Brianna Briggs, Ph.D. and Senior Economist at Bluewolf, shares advice for designing better customer and employee experiences using data as an advantage.
Data is the most valuable resource an organization has to serve its customers and employees. But innovative customer and employee experiences don’t happen by chance; they must be designed.
We’re not talking about design that’s focused on making something pretty (although that is also important), but rather, design that’s focused on delivering process innovation people can use and actually want to use — design that delivers human value which ultimately translates to real and lasting business impact.
Even before we can use data to improve interactions with customers, we must use data to design those experiences. Just as you can’t write a research paper without first doing the research, compiling data points, and distilling your findings into a central, purposeful thesis to guide the entire work, you can’t design user experiences without a firm understanding of customer and employee pain points, their cost to the business, and the specific (and tested) improvements that should be made to directly impact your business goals. In this way, data and analytics are integral pieces of the entire cycle of innovation, including the design process.
Dr. Brianna Briggs, Senior Economist at Bluewolf, introduces the integrated relationship between data and design, and offers guidance for becoming more data-centric (and hence, more customer-centric) in the Age of AI.
I wear many hats as an Economist here at Bluewolf, but I am focused primarily on heavy modeling and analytics for our Bluewolf Align™ service, which designs successful digital customer and employee experiences with Salesforce. For that service, I perform business case analyses to help clients understand the short-term ROI and long-term KPIs that they can expect from their technology investments.
I also lead a Journey Analytics practice, enabling our clients to map customer and employee journeys with data to reveal the specific moments of engagement that have a quantifiable impact on customer satisfaction, loyalty, and the organization's bottom line.
Data is indispensable to the design process. Qualitative findings must be validated with analytics to ensure that the user experience translates to a quantifiable benefit to the business. Data guides solutioning and unmasks problem areas. Data highlights the opportunities where change will deliver the greatest gains.
The process begins when the market opportunity of resolving the problem is quantified. The value of this opportunity can be continuously refined throughout the stages of development via rigorous testing and data insights.
This is the basis of our Journey Analytics approach. We quantify the emotional high and low touch points across customer and employee journeys in terms of each moment’s cost or benefit to the business, enabling us to create a true business case and design more impactful user experiences.
In this sense, data and analytics aren’t just critical for designing optimal user experiences, but also for proving the value of those experiences and securing stakeholder buy-in.
Yes – Customer Experience (CX) has immense benefits and quantifiable value for the companies that invest in it. It’s been shown that, on average, CX leaders outgrow their laggard competitors by more than 5 to 1.
We can estimate this benefit with data for each client considering a business transformation grounded in CX. We can then add confidence intervals to this estimate as we subject our desired CX to rigorous testing and simulation via our Killer App package.
*Forrester Research: Customer Experience Drives Revenue Growth, 2016
Be patient and realistic, but don’t let that stop you from getting started. Depending on where you are, whether it be a series of separate spreadsheets or handwritten notes, there is a learning curve involved. Determine where you are and where you want to be, then create a phased roadmap to reach your goals, allowing time to make the necessary transitions.
I would also advise all companies to develop and nurture a strategy around data quality and cleanliness. Data-centricity is far more difficult to achieve with poor or faulty data. As you progress on your data journey and bring on more sophisticated tools, ensure that data quality is top of mind.
AI is ushering in an exciting new phase in analytics, leveraging seemingly insurmountable and incomprehensible bytes of data to glean insights that can inform action.
With AI, analytics will continue to become more predictive and prescriptive. More and more, data and analytics will be used to augment human decisions, cut down on rote, repetitive tasks, and predict next best actions. Analytics in the age of AI enables organizations to serve customers better and faster than ever before. Ironically enough, data and analytics allow us to design more human experiences. It is a major game-changer and will also work wonders to reduce the cost of producing quality analytics due to an increase in the productivity of labor resources as they work alongside AI.
Companies that fail to keep up with analytics will lose market share, unable to keep up with the needs of their customers and employees. Bob Furniss, Bluewolf’s Service Cloud Practice Lead, defines the New Customer Covenant as “I will give you my information, but in return, you must know me—across all channels.” Consumers are willing to give up data about themselves for a superior customer experience, but if companies don’t invest in creating relevant and personalized experiences, they will lose customers.
Every organization can design better customer and employee experiences, grow their business and forge a path toward AI by first thinking about how to advance their data and analytics practices, technology, and processes.
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Bluewolf, an IBM Company, is a global consulting agency and proven Salesforce strategic partner that builds digital solutions designed to create results. Now.