Author: Divya Rao, Sr Manager – Partner Success at INTELLIBOT.IO – Robotic Process Automation
Organization: Intellibot.io
Data is increasingly becoming an abundant commodity in today’s digital world. Organisations possessing rich amounts of data are a common sight today however it is the ability to monetize data effectively that is the key to gain a competitive advantage in today’s digital economy.
Data Monetization or the art of extracting revenues from data requires new skills, processes, and work-cultures to generate the maximum returns. So how is the market for Data Monetization? It is a promising, growing and is expected to reach US$ 708.86Bn by 2025 at a CAGR of 21.4%.
“The key for most businesses is to deliver timely, relevant content in context providing real enablement potential.”
In my view, the conditions for data monetization range from the massive volumes of widely available semi-structured and unstructured data to harnessing the decreasing data storage costs.
We have arrived to the data-driven marketing campaigns that create relevant customer experiences; and improve business intelligence through data automation to harness the maximum from the unstructured and semi –structured data sources that are in vogue today. Currently, more than 80% of the data mined is unstructured making way for intelligent data capture through automation open new business avenues. By reading the complex unstructured data, companies can identify new trends and business opportunities, and in the long run make strategies around both structured and unstructured data.
Data is the new Oil to the World
Both small and large enterprises are strategizing on data monetization to generate new revenue streams. Alibaba CEO Daniel Zhang remarked at the Nielsen’s Consumer 360 Conference that the Chinese e-commerce major is focused on collecting consumer data and went on to say that data is Oil in the new Data driven economy.
I view that, to succeed from data automation it is imperative to have a trusted partner with a go-to market expertise in pre-built solutions and domain specialisation. Companies that have data-monetization experience, have learned the hard way that it is insufficient to simply put data and tools into the hands of employees without providing for adequate training sources, thus to harness the new oil goldmine it is essential to train your resources with the best of trainings.
The key to Achieve Data Monetization
Can marketers add value using data to create spectacular offerings? I my view Yes they can, and there are multiple cases where it is already being done by Predictive Analytics and Intelligent Automation making organizations bring together process, people, technology and information into a value network and provide extensive selection of data and decision-making capabilities.
Intellibot’s Predictive Analytics offerings coupled with the latest CMP (Cognitive Modelling Platform) makes data monetization process automated by transforming large volumes of unstructured enterprise data generated through images, invoices, e-mailers and so on into a monetary goldmine. In recent times, growing organisations have been increasingly using Predictive Awareness to identify concealed opportunities and uncover hidden risks buried within their legacy systems.
How can we link Data Monetization and CMP?
Intellibot offers a host of offerings to transform data into valuable insights. Intellibot’s Intelli capture solution works on semi-structured data like invoices, purchase orders, forms etc. deriving the required data points. The latest offering from Intellibot, Cogitative Modelling Platform (CMP) runs on highly repurposed machine learning and deep learning algorithms, to transform unstructured data to structured content, an essential step to make data pre-processing and analytics core to organisations. The Predictive Analytics offering from Intellibot consumes models created in data science platforms like Knime, Alteryx, H2O.ai integrate with Intellibot’s remote desktop automation (RDA) offering to help provide real time intelligence derived by data sources to the agent talking to the customer.