Assessing CX Using Multiple Data Sources

Assessing CX Using Multiple
Data Sources

New approaches to CX analytics in the world of expanding data and analytics.

As business leaders, employees and customers, we sense accelerating change everywhere. How can an organization ensure it is on the right trajectory for success? And where does CX fit in?


From then to now

A century ago, CX depended on informal relationships between store owners and their customers. In the 1950s, concepts around customer satisfaction began to emerge. Organizations measured satisfaction using mail surveys. They developed national and segment-specific indices by the 1970s. Other indices emerged to measure customer loyalty.

In the current century, CX Management became a core concept. The modes for gathering and measuring customer perceptions continued to evolve. We moved from mail surveys to mail and phone. We then shifted to email surveys, and in the last decade to survey by mobile phone, web, and social media.

We gather CX data more frequently too, especially for interaction- or event-based feedback. Automation, use of robots, and IoT devices enable us to track events, transactions and back end operations. The result is an astronomical growth of data. The emergence of new data sources is timely, because survey response rates have been declining, making them less representative of customer experience.

‘Big Data’ now dissects customer experience.

What’s left as a basis for competition is to execute your business with maximum efficiency and effectiveness, and to make the smartest decisions possible. And analytical competitors wring every last drop of value from business processes and key decisions.


Sophisticated analytics seek (1) to optimize business processes and (2) to make the best business decisions.

Tapping into sources of customer feedback – solicited or unsolicited – and customer behaviors lets us evaluate holistically. We can consider all organizational dimensions against a background of changing market forces. The data may be behavioral (operational, website), attitudinal (survey, social media, blogs, etc.), market, and financial. Execs can use it to grasp customer wants, product / service delivery relative to expectations, operational process efficiencies, and so on.

The many dimensions of an organization are interconnected and interdependent. We must analyze them that way. We must also go beyond linear relationships to the complex, intertwined fabric of the business. Specifically in relation to CX, customers expect consistency across all interactions. Leaders must implement actions that reflect the brand consistently across all channels and experiences.

Microsoft is a great example. Changes in business culture led to changes in business decisions. Microsoft’s market cap grew from $300 billion in February 2014 to over a trillion at the close of 2019.

“When we exercise a growth mindset by being customer-obsessed, diverse and inclusive and act as One Microsoft, that’s when we live our mission…”


Then what?

To what in the extent do marketers and consumers perceive brands as capable of delivering “an exceptional customer experience”? There is a marked mismatch. The gap ranges from 8% to 26%.

Source: eMarketer, March 2019

Consider the table above. Marketers and consumers diverge markedly in their perception of the quality of customer experience. We have to keep asking ourselves why.

Measuring CSAT or CX is not enough. Executives need to know the top three or four actions to take. CX analytics must yield insights, helping to identify customer needs and to prioritize actions. Decision makers need segmented insights linked to CX and financial outcomes.

We must also look wider, to understand economic and social behaviors. We are living through expanding sales and service channels, and through globalization. We have intricate networks of partnerships, and multiple media interactions. It is complex, and getting more so. Our models must incorporate the key components of this broader context. Then action planning can involve multiple initiatives across regions / channels. We thus ensure faster response times and create adaptive and flexible business processes.

“Companies that fail to adapt their people, processes, and products to this multiple-journey, multiple-experience environment will be left behind.”


Businesses define KPIs. Increasingly, they will monitor progress via dashboards and will adjust implementation to meet targets. Tracked metrics can be both ‘micro’ and ‘macro’, corresponding to implementation at different levels of the organization. Metrics must be specific and measured at appropriate intervals.

Data is burgeoning. The challenge is (1) to obtain data that is reliable, consistent and relevant; and (2) to find the nuggets most important to success. Achieving such results will require transformation of organizational culture. There must be gradual but steady enhancement of technological and analytical competency.

This evolution towards analytics program maturity is illustrated in the chart below. 

Source: OCX Cognition. Expected growth in workload sophistication and scale as an analytics program matures.

Initially, we have basic reporting. Then analysis grows in sophistication; ‘why?’ questions are tackled. Modeling starts, and with it the ability to predict outcomes. Next we shift reporting to ‘now’: machine learning means that customer status is always up to date, at least in predictive form. Then customer-event triggers make the system instantly responsive, so that resources shift to where we need them, when we need them.


In short

We need to move CX analysis from just surveys to the entire data architecture – in particular to operational and behavioral customer data. For this we need particular data and technology, because:

  • Automation, our digital world, use of robots (in manufacturing, warehousing, etc.), and IOT devices yield new data that captures client and customer experiences; and
  • Modern technical advances in data storage, computational power, and analytics software make it possible to analyze the ‘Big Data’ now to hand.

Crunching all the data will provide a more holistic view of the customer experience, far beyond what surveys alone can offer. We have decided to call this new measurement system Spectrum NPS.

Businesses need to be on this trajectory. Will your organization transform its culture and processes?


OCX Cognition delivers the future of NPS. We ensure customer experience success by combining technology and data science with programmatic consulting. In our Insights section, we present a comprehensive and evolving collection of resources based on our research and expertise, collected for CX leaders committed to delivering business outcomes.