Social media analytics is a powerful tool for uncovering customer sentiment dispersed across countless online sources. Though, analytics allow marketers to identify sentiment and identify trends in order to accommodate the customer better, always aiming to collect bundled information with web tracking techniques to derive management decisions for the overall corporate strategy.
With a lot of success stories available in the business environment, of which we will definitely present a few in the coming weeks, academic research projects have started to investigate the use of social data streams by analyzing and explaining circadian, daily or seasonal emotional patterns turning up in a population.
I recently read the blog “Data analysis should be a social event” of Judy Bayer and Marie Taillard on the Harvard Business Review portal which caught my attention because it tackles the common marketing issue of how to retain customers. The two authors came up with different scenarios of how analysts could approach the problem, claiming: “Depending on a company’s corporate analytics culture and the experience of its analytical team, experts treat customer retention as either a highly structured problem to be solved formally, which means finding the best algorithms to apply to the data found, or taking on a more sophisticated approach.” They also blogged: “More experienced analysts will take a broader view of the retention issue. Rather than framing the challenge as one of building a better churn model, they will look to improve their understanding of the customers behind the data.”ÂÂ
The authors say that although both approaches clearly deliver value, companies that don't explore the social aspects of analytics are missing out on opportunities to use data that could completely transform their businesses.
Pointing out that a lot has been written about analysts as storytellers and about creativity as part of the analytical process, they emphasize that it hasn’t really been explored if the storytelling analyst actively participates in co-creating value with others. “Psychologists believe that creativity flourishes in social contexts, as thoughts are translated into words, objects or images and in turn reformulated into ideas.” By the way, that’s one of the reasons why visualization of data is so valuable.
On the management side, there is increasing evidence that co-creative processes, involving consumers and other stakeholders, can have a transformative effect on key processes such as new product development, Bayer and Taillard explain, before describing how data analysis works in detail: “You put together ad-hoc teams that involve not only analysts with relevant domain expertise but also represent skills from other domains, that brings new ways of thinking to old analytical problems. Over a short two or three day period the team will brainstorm around the problem involved and bring together as much data and as many analytical frameworks as they can to both frame up the problem and outline potential solutions or at least pathways to solutions.”
Recently, both authors participated in a data-dive type process at a major telecommunications company that like many telcos was trying to woo customers through customized marketing communications and offers. A team, made up of analysts, business intelligence people from the operator and some external consultants, identified and applied an analytical methodology from the retail industry to quickly assess the needs and preferences of thousands of actual and potential customers. They built on these assessments to create thirty outstandingly targeted marketing campaigns. Two-thirds of these were successful beyond the company's wildest hopes, and what makes it even more impressive is the fact that all this came from just three days of group brainstorming.
“As with other co-creative processes, co-creative analytics comes with risks that must be mitigated through providing strong leadership and specifying clear deadlines and outcomes. But the fruits of the creative energy that you can unleash through teaming analysts and domain experts in these ways more than justify the investment of time and money involved”, the two ladies conclude.
By Daniela La Marca