The definition of customer experience continues to expand to include a broader set of touch points over broader interaction timeframes. Customer experience is less a singular event vs a journey with multiple touch points over the lifecycle of the customer. That’s the notion. Getting your arms around the customer journey means connecting lots of dots to understand customer voice and intent.
To date, those dots have been siloed across multiple data stores and multiple analytics engines – speech, desktop, text, surveys, etc. And across various channels and sources – web, social media, IVR, email, contact centers, retail outlets, etc.
Cross-channel analytics, or customer experience analytics, stitches the data together across these channels. The ability to centralize the storage and analysis of data regardless of source. The ability to normalize data to accurately correlate who made contact, where, when, how frequently, and most importantly, for what (the same or different) reasons. The challenge is compounded as companies try to puzzle together structured and unstructured data from multiple locations, various outsourced providers, incompatible system platforms, and inconsistent data models. From Enkata’s perspective, this key challenge is resolved by moving much of the data and analysis into the cloud.
A recent survey conducted by the Temkin Group provides insights into the current state of Customer Experience Metrics – “State of CX Metrics, 2011”. A good read. 210 corporations surveyed. Among other insights, the report highlights the need to effectively measure the customer experience across the lifecycle of the customer. And points out that there’s work to be done.
http://www.temkingroup.com/news/report-state-of-cx-metrics-2011
Any process or set of tools to improve upon the customer experience requires some fundamental components. Challenging stuff.
- Capture the data – structured, unstructured, voice, text, desktop, transactional,
temporal, behavioral - Correlate data – normalize it, analyze it, package and present it
- Measure the experience–track it in a useable, operational metric–translate it to
good experience / bad experience - Act upon the data–improve the metric/experience
- Build it into a continuous improvement cycle
The good news? The bits and pieces have come together. We’re now able to consolidate the data in the cloud, analyze it across multiple analytics engines dependent on the data form factor, and present it as next best actions for systematic improvements. Customer Experience Analytics has come of age. I look forward to reviewing the Temkin Group CX Metrics report in years to come to measure how we’re all progressing.