Manish Sood, CEO & Founder, Reltio
Forbes Technology Council
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Published in Forbes at https://www.forbes.com/sites/forbestechcouncil/2018/12/07/a-new-lens-into-the-customer-360-view/.
Customer 360 is a practice that involves gaining a comprehensive view of customer behaviors and preferences by aggregating data from all sources, including multichannel touch points, between a customer and a business entity. The idea is so simple and yet, so grand, so obvious and, in this multichannel operating environment, so necessary. Unfortunately, it’s also highly elusive — in fact, some industry insiders consider it an unattainable goal. But maybe there’s hope yet if companies are willing to do things a little differently.
First, consider a few recent events. In September, several major corporations — Adobe, Microsoft and SAP — launched the Open Data Initiative (ODI). The goal is understandably grand: The companies plan nothing less than “reimagining customer experience management (CXM) by empowering companies to derive more value from their data and deliver world-class customer experiences in real-time.” As any IT executive can attest, the whole point of data-driven initiatives is to free data from internal silos; the ODI effort wants to push disparate data streams, from transactional to IoT, in and out of public clouds, and spark new kinds of application development that natively build on relationships and other variations of context.
Then just a few days later, Salesforce released Customer 360, which is billed as a new way to connect Salesforce apps through a single Customer ID, and “deliver unified cross-channel customer experiences.” The company says it wants to go beyond an “app- or department-specific view of each customer” and create, essentially, a single profile to inform every interaction. Among other objectives, the Salesforce initiative offers a simple user interface for app and data management and “reconciled 360 ID and profiles across different applications,” along with off-the-shelf packages for different functions.
In my opinion, this is all great news, and companies should actively adopt both initiatives. Any strategy to get data out of silos and into the operating mix is a smart move, and benefits the entire ecosystem. However, I think it’s also important to remember that there have been similar efforts in the past, and we can charitably say that many have fallen short. There are many reasons for this, but here’s the topline issue: Even the most sophisticated CRM applications can’t create a true Customer 360 view — they’re not designed to, and traditional master data management (MDM) solutions don’t fit the bill either, leaving many essential components, such as interactions and relationships, out of the question.
CRM apps are typically built on legacy relational data models, which are not suited to be a single source of truth of customer data across all enterprise applications. They’re unable to capture complex real-world relationships — the kind we’ve become accustomed to in, say, graph-powered applications such as LinkedIn and Facebook. Meanwhile, MDM-only tools leave the transactions and insights to other systems and can be both costly and complex.
Ultimately, I believe data reconciliation of stand-alone customer profiles is noble but insufficient. We must understand relationships across more than just the customer domain. We must incorporate the customer’s relationship with other entities such as products, stores, locations and households. In my experience, the single most important factor is context — not just customer data but a larger perspective that encompasses broader profiles on customers, relationships and insights. Enterprises that want to benefit from a true customer 360 solution need to unlock the value of data relationships inside their operating models, and that means customers, households, stores, locations, products, parts, suppliers and more.
No one claims this will be easy. A data model that is both open and extensible, and enables and supports a broad partner ecosystem, involves serious challenges. I believe we need a new generation of technologies to extract specific data components from disparate sources.
And if that doesn’t seem difficult enough, let’s set the bar even higher: The process cannot be static. In this era of artificial intelligence and machine learning, and emerging regulatory needs such as GDPR, the data quality must undergo continuous improvement.
In other words, for a true Customer 360 experience, we need to simultaneously support not only new apps that operate with emerging data sources but also the legacy systems that reside in distinct customer silos. That’s primarily why companies would be unwise to bet exclusively on any one of the new options — they need data management technologies that are agile and scalable enough to keep pace with evolving business needs and changing business environments.
Bottom line: Rather than a single, magical solution, the mandate here is for a comprehensive approach that not only builds on MDM offerings but also extracts data from emerging data sources and, of course, integrates AI and machine learning to ensure continuous enhancement. It sounds like a lot, and it is. A holistic data management strategy encompasses a broad base of priorities: operational, analytics, compliance and more. An optimal modern data management platform organizes data from all current and future sources, infuses intelligence and enables the execution of the holistic data strategy. Those are sure to emerge.
Despite all the obstacles, the allure of customer 360 — a truly comprehensive view that can guide many business initiatives — is undeniable. The hard work needed to get there is definitely worth it.
Manish is CEO of Reltio. During his career, he’s architected the most successful data management solutions used by Fortune 100 companies.