Data Visualization vs. Customer Experience
There is no doubt that one of the ways that big data drives business monetization is by understanding customer behaviors. However there is a large delta between data visualization about customer behaviors and using data to enhance customer experience. Let me see if I can summarize the difference in two images:
Data Visualization: enables data practitioners to leverage visualization techniques to uncover insights, trends and relationships buried in the data (see Figure 1).
Customer Experience (or customer experience design): leverages analytic insights to provide a more engaging, more differentiated customer dialogue at the point of customer engagement such as web page, mobile app, email, or point of sale (see Figure 2).
Now we’ll dive deeper into the differences between data visualization and customer experience design because both play a critical role in your big data-powered business initiatives.
Data visualization is a branch of descriptive statistics that leverages trend, comparison and statistical analysis to understand the structure, content, context and relationships buried in the data. Data visualization involves the creation of the visual data representations including tables, bar charts, trend lines, box plots, geospatial maps, social graphs, etc. in order to help data practitioners identify potential correlations in the data as well as to flag outliers worthy of additional investigation (see Figure 3).
The key goal of data visualization is to reveal relationships in the data to data practitioners via graphics, and the highly iterative nature of the data visualization tools supports the rapid exploration of the data.
Customer Experience Design
Customer experience design (also called “user experience” (UEX) design) focuses on rendering and delivering the analytic results in an intuitive, actionable way that helps the customer do whatever it is that they are trying to do.
The importance of UEX as a business discipline really started with the web world, and has been dramatically accelerated by the mobile app avalanche. Web companies were one of the first to realize that there was limited real estate on the screen, so they had to make as productive use of that space as possible in order to influence customers’ browsing and buying behaviors.
From a customer perspective, the always-on, always-available smartphone has opened an opportunity to drive a continuous conversation with the customer. This in turn provides an opportunity for the organization to leverage insights about that individual customer (e.g., interests, passions, associations, affiliations, behaviors, tendencies, trends, and importantly, likelihood to do X) to deliver “extreme” personalization (see Figure 4).
Now leading organizations are realizing the same customer, product and operational insights can be used to power a more productive front-line employee dialogue. These insights provide organizations the opportunity to leverage analytic insights to make recommendations to the front-line employee at the point of customer engagement (see Figure 5).
There is a clear business discipline around customer experience design including persona development, storyboards, mockups, wireframes, prototypes, etc. See http://uxmastery.com/resources/techniques/ for a detailed overview of different customer experience design techniques.
Data visualization and customer experience design are two very different but very critical big data capabilities.
|Data Visualization seeks to use data visualization techniques to help data practitioners to tease patterns, trends and relationships buried in the data||Customer Experience Design uses analytic insights to create a more targeted and compelling customer engagement|
Organizations need to master both skills if they hope to get the most out of their big data initiatives.