A group of people conversing about collected data in their workspace

Companies that have seen a positive revenue growth collect more customer experience (CX) data than other non-growth companies, according to a recent survey by Gartner The survey found that nearly 80% of growth organizations use customer surveys to collect customer experience data, compared with just 58% of non-growth organizations. 

Gathering Customer Data

A growth organization as defined by Gartner is one that had positive revenue growth from 2018 to 2019 and is expected to have positive revenue growth from 2019 to 2020.  This is opposed to a non-growth organization which has reportedly unchanged or declining revenue from 2018 to 2019, with the same expected for 2019 to 2020.

The implication is that, despite concerns about data privacy, the most successful companies now are those that are gathering and using customer data in a way that is effective and compliant with existing regulations, like GDPR.

Emerging technologies are also enabling this. Gartner points out that the use of near- and real-time analytics to collect CX data is a rising trend among growth companies, with 43% of product managers at growth companies using analytics to collect and analyze customer perception and sentiment data. This is compared with just 22% of product managers at non-growth companies.

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Keep Customer Experience Agile

Rick Blair is vice president of product strategy and experience management at Melville, NY-based Verint. He told us that successful growth strategies must include agile CX programs that implement holistic experience management strategies, that enable companies to understand and act on insight captured across customer, employee, brand and product experience. This holistic approach can drive significant gains and successful CX outcomes. “A good metaphor for this is to think that we all take the same roads to work, only we just woke up to find the roads have all changed,” he said.

“The strong companies and programs that have the ability to navigate the overnight changes, and the tools in place to map a new pathway to continue the critical flow of information from the outside-in, are the ones that will weather the storm. Others could be flying blind.” So, what do successful companies do?

  1. They instrument as much of the experience as possible paying attention to key points along the journey, but still allowing for the identification of issues at any point.
  2. They ensure the right contextual data is included to support closing the loop and acting — the don't just collect data
  3. They go deep within each step of the customer experience — the most successful connect surveys, calls, emails, chat, social and experience analytics to close any gaps

They do this all in an integrated fashion, ensuring the data is connected and shared across the organization to support an org that's informed and acting on the signals from the customer.

DataOps Defined

DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics.

DataOps will write software that automates the integration and cleaning from thousands of data sources and executes the transformation and publication of analytics without human intervention. DataOps will check every one of the billions of data points that flow through the system, identifying and when possible, fixing errors. 

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The Role of DataOps

It's tempting to say that companies who collect CX data will improve their chances of success. Companies now have the tools to collect more CX data than ever. There are also other kinds of data, Chris Bergh, CEO of Cambridge, Mass-based DataKitchen, said.

Numerous customers are browsing company websites, talking to customer service, meeting with sales reps, purchasing products, requesting warranty repairs, and more. Data from dozens or even hundreds of sources must be integrated to create a single view of the customer.

Companies that collect data may think that they are setting themselves up for success. They will lag behind the companies that both collect data and institute automated processes to synthesize and monetize that data. Companies with the most responsive, robust and scalable data analytics will emerge as winners.

In fact, harvesting data is not enough and successful enterprises do a lot more that. It is not just data-driven enterprises that will win the day; it is enterprises that have strong DataOps operations.

The point is that companies will differentiate in two ways and both are required, he said.  First, they will collect CX and other data. Second, they will architect automated systems to integrate, clean, transform, and publish data with real-time error-checking and monitoring. “The laggards of the future will collect enormous amounts of data and then call upon their data science team to manage it using manual processes,” he said.  “The leaders of the future will use a methodology called DataOps which automates all of the above steps.”

DataOps will win the day by using automation strategically to cope with the ever-growing quantity and complexity of data. Automation will do the heavy lifting of data operations freeing up the data team to create new analytics that expand the enterprise's understanding of their challenges. They will garner more insights from their data and react more quickly to fast-paced market dynamics.

Data as a Priority

Pushpraj Kumar is a business analyst at India-based iFour Technolab. He pointed out that data collection has become a major priority for all kinds of businesses. Different tools and technologies help in capturing and analyzing customer data and draw new insights from it.

Companies do predictive analytics from consumer behavior data.  Many companies have already built an entire business model around customer data to create ads or to improve business. “Customer data is helpful in identifying and listening to the voice of the customer. Data allows organizations to not only better engage existing customers with relevant communications, but also create models for the buyer’s journey based on data for similar prospects,” he said.

Data align with customer interests and it allows measuring the business needs and interest of their audience. Analyzing customer data across different channels provides marketers valuable insights on how buyers interact with specific content – facilitated using technology tools such as web analytics and mobile analytics.