Customer data without integration is hardly data at all

Understanding customers has long been the Holy Grail for businesses leaders across industries. The unrelenting quest to know what they want, how they want it, and even when they might want it promises untold selling and marketing power.

We live in the powerful age of big data, where predictive analytics and all their spoils drive modern business and IT investment. Companies look to rip pages from Facebook (“People you may know”), Amazon (“Customers who bought this item also bought”), and Netflix (“You might also like”) in an attempt to understand (and successfully predict) customers’ wants and needs even before they do.

B2B companies also want in on these types of insights, and it’s why quality customer data integration, the process of consolidating and managing customer information from all available sources showing promise in consumer-facing industries, is picking up steam as businesses across industries strive to offer world-class customer experiences.

The key component of all this is visibility, and in its simplest form, improved data quality for downstream reporting. Clearer visibility into customer information across the entire enterprise means organizations can better serve those customers and grow their business.

But if obtaining such transparency were easy, organizations wouldn’t constantly strive to achieve it.

An integrated data-driven view of a customer base, critical for companies’ growth, is the key to unlocking this value, but customer data can be a challenge to collect and integrate into a usable asset in today’s multi-enterprise ecosystem.

Customer contact data, sales history, and marketing-generated interactions, such as survey responses, website visits, and social media engagements, help comprise that view. But the disparate, silo-ed applications, departments, and people that collect and store these interactions have kept organizations’ best integration efforts at bay.

Consider all the places a B2B company, whose customers are essentially other companies, might have to mine for so-called customer data. These include:

All of these tools are inherently dissociative and don’t naturally communicate with one another. Enterprises have previously relied on point integration technology for specific use cases, but that’s a tough sell today as organizations look to eliminate single points of failure from their architectures.