Is your Data Analytics isolated from the customer reality?

Big Data is the means to the end, not the end.

There are many big perspectives of Big Data; customer insight is surely one of the key arenas Big Data can make big difference. There are plenty of examples that show the analytics is really working. However, in many organizations, the fact is that the data analytics is isolated from the customer reality, what’s the root cause, and how to truly bridge the data analytics and business/customer perspectives?

The biggest challenge is to create a corporate culture that incorporates analytics into the decision process. The best way is to start small (few reports and few process) and engage in a spiral of continuous improvement. The results in additional revenue and increased profitability can be astonishing. So if there’s data isolation existing, it shows the big gap between proper execution and data storage, all those companies store petabytes of data, but without proper data/information management of that, it’s useless.

Big Data analytics is the means to the end, not the end. One of the biggest invention of corporation is their Great Customer Service. While the biggest impacts come from starting with the customer then building the data insights and business processes to serve them better. Most companies are so bogged down by the complexity of their own businesses and new technologies that they forget to think about their customers enough. "What is it that my customer is trying to accomplish? How can I help him/her do that?" These are the key questions they forget to ask.

The isolation in responsibility is the gap the industry needs to mature up to. The isolation of responsibility plays a part along with the focus of these groups on their KPIs and what insights and data can tell them. How can you give service to customers when many of their call center, data analyst, BI and so on, don't even know the product for which they are given service. The isolation in responsibility is the gap the industry needs to mature up to. While one arm revels in discoveries made through analytics & BI, it does not necessary translate into actions (or even data) for the marketing through a funnel that enables team members with "personalized" approach when reaching client.

There are still quite a bit of work to do in turning analytical results and connecting to the operational system. More often, the analytics team in the company correctly recognizes the customer value, but that knowledge is still only within the analytics team. The connection between the analytics and the operational system has not been made yet. There are plenty of organizations doing the analytics, but not yet have matured the process enough to drive the front end systems.

Focus on alluring new customer, with the ignorance of long term loyal customers. The business model ignores long term loyal customers because the model says that those customers are satisfied and will continue paying the company for services, many companies currently do not care whether you leave or not; their emphasis is on using marketing, advertising, data analytics to entice new customers to pay for their services. There're analytics gaps need to be filled out for delighting the current customers as well.

Lack of incentive to motivate customer service professionals to take extra miles: Regardless of how good machine learning gets, companies will never be able to achieve the good customer service with machines and big data as they can with one customer representative that owns shares in the business. The customer representative works with the incentive to do a better job in customer service than a machine could. This is the incentive business needs to really succeed in customer satisfaction.

Big Data has big potential, however, it shouldn't be grown in the ivory tower, it has to be connected with the business reality and explore the customer insight in order to build an intelligent and customer-centric business.