Customer Analytics

Recommended Read: Optimize Customer Experience with Digital Intelligence

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Customers today demand a great experience – myself included. I recently switched my coffee allegiance to Starbucks based purely on the fabulousness of their mobile app. Truth be told, I like the competition’s coffee better. But the Starbucks mobile app is the bomb! They know me. They know where I am. They remember what I ordered. With a single click I can place my order on my mobile device, bypass the line and pick it up in the store. And, every so often, based on how much I’ve purchased from them, they let me order absolutely anything I want for free, which in my case is a quadruple shot, Venti, iced latte. Short of drones delivering coffee directly to my doorstep, Starbucks couldn’t possibly make this easier or more delightful for me. While most brands still struggle to make data actionable, some are succeeding wildly at harnessing data and delivering engaging experiences across all channels.

This is all enabled by customer analytics, a topic I’m pretty passionate about. I am a voracious reader on the topic of analytics and customer experience and each day I learn something new.

One of the more interesting reads I’ve encountered is Optimize Customer Experiences with Digital Intelligence, a report by James McCormick and Cinny Little of Forrester Research. In this report, McCormick and Little set out the analytics practices businesses must follow to truly understand their customers and thrive in today’s digital environment.

One passage from the February 2016 report really resonated with me:

“To conduct multichannel digital analysis, digital intelligence incorporates customer data management capabilities across a broad range of data types. This includes melding interaction and behavioral data across all digital and offline channels with customer data and business data such as financial and product information. This enriched data set must feed advanced analytics and annotation capabilities for power users, non-technical users, and business stakeholders alike. To be effective, role-relevant analytics user interfaces must provide persona-appropriate self-service functionality.”

There are really two points in here. One is about data integration. Brands need an easy approach to data integration so they can see the entire customer journey and connect experiences across touch points. As evidenced by my example with Starbucks, the brands that customers LOVE have the ability to connect data and experiences. I can order online or through mobile and pick my order up in store.

The second point is around having role-relevant analytics available to business users in a self-service model. The typical model today is that the business user asks a question, the analyst comes back with a report, the business user asks a follow up question, and so on. There’s too much latency built into this model and it impedes timely action.

IBM Customer Experience Analytics addresses both these needs. We simplify the process of connecting data from across the customer so you can see the entire picture. And the same mechanism – IBM Universal Behavior Exchange  – that enables us to report on the entire journey also enables brands to use data from any point, in any point—just like Starbucks is able to seamlessly connect my mobile, web and in-store experiences.

IBM Customer Experience Analytics also makes it easy for the business user to get access to the information they need with role-based dashboards. Business users can drill in from the dashboard to investigate trends and uncover root causes. And, because all roles are working off a common source of customer data, everyone has a common view of the customer.

I invite you to download and read Optimize Customer Experience with Digital Intelligence by Forrester.
 Once you do, think about how your digital analytics needs have evolved and learn more about IBM Customer Experience Analytics at

Program Leader, Product Marketing, Customer Analytics, IBM

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