Since it started to make a dramatic splash on the public scene, big data has gradually shown a glimpse of the benefits it can offer businesses. Initially focused on storing and providing access to massive volumes of data, big data quickly became the “Holy Grail” for marketing specialists.
Engagement, loyalty, sentiment, sales forecasting - big data has improved segmentation and decision-making. At this stage, it was mostly an extension of pre-existing analytics strategies, increasing customer knowledge through more numerous, more granular and more contextual data. A good example would be databases of market leaders such as Walmart that are now able to acquire more than one million transactions per hour.
Beyond marketing, other data professionals in healthcare, banking, finance, telecommunications, etc. quickly started to realise how their industries could also benefit from big data. In 2012, McKinsey estimated that for the healthcare industry alone, big data held a potential value of £175 billion, just through optimisation of existing processes based on better knowledge.
Big data now sustains operational procedures
Riding the success wave of these analytical projects, companies are now seeking to go one step further by automating their strategic procedures and processes based on “big analytics”. The most publicised examples include Amazon’s or Netflix’s recommendation engines, which did not wait for any media buzz to start analysing large-scale data.
This operationalisation of data has cleared the way for innovative strategies, aimed at creating new sources of value. Big data has become a tool to help companies explore new territories and achieve results that were once deemed impossible. In these cases, big data may reveal an intrinsic value that was not necessarily expected. For example, every retail chain worth their marketing budget studies the buying behaviour of their consumers through the analysis of receipts and loyalty cards.
The goal is to improve the customer experience in the store, to highlight certain products and to boost loyalty with customised offers. Digging further into the data will drive the retailers to work with their suppliers, for example enabling them to send instant location-based coupons to consumers on their mobile phones.
In another field, TomTom, the leading provider of tracking and navigation products and services, collects billions of records from its customers’ two-way GPS systems on a daily basis. While this data is used to optimise the routing provided to users in real-time (avoiding traffic jams or construction zones), it is also sold (consolidated and anonymised) - for example, to local authorities to consider roadway and infrastructure improvements.
These two examples illustrate how big data can change company business models and bring new sources of revenue to light. In TomTom’s case especially, the company has not changed its business, but found new sources of revenue with new customers.
A radical change of business model
The next milestone is on the horizon, when some companies will drastically change their business models through monetisation of data. Take for example, a sports shoe manufacturer seeking growth in a very tough competitive environment. Observing the progress of the Internet of Things, it sees in the “quantified self” movement a means of radically modifying its business.
The manufacturer may decide to offer (or sell at a loss) good quality connected shoes, in order to get more value out of the data collected and monetised. The model is none other than Google’s, which offers a search engine (and even a browser and operating system) to better collect data it then leverages commercially. In this case, the sports shoe manufacturer retains its original business, which becomes a “pretext” to collecting data and positions itself in an entirely new business.
The prospects are basically unlimited. Big players understand this, like Apple did when launching a business of selling music and apps, or Google when buying Nest. More and more companies will choose alternative paths that stray from their original line of business. Keep an eye out for automobile manufacturers, for example.
These manufacturers have already drifted from their historical business model (building and selling cars) by offering financial and insurance services. They are now becoming car-sharing operators (think Zipcar) and are also adding value by analysing driver behavior and monetising these analyses.
A true revolution is underway. Data is and will continue to be at the heart of the business world in the 21st century. And the giants of tomorrow are being created today.
Posted by Yves de Montcheuil, VP Marketing, Talend