I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.
Ventana Research recently announced its 2020 research agenda for data, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value and improve business outcomes. Data volumes continue to grow while data latency requirements continue to shrink. Meanwhile, virtually every organization is confronting a need for good data governance.
For interactions with customers to go well, organizations must manage an ever-increasing array of engagement channels. Our research finds that organizations expect to see interaction volumes increase on all channels, especially digital ones such as text-based messaging, chat, mobile and social apps. Unfortunately, the systems that manage these channels are typically disparate and uncoordinated and may not use the same underlying technology. This makes it difficult for organizations to coordinate customer interactions consistently and provide the best possible customer experience.
Topics: Customer Experience, Voice of the Customer, business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, AI and Machine Learning, subscription management, agent management, extended reality
Using customer analytics effectively involves several challenges. Organizations must make it a business priority, cultivate leadership and set a course for ensuring data and analytics are being processed and governed effectively. But effectiveness also requires technology that will assist in the effective operations and management of customers and help an organization achieve its goals.
Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, Conversational Computing, AI and Machine Learning, collaborative computing, mobile computing, subscription management, agent management, extended reality
Configure, price and quote (CPQ) software has been around for decades. Lately, I’ve been using the term “Dynamic CPQ” to apply to a variant of this software category that explicitly aims to produce a quote that optimizes the trade-off between the profitability of a deal and the probability of closing a sale. Dynamic CPQ software is a hybrid of price and revenue optimization (PRO) software and CPQ, providing companies with the ability to better execute their market share and pricing strategies. It’s designed especially for business-to-business (B2B) relationships that involve sales agents in the pricing process.
Topics: Customer Experience, Office of Finance, Data Preparation, Information Management, Sales Performance Management, Financial Performance Management, Price and Revenue Management, robotic finance, revenue and lease accounting, sales enablement