“Data is a capital asset in digital economy”
Rough-cut estimate on the absolute $ value being created by 1 GB of data is 3₵ to 5₵ without factoring qualitative value creation of data. The value created by big data is constantly increasing with further advancements. This put in a context the overall potential of Big Data that is approximately growing at 40% annually taking the size of data to 44 Zettabytes by 2020. It is also projected that about 37% of that data will be useful if tagged and analyzed properly.
I was trying to understand and unveil how Big Data creates value to businesses? In true sense, the value is co-created by virtue of big data interconnecting the businesses with consumers. Getting further deep into the big data resources and platforms co-creating value helps the businesses carve out competitive strategies in the data-age. Businesses creates and offers “Platforms” as a means for consumers to create and share data back. Summarizing below on platforms being deployed by businesses to engage with consumers to capture big data and there by the co-creation of value.
- At a basic level businesses deploys “transactional platforms” to process buy and sell tractions e.g. kiosks, POS systems, payment gateways etc.. The buyer role of consumers generates “transactional big data”. Purchasing behavior, price, product category, color, numbers, buying cycle, location, and demographics is the source of transactional big data. This data can help business to profile consumer behavior, run tailored campaigns and create shopping guides in the provision of customized services.
- Use Case: PayPal processes more than 20+ terabytes of log data every day using Hadoop data platform for sentiment analysis, event analytics, customer segmentation, recommendation engine and sending out real-time location based offers.
- The second popular platforms are “virtual social networking platforms”. These communication platforms support consumer community communication and enable the collection and transmission of “communication big data”. The information generated from communication platforms is non-transactional in nature and offers mountains of value. Consumer’s favorite topics, trends, emotional feelings, or characteristics could be reflected by these data. Businesses leverage communication platforms to attract customers with different themes e.g. enable customers to stay, review, give thumbs-up, or forward their favorite threads. Opinion leaders may emerge after frequent interactions. Some businesses grant opinion leaders certain authority, such as casting a ballot for controversial topics etc.
- Use Case: Delta Airlines Airline uses communication platform for sentiment analysis to analyze flyer tracking experience. Delta monitors tweets to find out how their customers feel about delays, upgrades, in-flight entertainment, and more. For example, when a customer tweets negatively about his lost baggage with the airline prior to boarding his connecting flight. The airline identifies such negative tweets and forwards to their support team. The support team sends a representative to the passengers destination presenting him a free first class upgrade ticket on his return along with the information about the tracked baggage promising to deliver it as soon as he or she steps out of the plane. The customer tweets like a happy camper rest of his trip helping the airlines build positive brand recognition.
- The third type of platforms that support businesses’ effect to attract consumers to participate actively in product improvement and to re/configure new services or new business decisions. Businesses use collaborative features these participative platforms to accurately reflect personalized demand and generate substantial amounts of participative big data from consumers. The data collected on these participative platform is shared among R&D, designers, engineers, managers, and procurement for potential actions.
- Use Case: P&G leveraged participative platform and resulting big data successfully into its new product development process, by aggregating consumer data from multiple brand touchpoints and using it to both launch and promote new products. For example, P&G used them to determine how the molecules in certain household products like dishwashing liquids will react over time to refine the product.
- The forth type of platforms that support businesses in acquiring new knowledge shared by consumers who build connections across diverse ecosystems. Establishing or joining a multi-brand and multi-industrial virtual community is an efficient approach for businesses to establishing a transboundary platform. The intermediary consumers generates transboundary big data. Transboundary big data refers to data generated by consumers who share different service ecosystems and facilitate the export and import of knowledge across different ecosystem boundaries. Consumers act as intermediaries because the Internet significantly reduces switching cost and searching cost for consumers and enables them to try different brands, products, or purchases.
- Use Case: A largest automaker use transboundary big data to support predictive marketing that helps automaker build brand loyalty by boosting its aftermarket service revenues. Automaker analyzed customer data from multiple sources, vehicle data and the qualitative notes written by technicians to entice auto owners to come to its service centers.
Big data and Internet-based technologies have empowered consumers and forced businesses to be more consumer-centric. The advent of the big data and Internet significantly reduced information asymmetry between consumers and businesses, increased customers’ bargaining power and, consequently, changed the power structure. As a result, big data co-create the value by interconnecting business with consumers and defining win-win scenarios. Hence the necessity to progressively excavate consumer big data and analyze potential demand in advance of competitors have become a fundamental requirement for businesses in the fiercely competitive global market.