Customer Experience in 2013: The Promise of Big Data

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This blog series focuses on some trends and themes that I predict will have a great impact on the discipline of customer experience in 2013. In my last blog, I forecasted that we will continue to see great volatility in customer sentiment in 2013; this time, I want to focus my attention on a topic that is getting immense attention – big data.

“Big data” has become the buzz word du jour; like many buzz words, there seem to be different definitions of what this means, which results in different expectations on its impact. For purposes of this discussion, I would posit that “big data” relates to the collection and synchronization of disparate data sources with the intent of having a more holistic view of a system and its component parts. When looked at from this perspective, big data does not seem like such a radically new notion – after all, companies have always had customer lists, financial data, employee data, etc. The key point is on the notion of synchronization – in the past, most of these data sources were not able to talk to one another.

Big data reflects the realization of the promises of CRM – that is, firms can now not only look across a wide variety of data that is organized and linked in an efficient (if not complex) manner, but they can also begin to mine this data to reveal the underlying relationships that may not be evident to the casual observer. While I would offer that the full realization of CRM’s promise is yet to be achieved, we have certainly made great strides over the last decade.

How does this relate to the work of customer strategists? I would offer a few observations:

  • As more behavioral data become available, we have the ability to identify meaningful customer segments; this will be especially valuable in identifying cross-sell and upsell opportunities.
  • Linking survey-based data with behavioral data will become more the norm, not the exception. More emphasis will be placed on linking customer listening exercises to hard financial outcomes.
  • Having a mechanism and process by which we can understand the inter-relationships of various data provides greater opportunities – and more imperative – to take a more action-oriented analytic approach. Stated differently – analyses that do not focus on action (and business outcomes) will have little value in organizations.
  • The complexity of the data systems will require that customer strategists be skilled (or at least conversant) in the theory of data structures.
  • As the volume of transactional data grows, the opportunity (and demand) for sophisticated longitudinal analysis and/or complex predictive analytics will increase. Customer strategists will need to be not only more data-savvy, but also will need to be more skilled in the use of complex predictive analytics.

Big data represents a great opportunity for the customer experience industry; however, it will require customer experience professionals to evolve. Here are my recommendations for staying ahead of the curve:

Continue to learn – Being conversant in data structures and analytics are a must. Even more important is to be more comfortable and capable in dealing with financial concepts and models in order to link customer experience work back to business outcomes.

Build new relationships – Learning new skills does not necessarily mean going back to school; expanding your business network beyond the boundaries of customer experience to include IT and financial resources will provide go-to resources who can aid in your ongoing learning.

Be proactive – Look for ways to embrace big data before you are asked; doing so shows initiative, and will speak to your ability to think strategically.

How is big data impacting your organization? What advice would you offer to customer strategists? As always, I welcome your comments.

Mark A. Ratekin
Senior Vice President, Consulting Services

Republished with author's permission from original post.

Mark Ratekin
Mark is responsible for assisting clients in identifying and quantifying the financial linkage of their customer loyalty management programs. He plays an active role in translating program findings and conclusions into actionable recommendations and works with management and employees to facilitate the implementation of program findings into quality improvement strategies.

2 COMMENTS

  1. An interesting perspective on the impact of big data on customer experience. We have seen customers truly becoming the king in the digital space, and this trend will likely continue through 2013 and beyond. Big data can offer some strategic insights into consumer behavior, buying history and patterns, demographic/cultural preference, and so on.

    These can be a useful platform for building the right strategies that are in line with your customers’ needs and market demands. To know what’s working you must have the right analytics in place. To measure your performance you will need to implement a comprehensive measuring system, such as the Customer Effort Score (CES)–a measure of how much effort your customer is exerting to get an issue resolved, or buy a product/service through your online channels, etc. A high CES translates into lower customer experience and vice versa. You can read the post here:

    http://www.minacsblogs.com/CustomerRelationshipManagement/CustomerEffortScoreCESANewPerspectiveonCus.aspx

  2. Thanks, Mahima, for your comment. I agree – the proliferation of data will enable us to garner immense insight. A couple of keys occur to me – first, as customer strategists, we have to continue to stay “ahead of the curve” from a knowledge/technical perspective. The technology is changing rapidly and to extract the most utility from the data, we have to be adept at all the techniques at our disposal.

    Second, I’ve noticed that as things become more complex, the more we strive for simplicity – the emergence of NPS and CES are two examples. While simplicity is laudable, we need to make sure that we are using the right metric – CES, for example, would seem to be better aligned with a customer service/support function, while NPS tends to align better on B2C programs. The key, to your point, is to have the right metric and analytics aligned with the right activity (and, by extension, to be aware that there isn’t a one-size-fits-all approach).

    To be sure, it is an exciting time to be focused on customer strategies! Thanks again for your comment.

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