Not long ago, organizations engaged with customers by meeting them in person, speaking with them on the telephone or writing to them. To be competitive today, however, organizations cannot confine customer service to those forms of engagement. Customers now engage with each other and organizations through a variety of digital channels that include email, corporate websites, text messaging, instant messaging, social media, smartphone applications and video.
The importance of analytics for sales organizations is clear and, as I pointed out in my recent analyst perspective on the next generation of sales analytics, these capabilities optimize revenue potential. However, utilizing sales analytics requires a set of data skills that most organizations still find challenging and are thus not fully prepared to support. The efficient access and preparation of data underlies any analytics processes, which must meet demanding needs that are not always automated. Our research into next generation sales analytics has found many impediments that must be addressed and is a critical part of our expertise agenda for sales organizations.
Topics: Big Data, Sales, Machine Learning, Analytics, Cloud Computing, Product Information Management, Sales Performance Management, digital technology, Billing and Recurring Revenue, Digital Commerce, Sales and Operations Planning, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Collaboration for Business, Sales Planning and Analytics
Our benchmark research into next-generation contact centers in the cloud confirms what many others are writing and talking about – that customer experience is now the business differentiator. This means that organizations need to get customer engagement right at every touch point, be it assisted by employees or digital. The same research shows that while organizations are supporting more channels of engagement, many are struggling to integrate systems and engagement channels; fewer than half of companies can offer omnichannel experiences. Making matters worse, many of their employees don’t have the full range of skills needed to handle all channels and types of interactions. To overcome these challenges, organizations need a systems architecture that integrates assisted and digital channels, workforce optimization and other business applications such as CRM and multidimensional analytics. Several vendors are working to provide such a suite, most focusing on in-system integration of channels, WFO and analytics, and integration with third-party CRM systems.
Compensation management is essential for any organization that values engaging and retaining its employees. It is a fundamental component of a range of personnel-related activities – recruiting and hiring, assessing performance, and career and succession planning. Determining and providing appropriate compensation, which may involve base pay, merit pay, variable pay and incentives or bonuses, is equally important for all members of the workforce – full- or part-time employees, contingent or on-demand workers and contractors. Incentives are an important part of compensation. Business areas such as call centers, sales forces and field service frequently tie incentive compensation to performance objectives. Whatever the particulars, the effectiveness of compensation directly relates to the core challenge faced by human resources departments: keeping employees productive, satisfied and motivated.
Topics: Human Capital Management, Office of Finance, Learning Management, HRMS, total compensation management, Workforce Management, Work and Resource Management, ERP and Continuous Accounting, Payroll Optimization
Ever since I became involved in the CRM and customer service markets, everyone – businesses, vendors, consultants and analysts – has been talking and writing about the “360-degree view of the customer”. Despite claims from several vendors, I haven’t seen any products that produce a full 360-degree view, and user organizations haven’t had the time or resources to develop the technology themselves. As our research into next-generation customer analytics shows, the main issue is data – organizations have far more of it than most realize. The research shows that organizations on average use eight data sources as input to analytics, but there are more than 20 potential sources of customer-related data and the situation is getting worse. Beyond the sheer volume of it, data now comes in several forms – structured, unstructured (such as call recordings and text), event data (for example, video that customers download) and process data.