buying a soft serve ice cream cone
PHOTO: Seth Sawyers

In God we trust, all others bring data ― attributed to W. Edwards Deming 

While researching statistics for a presentation earlier in the year, I stumbled upon a recording of an old (2015) webcast done by a longtime customer experience guru, Bruce Temkin. The title of the webcast, “5 Trends That Will Reshape CX Insights,” intrigued me, and I listened expecting to hear some pretty outdated trends. Three and a half years is a lifetime in the digital world, after all.

To my surprise and delight, the trends discussed in the recording, while old(er), are by no means irrelevant. Better yet, they tie directly to the results of a recently released HBR Pulse Survey examining analytics and customer experience. Both highlight the strong connection between analytics and experience. The webcast was predicated on this concept, with all five trends explaining the do’s and don’ts of customer insights for shaping experiences. The survey revealed how little things have changed since 2015, showing that analytics still plays a critical role in experience management. Highlights of the survey include the fact that 60 percent of respondents said they believe real-time analytics drives customer experience while 58 percent credit significant improvements in customer loyalty and retention to analytics.

5 Old Trends With a Modern Spin = Great Customer Experience

Let’s take a fresh look at the five trends Temkin discussed in his webcast.

Deep Empathy, Not Stacks of Metrics

This maxim is tailor-made to help companies take advantage of the myriad unstructured data sources available today — sources that enable companies to not only measure the what (e.g., customer satisfaction) but also understand the why (personal context). Sentiment analysis can pinpoint the why with surprising accuracy, enabling empathy and generating customer insights that shape experiences.

This includes the use of natural language processing, text analysis and cognitive computing to identify and extract subjective information from varied sources, including social media, complaint applications, video and audio tapes, and voice-of-the-customer feedback mechanisms. More sophisticated applications go beyond designations like positive, negative or neutral to assign nuanced mood designations. These designations can be correlated with historical behavior to predict immediate and future impacts based on the prevailing sentiment shown by the customer at any point in the journey.

The HBR survey reinforces this trend. While respondents pointed to traditional technologies such as customer relationship management (CRM) systems, content management applications and marketing platforms as being very important, the following results indicate that they think technologies that can help with empathy are important now and will still be important in the future:

  • Social media monitoring: 60 percent of the respondents said this is important now, and 70 percent said it will still be important in two years.
  • Text analytics: 37 percent said this is important now, and 52 percent said it will still be important in two years.
  • Interactive voice response: 35 percent said this is important now, and 45 percent said it will still be important in two years.
  • Speech/voice analytics: 21 percent said this is important now, and 39 percent said it will still be important in two years.

Related Article: Use Design Thinking to Put Yourself in Your Customer's Shoes

Continuous Insights, Not Periodic Studies

While the periodic studies named in the original trend referenced activity such as market research and focus groups, modernizing the trend brings us into the realm of real-time analytics and the associated decision engines. Next-best-offer tools, which combine historical behavior with situational context (what the customer is doing on the website, in the mobile app, etc.) to identify the best communication for the customer in real time, provide the type of continuous insights that the webcast suggested companies should strive for.

Nearly three-quarters of the respondents to the HBR survey said they have increased their spending on real-time customer analytics in the past year. In building a foundation for using real-time analytics to power customer experiences, respondents said they value the following:

  • Translating data into actionable insight at the optimal time (cited by 83 percent of the respondents).
  • Making data accessible to the right people at the right time (80 percent).
  • Incorporating results into updated algorithms to provide closed-loop marketing (59 percent).

Related Article: Attitude Check: What's Your Organization's Customer Insights Culture?

Customer Journeys, Not Isolated Interactions

While journey mapping was (and is) a popular way to gain an understanding of the end-to-end customer journey, it is not typically done on an individual customer basis, but rather by persona. Since Temkin recorded his webcast in 2015, a new way of looking at the customer journey through detailed analysis has been developed — customer journey analytics. As interactions become nonlinear and customers bounce from channel to channel, journey analytics attempts to connect various data sets into recognizable journeys that reflect how customers actually navigate a company’s various sites. This provides depth of understanding of behavior within a channel as well as a panoramic view across channels. The goal is to identify pain points and develop actionable responses at an individual level with an astonishing degree of accuracy.

Just over half the HBR survey respondents said that their use of real-time customer analytics has provided them with a significantly better understanding of the customer journey — an understanding that has helped them strengthen the customer journey. Here are two of the top drivers of increased investments in real-time customer analytics:

  • Scaling customer-centered decisions and actions across function in the business (cited by 69 percent of the respondents).
  • Designing contextual customer engagements across the customer journey (62 percent).

Related Article: Why Customer Journey Mapping + Journey Analytics = 5-Star Customer Experiences

Useful Prescriptions, Not Past Predictions

This trend highlights much more than the need to shift to predictive or prescriptive analytics. It focuses on understanding what decisions the business needs to make and then determining how to apply analytics to support those decisions. In other words, the goal is to avoid analytics for analytics’ sake and promote analytics for the business’s sake.

HBR found much the same: Real-time customer analytics transformation goes well beyond pure technology adoption, requiring an understanding of business objectives to ensure success. Respondents identified the following as success factors for using real-time analytics to deliver meaningful customer interactions:

  • Clear strategy/goals (cited by 42 percent of the respondents).
  • Actionable data/visualizations (39 percent).
  • Collaboration across roles/functions (33 percent).
  • Strategic alignment (29 percent).

Related Article: A Pragmatic View of Predictive Analytics

Enterprise Intelligence, Not Customer Feedback

I see this last trend as an amalgamation of all the others. It is an affirmation that single-point factors (such as metrics, periodic studies, isolated interactions, past predictions and customer feedback) alone do not a great experience make. Because the customer experience is the sum total of all interactions over the life of a relationship, shaping it requires data from all sources knitted together with people and processes from across the organization into an enterprise intelligence.

Respondents to the HBR survey reinforced this interpretation by highlighting the following requirements for using real-time analytics to power customer experiences:

  • The ability to access and use all available data (e.g., customer activity) in a seamless fashion (cited by 73 percent of the respondents).
  • The ability to predict, optimize and forecast using trusted algorithms (64 percent).
  • Organizational support for experimentation (61 percent).
  • The ability to add/enhance data with new sources (61 percent).

Mapping the HBR survey findings to the five trends shaping customer experience (circa 2015) puts a modern twist on an oldie but goodie and yields concrete steps that companies can take today to improve the customer experience.