Integrating Customer Analytics is the Next Step to Increase the Value of All Business Analytics

Today’s successful “modern experience” business runs on analytics. This fact-based approach to operations enables the business to identify issues and opportunities more quickly and precisely—and address them more effectively. And as businesses move from their first generation of analytic activities to their second, one of the most important projects during the transition is the incorporation of additional customer data sources. This means a change in the analytics practice to a customer analytics focus, instead of channel-specific or application-specific data analyzed in silos.

According to Nate Smith, Head of Product Marketing Analytics at Adobe, this has two benefits.

“It provides more input into your analysis and models at a customer profile level, giving you a high-resolution view of your customers and how they engage with your brand,” he says. “Then, by utilizing more precise insights in a customer-journey context, brands can significantly maximize customer satisfaction and revenue by delivering relevant, compelling experiences in moments that matter. Brands are learning that customer insights have a shelf life that is increasingly getting shorter based on ever-changing consumer expectations.”

Customer-based analytics has unique aspects that make it particularly valuable. Perhaps the most important is that it generally delivers a truly external perspective. It provides the critical “voice of the customer” information that internally derived data doesn’t. In addition, there is often highly valuable competitive information available when a customer engages with one brand but buys another. Understanding why a customer didn’t buy is as valuable as understanding why they did.

Gaining deeper insights

One operational group that can truly benefit from analyses infused with customer analytics is product management. For example, if the customer data makes it clear which features are most commonly the first choice for sorting, or what filters are used to identify a subset of products from the whole line, product marketing teams can gain deeper insight into feature priority. Findings from customer analytics also enables product management to evaluate these criteria for different customer segments, delivering even more value.

Sales can benefit by adding more details about how fast customers buy, what the purchase catalyst is, or how long customers research before they’re open to a sales call. Delivering more information that details what happens before the sales cycle starts will help improve analyses focused on revenue generation.

There are many more examples of how customer analytics can enhance broader corporate analytics. However, to complete the integration of this data successfully, there are some important considerations that must be included in the marketing database technology stack.

“In a word, interoperability,” says Adobe’s Smith. “When an organization prioritizes customer experience management, it’s important that the underlying data store be maintained as a system of record for customer data. This means it has to be interoperable in real time with other data-collection systems to truly deliver on the promise of customer analytics solutions.”

The simple truth is that more data from relevant sources makes for better analyses and better results. Most companies started by using the internal data stored in core business applications. That worked well for the “analytics 1.0” phase. To increase the value of analytics and enhance the benefits to the business, integrating new data is mandatory. And the most valuable new data source for many companies is information from customer analytics.

This integration requires two ingredients: the right technology that speeds and simplifies integration, and the creativity to find new ways for other functional areas to tap the voice of the customer to improve their plans and operations.

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