Mark Smith's Analyst Perspectives

Having effective analytics enables businesses to understand far better than ever before the data they’re collecting, and to do so in greater volumes and more forms. These new capabilities are especially relevant to sales organizations. When applied to sales data, analytics can help sales teams achieve quotas and forecast more consistently, as well as understand the impacts of incentives and maximize the potential of territories, all of which help improve sales performance. These benefits provide the foundation for a business case to adopt analytics tools that generate information to guide actions and decision-making for sales organizations.

Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Internet of Things, Contact Center, Data, Information Management (IM), Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, AI and Machine Learning, subscription management, agent management

We now are well beyond the year depicted in 2001: A Space Odyssey, a cinematic perspective on the future of artificial intelligence in which HAL 9000, a computer, is able to simulate human behavior and control machines. Anyone reviewing the past two years of marketing around AI in the business technology industry can be forgiven for believing that we have arrived at the futuristic state Stanley Kubrick imagined. We have not.

Topics: Big Data, Data Science, Mobile, Customer Analytics, Customer Engagement, Customer Experience, Machine Learning, Mobile Technology, Wearable Computing, business intelligence, Analytics, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business

We are have arrived at the May 25, 2018 date when the European Union’s General Data Privacy Regulations (GDPR) become enforceable, following what has been a two-year transition period. Companies were given this time to put in place reasonable measures and the systems necessary to support the legislation’s wide-ranging personal data privacy requirements, which apply to any organization with more than 250 employees that serves EU citizens. While this regulation will apply in the EU, it has implications for any organization in the world that provides services involving the personal data of any EU citizen.

Topics: Big Data, Data Science, Mobile, Sales, Customer Analytics, Customer Engagement, Customer Experience, Marketing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Digital Technology, Digital Marketing, Digital Commerce, Cybersecurity, Billing and Recurring Revenue, collaboration for business, mobile marketing

Advancing the potential of any business requires continuous improvement in the processes and technology that support it. Many companies have embraced attempts at a digital transformation, and it’s become a goal to which organizational resources and budgets have been dedicated around the globe.

Topics: Big Data, Data Science, Mobile, Sales, Customer Analytics, Customer Engagement, Customer Experience, Human Capital Management, Machine Learning, Marketing, Marketing Performance Management, Mobile Technology, Office of Finance, Wearable Computing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Product Information Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Machine Learning and Cognitive Computing, Pricing and Promotion Management, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business

If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?

Topics: Big Data, Data Science, Mobile, Machine Learning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Digital Technology, Machine Learning and Cognitive Computing

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.

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.

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.

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.

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

Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus  away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.

Topics: Big Data, Data Science, Machine Learning, Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data Preparation, Internet of Things, Cognitive Computing, Information Optimization, Digital Technology, Cybersecurity