From Five Basic Food Groups to What’s For Lunch: How Journey Visualizations Guide Specific Actions

For decades, kids were taught about the five basic food groups. But this was an oversimplification, and those five food groups evolved to charts such as food pyramids and plates, along with serving guidelines and nutritional information on many food products. These visuals were all well-intentioned efforts to provide a guide to nutrition, but of course, we know that nutrition is complex and dynamic and new research comes out every day, requiring us to think about our own food choices.

Just as nutritional trends require constant reassessment and evolution, the same can be said of the data visualization tools available to analysts in their BI tools. Traditional charts and graphs are only useful at explaining bits within the data—usage information, the health of KPIs, and other things that are tallied, evaluated for change over time, compared and correlated.

But journeys are different because they consider sequential events—the flow of traffic and the pattern of behavior. Journey analytics is intended to enable people to figure how events relate to one another. It’s not a snapshot that answers a general question like “How is your website doing?” What journey analytics offers is an answer to more specific, valuable questions like “What one change could you make to your website that would have the biggest impact on your NPS score?” This type of flow can be thought of as the difference between a one-size-fits-all food pyramid and a personalized nutrition plan that tracks your eating patterns, nutrient absorption, and the impact on your health over time, leading to specific, actionable recommendations.

In order to take full advantage of the additional depth of journey analytics for meeting business goals, analysts need visualization options that enable them to interpret data faster, more intuitively, and to represent things that traditional charts or graphs cannot. A typical graph can illustrate how a metric changes over time, but cannot readily reveal:

  • Common patterns of behavior
  • Relationships between behaviors
  • How triggers affect future behavior
  • What triggers, behaviors, and outcomes matter
  • What changes to the environment will deliver the best impact for the business and for customers

When you start to add the weight of this journey data to traditional analytics visualization tools, the illustration quickly becomes clogged with visual noise. In order to be effective, analysts need visualizations that enable them to absorb more data of value, without slowing them down or creating distractions.

Consider Google Maps, which has endless lines, streets, parks, buildings, and names for everything. It is inherently very complex and noisy, but it’s designed to make finding what you need (like the nearest, best-rated health food store) easy to discover and navigate to.

A graph or spreadsheet can show you the number of cars per minute passing through every intersection. When it comes to making a decision about how to improve traffic flow, what’s more useful is a bird’s eye view of the city that highlights where traffic is heavy and how it changes over time. Such a view makes it easier to spot patterns and interpret the data in a way that lets you drive at solutions.

We humans are built for discerning patterns, and our very bodies are built of elegant patterns. We recognize them in nature and we design them into our world and products. The best visualizations for journey data will enable the analyst to discern patterns in data as easily as they can spot patterns in their natural environment.

That’s why the new visualizations we’re providing and developing for Fox draw on these lessons and take advantage of that inherent human capability. A Sankey diagram, for example, is useful for the high-level understanding of journey traffic and flow. Our dominant path visualization (shown below) is an enhancement of that, taking the best of the initial visualization and perfecting the algorithm for sorting information and laying it out in a way that enables an analyst to make sense of complex behavior patterns.

Further, the best visualizations for journey analytics are not static. They offer the ability to readily combine visualizations and enable interaction between them, letting the analyst to follow the story—the sequence of events and wherever they lead. The idea is that when an analyst clicks on a certain part of one diagram, it brings up a new visualization that is ideally suited for spotting the patterns in the data for this new layer. Now the analyst can drill in and out, spotting patterns and encouraging further exploration into the sequence.

With Fox, we are striving to enhance, combine and create new interactive journey visuals to help analysts explore and understand journey data and find the many delicious nuggets of business value inherent in it. We’re working hard to help you easily see the patterns in your data and figure out specific actions that can make your business healthier.

Bill Payment Workflows


Web Service Quote Leaking to Agent



Learn more about next-generation Journey Science Platform, Fox:

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Written by Pedro Quinones

Pedro Quinones is responsible for product design and UX strategy at Clickfox. He works closely with product management, design, engineering and end users to ensure that the company’s software products deliver valuable experiences to Journey Analysts. Currently, Pedro is pioneering the Fox user feedback program to guide ideation, design and development for new product features. Prior to Clickfox, he improved the usability of IT infrastructure monitoring products through user centered research and design at CA Technologies. He holds a Bachelor of Science in Computing and Human Factors from Colorado State University.

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