Customer relationship management is a $23 billion-plus business, and has enabled Salesforce.com (News - Alert) to become a software giant, generating sales of around $4.3 billion and growing at 20 percent. But despite all that, there’s still much debate about what CRM actually is, and what it will become. However, general consensus seems to indicate that CRM systems are evolving from databases that act as the systems of record on customer-related information to more dynamic solutions that can track customers during their entire lifecycles and across different communications channels, providing businesses with useful information along the way.
The CRM of the future will arm the enterprise “with real-time analytics that can calculate the needs and expectations of the customer, and match that to the potential benefit (profit and growth) that will ensue from an engagement,” Gartner (News - Alert) analyst Michael Maoz recently blogged. In a recent interview with me, Maoz explained that real-time analytics is already in use by airlines, hotels, and telecommunications companies, all of which use complex algorithms in their contact centers; by companies to manage their field repair workforces; in supply chain applications, so businesses don’t run out of inventory; and in the world of finance for things like credit scoring and mortgage approvals. And now, he says, real-time analytics is coming to customer relationship management.
Data-driven insights based on available data can result in 23 greater likelihood of customer acquisition, six times greater chance of customer retention, and 19 times greater possibility of profitability, according to McKinsey Global Institute, which in late 2014 said the analytics market is worth $38 billion.
This marrying of CRM and real-time analytics will enable a wide array of new scenarios, but Maoz of Gartner offered as one example the ability for a bank or an insurance company to see that one of its customers has a college-aged child who is leaving the region to attend college, and to identify that opportunity and then offer that customer a special bank service or an insurance policy (since the child will no longer be covered under the existing policy in the new region) to address that new life experience. A company called Personetics is already supporting this kind of thing for the banking industry, Maoz noted.
Salesforce, the leader in CRM software, clearly recognizes the importance of analytics to customer relationship management, as it has at least 20 analytics partners in its ecosystem. The next step, Maoz said, is for Salesforce to build an analytics platform, which he said it’s already doing.
Indeed, Salesforce in October 2014 introduced an analytics cloud solution called Wave, which was designed to help businesses review, get insights from, and act on any kind of data from any device. Users can interact with data via charts, dashboards, and other views that enable them to customize and filter data as desired.
Personalization via analytics was also a key theme Microsoft (News - Alert) discussed late last year when it made Dynamics CRM 2016 generally available. Microsoft Dynamics CRM General Manager Jujhar Singh in a Nov. 30 blog wrote the new release is the group’s most comprehensive one ever and represents a huge leap forward in its journey to deliver intelligent customer engagement.
That effort, he added, will bring the advanced analytics and machine learning capabilities of the Cortana Analytics Suite to allow for intelligent selling, with cross-sell recommendations so sales reps can predict which products and services a customer will need during the sales cycle; intelligent customer service, with knowledge articles recommendations to empower service agents with answers to questions so they can more effectively resolve customer cases and solve problems; intelligent social with machine learning capabilities powering sentiment analysis, as well as the ability to process significant streams of data to detect social posts that are most likely to be customer service cases or new leads; and intelligent collaboration with Delve functionality to surface trending content that is most relevant to what a person is working on.
“Our strategy is clear: to enable organizations to personalize customer experiences – engaging customers at the right time, in the right place and with the right content; to give them the tools to be more proactive, and to empower them with the intelligence to be able to predict trends and identify patterns -- to know what the customer needs and wants before they do,” Singh added.
SugarCRM, a rapidly growing pure play CRM company, has also been talking a lot about the need to better understand customers and take actions based on that information. In fact, in April SugarCRM announced it had combined customer journey mapping with CRM, and in May the company launched the i2i Customer Journey Workshop series, during which industry author and speaker Phil Winters presented strategies companies can take to break down customer journeys and identify key points of engagement along the way.
“What matters most is customer engagement,” SugarCRM CEO Larry Augustin (News - Alert) said last spring during these announcements. “A solid CRM platform needs to function as the engine that drives and orchestrates that engagement.”
And a December blog in which SugarCRM’s Head of Product Evangelism Martin Schneider presented “5 CRM Predictions for 2016” lists personalized analytics as No. 2, just behind user experience.
“Predictive analytics will be the next big data trend, and soon salespeople and marketers will use predictive analytics to forecast the impact of their activity and provide more personalized pitches or content to individual customers,” writes Schneider. “Modern CRM applications are beginning to provide greater analytics for the individual user. Nimble (News - Alert), and consumable tools will be embedded into CRM and provide sales, marketing, and support professionals with customer preferences and history, helping them engage throughout the customer journey. CRM is moving toward systems of engagement that use predictive analytics to cut through the big data noise to uncover actionable customer insights.”
Edited by Kyle Piscioniere