Há tempos numa empresa dei comigo a ouvir alguém a sugerir como usar o Big Data para criar valor para um cliente, para o ajudar a ganhar dinheiro, para o ajudar na sua relação com os seus clientes:
"in the rush to uncover and target the next transaction, many industries are quickly coming up against a disquieting reality: Winning the next transaction eventually yields only short term tactical advantage, and it overlooks one big and inevitable outcome. When every competitor becomes equally good at predicting each customer’s next purchase, marketers will inevitably compete away their profits from that marginal transaction. This unwinnable short-term arms race ultimately leads to an equalization of competitors in the medium to long term. There is no sustainable competitive advantage in chasing the next buy.Um desafio que muitas mais empresas deviam assumir de forma deliberada: como criar valor?
To build lasting advantage, marketing programs that leverage big data need to turn to more strategic questions about longer term customer stickiness, loyalty, and relationships. The questions that need to be asked of big data are not just what will trigger the next purchase, but what will get this customer to remain loyal; not just what price the customer is willing pay for the next transaction, but what will be the customer’s life-time value; and not just what will get customers to switch in from a competitor, but what will prevent them from switching out when a competitor offers a better price.
The answers to these more strategic questions reside in using big data differently. Rather than only asking how we can use data to better target customers, we need to ask how big data creates value for customers. That is, we need to shift from asking what big data can do for us, to what it can do for customers.
Every company should ask three questions to examine how its big data can create customer value:
What types of information will help my customers reduce their costs or risks?
What type of information is currently widely dispersed, but would yield new insight if aggregated?
Is there diversity and variance among my customers such that they will benefit from aggregating others’ data with theirs?"