More than a year ago I wrote from personal experience about the challenges our firm encountered with Salesforce’s cloud computing systems and customer service and if we can trust them for business in the cloud. That perspective covered a range of issues that the behemoth cloud computing applications and platform company is facing regarding its service and technology. While Salesforce has shifted its customers like us and others to a different cloud computing environment, as it did in moving us off its #NA14 cloud computing instance, core challenges of its customer experience and billing processes persist. After the last customer experience incident, I contacted its executives about the need for operational improvement; it was clear in the dialogue that they saw some but not all of our experience as issues important to improving its customer processes. It was good to get some immediate attention, but my hope was to speak for all SMB companies in pointing out the importance of effective communications and escalating notifications and interactions when those customer moments go sour, so the customer isn’t forced to turn to social media to be heard. This was an area where Salesforce had significant room for improvement in customer engagement, reflecting a pattern we see in our benchmark research, which finds the most common challenges in almost half of organizations are integration of channels of engagement and managing activities as silos.
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Topics:
Big Data,
Sales,
Office of Finance,
Analytics,
Cloud Computing,
Collaboration,
Product Information Management,
Sales Performance Management,
Digital Commerce,
Sales and Operations Planning,
Machine Learning and Cognitive Computing,
Sales Enablement and Execution,
Machine Learning Digital Technology,
Sales Planning and Analytics
Our firm regularly explores the impacts of new technologies on business. Analytics is foremost among recently emerging technologies, which our benchmark research consistently confirms. In our research on next-generation sales analytics, fourth-fifths (82%) of participating organizations cited analytics as the most important technology trend for sales; however, several other technologies also are adding power and flexibility to the use of sales analytics.
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Topics:
Big Data,
Sales,
Mobile Technology,
Office of Finance,
Analytics,
Cloud Computing,
Collaboration,
Product Information Management,
Sales Performance Management,
Digital Commerce,
Machine Learning and Cognitive Computing,
Sales Enablement and Execution,
Machine Learning Digital Technology,
Sales Planning and Analytics
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.
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Topics:
Big Data,
Sales,
Machine Learning,
Office of Finance,
Analytics,
Cloud Computing,
Collaboration,
Product Information Management,
Sales Performance Management,
digital technology,
Digital Commerce,
Sales and Operations Planning,
Machine Learning and Cognitive Computing,
Sales Enablement and Execution,
Sales Planning and Analytics
I have been following advances in sales analytics since the 1990s. Over the last five years, however, I have seen evolution, not innovation. In most cases the information that analytics provides is too complicated and not contextualized enough for sales people who are not analytics experts to understand, let alone take action on. As I pointed out in my 2017 research agenda on sales, analytics is essential for planning that improves the impacts of sales efforts and meets the goals of the organization.
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Topics:
Big Data,
Sales,
Office of Finance,
Analytics,
Cloud Computing,
Collaboration,
Product Information Management,
Sales Performance Management,
Digital Commerce,
Sales and Operations Planning,
Machine Learning and Cognitive Computing,
Sales Enablement and Execution,
Machine Learning Digital Technology,
Sales Planning and Analytics
I am happy to provide my personal perspective on the potential of sales organizations, processes and technology to supercharge business activity in 2017. The sales processes of organizations – whether they involve digital commerce or direct or indirect physical selling – should be part of continuous optimization efforts to reach maximum results. To do this, the people leading and running sales processes must be able to use technology that supports their responsibilities and analyzes the crucial information coming into the business. For almost 15 years, we have advocated for sales applications and tools that are necessary to optimize sales effectiveness and improve the outcomes of their sales efforts. The available portfolio is much larger than sales force automation (SFA) and involves more than the continued use of CRM, which has clear limits in its ability to manage customer relationships. The applications on offer include many facets of sales: coaching, compensation management, contract management, configure price quote (CPQ), forecasting, quota and territory management, planning and optimization, pricing and revenue optimization, and target or market intelligence. New applications designed for sales also enable digital effectiveness that can transform organizations. Let me provide my perspective on six topics that are shaping the way sales can and should operate in 2017, and which are part of our sales research agenda for the year.
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Topics:
Big Data,
Sales,
Machine Learning,
Mobile Technology,
Office of Finance,
Analytics,
Cloud Computing,
Collaboration,
Product Information Management,
Sales Performance Management,
digital technology,
Digital Commerce,
Operations & Supply Chain,
Sales and Operations Planning,
Machine Learning and Cognitive Computing,
Sales Enablement and Execution
