Our recent study entitled “Boom in Big Data Analytics” researched 436 companies with greater than $4B in revenues (Fortune 500) and found how analysis of both structured and contextual business information impacts customer management best practices. Business executives that actually utilize, recommend, influence, hold budget or veto power over customer management business processes and/or the purchase of customer management software and services reported double-digit return on investment is both tangible and real. Wouldn’t you want to know how they did this?
For starters, 89.6 percent of respondents cited the importance of customer recognition across multiple channels of engagement as “important and useful” or “critical for our business” in regards to analysis of customer behaviors such as:
- Transactional (purchase)
- Interactional (engagement) and
- Influence (probability to recommend products or influence others to purchase)
Figure 1: Business Intelligence & Customer Analytics: Importance of Multichannel Customer Recognition
Not surprisingly, the ability to analyze multiple sources of customer information fuels additional investment in business intelligence at these large enterprises. Eighty percent of respondents converged on the ability to “proactively uncover potential issues, make appropriate course corrections, resolve customer complaints before they escalate” and the “importance of customer recognition across multiple channels for customer management initiatives” as a high priority for investment as well as critical for overall business operations.According to our research, organizations overwhelmingly acknowledge that understanding a customer’s preference of interaction is key to driving relationships, and ultimately sales. Whether a company seeks to calculate customer risk, market-basket affinity value, annual customer profitability or customer lifetime value, performing that analysis accurately, and on a repeatable basis, requires information that typically streams from numerous sources (such as mobile device, social, online content) or resides in various business systems (such as CRM, ERP, ecommerce, SCM, data warehouse, third-party data).
Figure 2: Importance of Customer Recognition across Multiple Channels for Customer Management
A clear path to understanding and leveraging the intrinsic value of customer intelligence demands that companies exploit the enormous amount of multichannel information available to them by converting it into decision support and actionable insight. Is this a continuation of the democratization of business intelligence I called for in 2008? (See “Decision Science & Customer Analytics: Competitive Advantage or Competitive Necessity?”) Absolutely! Is business intelligence the same as big data analytics? Depends upon your business requirements and upon whom you consult!
Figure 3: Respondents Roles: Analysis of Big Data for Customer Management Initiatives
Stay tuned for more research insights and excerpts from “Big Boom in Big Data Analytics” in future SandHill.com articles. Is everyone there yet? Well, based on this latest research, a great deal of progress has been made. In the five years since we published Decision Science & Customer Analytics, more line-of-business executives are involved with, and even champion investment in technology. Their active participation is driven by the desire to realize the downstream business benefits of doing so. In fact, senior executives at the vice president to C-level comprised one-third of our respondents while more than another third (37.8 percent) included those at the director and manager level. Team leaders (14.6 percent) and team members or individual contributors (15 percent) contributed as well.
Leslie Ament, SVP of research & principal analyst at Hypatia Research Group, is a Customer Intelligence Management thought leader and analyst who focuses on how organizations capture, manage, analyze and apply actionable customer insight to improve customer management techniques, reduce operating expenses and accelerate corporate growth. Her coverage areas include CRM, Business Intelligence, Social Media Intelligence/Search/Text Analytics, Web Analytics, Marketing Automation & Customer Data Management/Data Quality. Ament has driven process requirements gathering implementation for both on-premises and SaaS CRM systems. Contact her at [email protected].