It's Time to Redefine the "R" in CRM
By J T Kostman, Chief Data Officer, Time
To say that Edgar Codd changed the world of commerce might be an understatement. While working at IBM's San Jose Research Laboratory in the 1970s, this unsung hero of modern mercantilism invented the relational model for database management—and in so doing, planted the seeds for SQL, Oracle, DB2, SAP, Teradata and a host of similar systems that introduced a new way for organizations to conduct business. In establishing the Relational Database Management System (RDBMS) approach, Codd provided the world with more than a new technology. He introduced a new mindset.
"If we truly want a relationship with our customers, we must do more than check off times and types of purchases, visits and clicks"
RDBMS thinking has, at its core, the notion of relations—which, according to the Oxford English Dictionary is defined as “The way in which two or more concepts, objects or people are connected or the state of being connected.” This notion is so fundamental to RDBMS that Codd began the baker’s dozen of his Twelve Rules with Rule 0:
“A relational database management system must manage its stored data using only its relational capabilities. The system must qualify as relational, as a database and as a management system. For a system to qualify as a relational database management system (RDBMS), that system must use its relational facilities (exclusively) to manage the database.”
As effective as the RDBMS approach has been, it may be in this very definition that we find a serious, if not fatal, flaw in how we have come to define Customer Relationship Management (CRM).
Thus Spoke Zarathustra
In establishing the RDBMS mindset, Codd paved the way for decades of otherwise impossible capabilities, efficiencies and extensible technologies. HRIS, with its capacity to better understand and track HR activities and process transactions electronically, has certainly proven to be a boon; RDBMS applications in accounting have similarly saved millions of hours of labor. Yet when it comes to CRM, the promise too often fails to live up to its full potential.
A report from Gartner in 2013 estimated that more than $2 billion had been spent on CRM software that is not being used. Research firm CSO Insights similarly found that less than 40 percent of 1,275 participating companies had end-user adoption rates above 90 percent, and according to a cover story in BtoB, many corporations only use CRM systems on a “partial or fragmented basis.” The all-knowing oracle of Wikipedia likewise reports: “In a 2007 survey from the UK, four-fifths of senior executives reported that their biggest challenge is getting their staff to use the systems they had installed” and “43 percent of respondents said they use less than
The dismal performance of CRM in so many organizations led Graham Hinde, a manager at Business & Decision UK, to lament that “despite all this effort and investment [in CRM], it is hard to discern a noticeable increase in consumer attachment to the companies such as financial services or utility providers who have invested most heavily. Something appears to have gone wrong along the way; could it be that the basic foundations of CRM are flawed?”
The question we are left with is why the RDBMS, which has proven so profitable in countless other areas of business, is so often sub-optimally effective when it comes to CRM. The answer, as with most IT solutions, comes from the mistake of focusing on the technology—and not the use case. When it comes to CRM, defining our terms, and in particular what we mean by a Relationship should be a critical first step.
Returning to our friends at OED, the Dons at Oxford offer an alternative definition of Relationship to the one relied on by Codd, a definition that appears considerably more salient when it comes to CRM:
“Relationship: The way in which two or more people or organizations regard and behave toward each other.” It is this much more humanistic definition of relationships, I would argue, to which we must aspire if we are truly interested in serving our customer’s needs—and not merely efficiently transact business with them.
As with all human relationships, the B2C relationship must be grounded in communication and in caring about who our customers really are and what they really want. While attributional research (surveys, focus groups and interviews) can certainly help enrich those understandings, it is through gathering information about the overt and implicit behaviors that demonstrate what our customers truly care about. It enables us to transcend the insights afforded by merely focusing on the transactional aspects of our interactions with them. When Hyatt Hotels marry a record of which paper I prefer in the morning to the comments I have made on my various stays—and then ties that data to records of how often I use which amenities, the typical cadence and duration of my visits, and which restaurant recommendations my colleagues and I prefer—and then integrates this information with the billions of bits and bytes of the digital trail I leave in my wake as I visit various Hyatt properties around the globe, Hyatt gets to know me. In so doing, they ensure my Diamond status is unlikely to ever lapse.
In short, if we truly want a relationship with our customers, we must do more than check off times and types of purchases, visits and clicks; we need to concern ourselves with who they are, what they want, what they do and what (and whom) they care about most deeply.
A New Paradigm for Relationships
Big Data, Advanced Analytics and NoSQL databases offer more than just a way to contend with the volume, variety and velocity of the torrents of customer data we now have access to. They also offer us a new way of understanding that data–and, by extension, our customers.
Hadoop enables organizations to move beyond transactional data and focus on the nuances of behavior that would otherwise be inaccessible. Graphical databases, like Neo4j, allow us to examine relationships in the most meaningful sense: between people, entities, places and preferences. Social Network Analysis provides a means for better understanding and appreciating the evolving and dynamic interplay between our customers and their connections; while Cassandra allows for an examination of behavior in context over time. Who would have thought a few short years ago that the recommender systems enabled by Machine Learning and Mahout would give us an ability to anticipate, understand and serve our customers’ needs so much more effectively.
By munging multiple sources of data and working in symbiotic collaboration with our advertisers, we are able to leverage this new mindset to provide organizations across a wide-range of industries with insights into their own customers that often transcend what would have been possible on their own. When we incorporate their messages with compelling content, we are more effectively able to ensure that they are providing the right message to the right person at the right time in the right context. Perhaps even more importantly, by breaking free of a pure RDBMS perspective, we are helping our partners strengthen their client relationships in deeper, more rewarding ways. And at the end of the day, that’s not just a more humane way to do business. It’s good business.