Monday, October 21, 2013
CMOs- How Data Mining Can Help Your CRM Programs Succeed
If you’re a CMO and you don’t think your company should invest in data mining for your CRM programs, think again. As a CMO, you know a successful CRM program contributes to your company's bottom line growth. The two foundations for successful CRM are customer data and powerful analytics. As a graduate student with a concentration in marketing analytics, I have been looking at strategic customer management throughout my graduate courses. I have found two articles providing valuable insights in how CMOs can help their CRM programs succeed through data mining and advanced analytics.
In the article “Data Mining for Advanced Customer Management”, Beatriz Sanz Saiz, Ernst & Young's Global Customer Leader, believes that the transformation from product-centric to customer-centric commercial strategies is an unstoppable trend. She points out that though most CMOs are aware of the importance of big data, many companies are data-rich but insight poor due to their lack of understanding of customers. Strategic customer segmentation is the starting point of driving customer insights, which not only provides descriptive analysis but also the “so what” and future prediction. Traditional segmentation schemes may only focus on the contribution a customer has made, but Sanz Saiz points out that strategic customer segmentation breaks down a customer’s total value into present and potential value. This prediction of customer evolution can guide different commercial strategies to divest underperforming customers or to move customers with great potential up the value chain.
In “Real-Time CRM To Maximize Your Customer Lifetime Value”, Chris Diener, Senior Vice President of AbsoluData Analytics, says that some CMOs are missing great marketing opportunities because “they’re not incorporating real-time flow into models and applications”, partly because some CMOs hesitate to invest in data management system and data mining. He holds the same opinion as Sanz Saiz that Customer Lifetime Value (CLV) provides a clear vision for a company’s CRM program, because knowing your customers’ CLV helps you to build strategic plans to increase customer loyalty and brand value down the road. Diener also suggests CMOs to “build a more social and emotional bond with your customers” by tapping into real-time big data, including valuable data from social media.
Despite the technical nature of data mining, it requires strategic thinking and prioritization from the C-suites. Based on the reviews of these two articles and my related course at Northwestern University, there are three things CMOs need to do in order to help their companies succeed in the “big data” era.
1) Break the silo.
CMOs must determine the right information to collect and break the information silos between marketing and IT departments. This may require organizational and system investments.
2) Offer analytics team C-level support and mandate.
CMOs should support their analytics team to implement strategic customer segmentation schemes, which evaluate the customer lifetime value to guide future CRM strategies. CMOs play the key role in combining marketing analytics, insights, and big data, including social media and digital data.
3) It’s all about real-time.
In this “big data era”, identifying customers at different touch points and offering personalized services and communication messages are the key factors of a successful CRM program. CMOs need to think and act real-time by tapping into real-time data to arrive at valuable business insights for their CRM programs.
Yi Zhang is a MS Candidate in Integrated Marketing Communications at Northwestern University, specializing in Marketing Analytics. Follow her on Twitter @Yi_Zhang12