With social media on the rise and more and more human behaviors leaving digital footprints in the virtual space the discipline of marketing data analytics have gained a new powerful information base. Estimates say that consumers generate more than 2.5 quintillion data bytes every day. Most of the stored data has been created just recently through the internet of things and that is just the beginning. Big data constitutes a foundation for endless analyses and discovery. So called Big Data includes traditional marketing information sources as well as (new) data harvested in digital space, whether it comes from social media, sponsored links, websites, transactions, sensors, devices, wearables, apps or cellphones to name a few.
As Gartner consulting company asserts, Big Data can be characterized by high volume (amount), high variety (different sources, variety of forms, cocktail of structured and unstructured data) and high velocity (the speed at which data is being produced or self-generated and at which they might be flowing within and into the enterprise). Big Data, which is by definition available in large quantities, eases out concerns about evidence quality as it covers sheer digital populations in their entirety. On the other hand may, analysts require more robust infrastructures to arrive at conclusions.
Big Data presents both an opportunity and a threat to businesses. Its potential is anchored in the ability to answer numerous market-related questions without resorting to expensive primary data collection methods. Pitfalls are hidden in the necessity to master robust analytical techniques underpinned by excellent methodological guidance. At times, Big Data require additional or different technologies for data warehousing and analytics. A major challenge, however, could reside in neglect of Big Data altogether. In spite of recent surveys confirming that companies have been gradually investing in Big Data, only a tiny portion of businesses is able to drive value out of it. Utilizing Big Data in a meaningful way assists to sustain competitive pressures and gain further competitive advantage.
Big Data analytics substantially increase market intelligence. Instead of relying on gut feelings, marketers now make informed decisions supported by more accurate predictions of buying behaviors. Big Data utilization allows for personalized offerings and complement traditional customer relationship management data or evidence gained from loyalty programs.
Gartner predicts in 2015 that by 2020, Big Data will be used to reinvent, digitalize or eliminate 80% of business processes and products as we know them today. This year, more and more Big Data analytical tools for companies will become readily available to companies. Cloud services and data warehousing companies will likely introduce new Big Data software support. For a period of time, companies may be struggling to attract the right talent for Big Data tasks. Professional Big Data analysts have been scarce and specialized analytical firms might have been gaining necessary experience still.
At the same time, we may expect more intense discussions about digital privacy and security. Companies using Big Data will need to find answers to enhanced data safety, privacy, data protection, ownership and copyright issues. Only those entities, who will possess the key to classified information and analytical findings derived from petabytes of stored logs, will succeed. Encryption mechanisms will need to be developed beyond our current imagination.
The future of Big Data marketing is scary and exciting. Marketing driven by outcomes and accountability will be on increase. Marketing analytics will need to receive curricular boost in marketing-focused degree programs. Big Data analytics will gradually make its way into academic papers.
Mějme ambice: Jak Big Data mění marketing
Podle mnoha předpovědí bude z hlediska využívání Big Data pro manažerské rozhodování přelomový právě letošní rok 2015. Big data představují nový pohled na informace o chování zákazníků a jejich potřebách. Kombinace tradičních primárních i sekundárních tržních informací stále více uvolňuje analytický prostor pro data pocházející z digitálních zdrojů – sociálních sítí, webových stránek, aplikací, navigačních přístrojů, chytrých telefonů či různých senzorů. Tzv. internet-of-things produkuje z hlediska objemu, variability i rychlosti zcela novou kvalitu dat, s níž se marketéři musí naučit pracovat.