Customer experience management continues to be a rapidly gowing segment, (Huffpost article with good data) estimated to grow at 20% CAGR over the next 5 years. Key factors that are driving this growth include; 1. Increased enterprise level closed loop management; 2. Establishment of the virtuous circle of employee engagement with CEM; and 3. The realization that there is an undeniably higher ROI for managing your current customers, rather than spend on new client acquisition. (Your current customers will bring the new clients if you manage this well). I could speak at length on any of these shifts, but I believe that the most significant changes will come with the increased integration of CEM data with corporate big data initiatives, especially when they are integrated with loyalty card data. If you think the 20% growth rate of CEM is impressive, consider that that Big Data is growing at 58% CAGR according to IDC! One can only wonder what the potential is at the intersection of Big Data and CEM? Loyalty card and point systems are now essentially mandatory in any mature retail business of any size. These point systems are providing the basis of the data for advanced merchandising and effective one to one marketing. It's important to note that these systems have grown because they are tied directly to a measurable ROI, therefore comapanies are committed to these (conversely, it's psychologically difficult to cut a program that the data suggests would also reduce your revenue). Merchandising with this approach is essentially leveraging on the economic principle that selling to existing customers is more efficient than selling to new customers. Taking this one step further, when we look at the Customer Experience economics, we know that customers will spend up approximately 25% more with merchants that provide the most superior service. To achieve superior service, one needs to have highly engaged and efficient employees, which the research tells us provides for up to 30% productivity improvement in distributed organizations vs the average. Of note then, is the connection between big data and just these these three perspectives. There are additional perspectives that can contribute further insights, such as full transactional information from coalition points or credit cards, but this is a digression from this post. Companies are starting to map out the journey of a customer on a more holistic perspective:
When the customer begins thinking about purchasing (merchandising with the points card data),
To delivering a truly differentiated customer experience on site (based on the points data of the individual and their customer experience feedback history)
Through the attention and consistent service level of the engaged employee (systems tied to customer awareness - see my post on the Tampa Bay Lightning).
Key to the customer experience is ending this on a positive note, ie at the customers perception of the end of the transaction.
So what does this mean to big data planning? As companies start looking at operational optimization, it becomes clear that the employee and customer engagement processes must be inextricably linked to the one to one customer loyalty (points/cards) systems. Predictive data projects will flourish where there is observable ROI and specific actions that can be defined as a result. The areas of revenue generation (merchandising, client acquisition, new product development) and efficiency improvements (employee engagement and process design) offer great areas to initiate your big data projects. These areas typically have long histories of benchmark data that will be key to creating momentum for the adoption and leverage of big data practices in the organization.