honest,  55% of big data initiatives fail to meet the ever-changing needs of today’s global marketplace. Companies need solutions that are easily scalable across organizations, support redundancy, deliver decision analysis across the organization.

A cognitive solution could remove barriers of scale and allow companies to develop simple-to-deploy, cloud-ready, big data exploration solutions.