28 Jan

Taming Unstructured Data - The key to Revenues from Data Monetization

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.

CMP

Here are the Industry Specific Used cases where organisations have extracted actionable Key Performance Indicators from data sources for their data monetization objectives:

·         Financial Services

The BFSI domain generates multitudes of data everyday offering data monetization opportunities across all segments. Financial Services companies can analyse various events in the context of the customer’s lifecycle by predictive techniques to offer customised services, such as travel specific cards for frequent travellers, or loans offerings for customers planning future purchases. Importantly, BFSI institutions may also be able to use this information for customer-retention and customer-relationship management campaigns. Actionable data is an essential component for credit card companies and banks to detect loan eligibility and address frauds.

·         Digital advertising

Sophisticated marketing platforms have given organisations an upper edge to gather data points that take the guesswork out of digital advertising. Availability of actionable data (from Intellibot’s CMP), and predictive analytics have made it possible for marketers to opt for competitive media buying choices.

The rise of artificial intelligence and predictive analytics has powered the advertisers to develop ad campaigns that are helping them gain a deeper understanding of their target audience.

·         Entertainment and Events

Data captured in Entertainment and Events are valuable customer information. This data may be semi-structured or unstructured. Using Intellibot’s Intelli capture and CMP platforms, business enterprises can transform them into actionable data and through predictive analytics sell tickets, target premium services, manage attendee traffic and promote fan-related merchandise.

·         Billboard Advertising

By understanding traffic patterns and traffic plans, advertisers can deliver highly relevant location based content thorough digital signage and other media sources in a dynamic environment. Through CMP and Intelli Parser, companies can achieve targeted marketing in digital signages that may be located on busy thoroughfares or near various attractions.

·         Internet of Things

The data collected from the number of connected IoT objects is expected to reach new heights over the next decade. In my opinion, potential uses for customer data by third parties will grow as the digital economy continues to reach new heights. The data generated is semi-structured and unstructured which can be converted into comprehendible data sources with Intellibot’s CMP and Intelli capture technologies offering huge promise of data- monetization.

·         Traffic Management

Data captured live from traffic movements can be used to optimize standard schedules to understand and plan for traffic at busy roads and special events. Predictive analysis of traffic conditions is a boon for logistics companies who may find this information valuable in optimizing their delivery routes and methods

·         Public transportation

The live data harnessed from public transportation sources is highly unstructured. Intellibot’s CMP can be deployed to convert this unstructured data into structured actionable insights to improve both the passenger’s experience and operational efficiency of their transportation systems.

  • Retail

Semi-structured data like target audience’s spending history; and demographic information are helpful to retailers strategize on the new store locations especially for new store openings. Additionally customer data is a goldmine making retailers deploy predictive analytics to help provide real time intelligence derived by data sources to the store manager talking to the customer.

To know more how Intellibot’s products can revolutionize your business get in touch with us.

Happy Automation!!

About Us

Intellibot is an Artificial Intelligence (AI) company with end-to-end products and service offering designed for the modern business. With its proprietary AI-enabled Robotic Process Automation (RPA) platform, which incorporates a host of next generation features such as machine learning,natural language processing, name entity extraction and computer vision, Intellibot simplifies the lifecycle of RPA deployment through a reliable, easy-to-use and extensible platform architecture. Intellibot enables organisations to create their own software robots, that are easily trainable, secure, flexible and reliable and can work on an enterprises’ day to day business processes, thus, becoming the digital workforce of the organization.