Analyze your customers' journeys using Path Finder reports and dashboards

Analyze your customers' journeys using Path Finder reports and dashboards

Discovering a path is only half the story. Once Path Finder captures your customers' footprints, you still have to make sense of them—where they cluster, where they scatter, and where they simply vanish. A discovered path that's never read is just data sitting idle.

This is where Path Finder's reports come in.

Native Path Finder reports

Path Finder renders the discovered journeys in three visual forms: Path, Sankey, and Journey. Think of these as the tool's first language—the maps it draws for you the moment it starts observing.

Path report

A Path report lays out each type of journeys taken on your business landscape. It lists out the distinct journeys your customers have taken—one row, one path—so you can set them against each other and ask: which route is more common, which one converts faster, and where do two seemingly different customers actually behave the same way?

Example: Comparing onboarding routes

Zylker, an online retail store, notices that its Path Finder has recorded several distinct onboarding routes for new sign-ups. Some customers verify by email and browse straight to the product catalog; others sign in via a third-party app and head to testimonials before browsing anything.

A Path report lays both routes out for Zylker to compare—revealing that the testimonial-first customers, though fewer, convert to a purchase noticeably faster. That's a pattern Zylker wouldn't have caught by looking at a sing le journey in
isolation.

Sankey report

If Path Finder's job is to capture flow, Sankey is where you actually see it. A Sankey report shows how your customers navigate through touchpoints, graphically—as bands of movement whose width tells its own story. A thick band means a well-traveled route; a thinning one means customers are peeling off along the way. You're not just looking at where customers went—you're looking at how much traffic and saturation each touchpoint carries.

Example: Spotting where prospects thin out

ZylkerSure, a digital insurer, wants to understand how prospects move from browsing insurance plans to requesting a quote. In the Sankey report, the band leaving "Compare plans" fans out wide toward "Price calculator," but only a slim thread continues on to "Request a quote." That narrowing is the tell—ZylkerSure now knows exactly where its funnel is losing width, without needing to guess.

Journey report

A Journey report is a flowchart representation of your customers' journeys—the most structural of the three. Hover over any touchpoint, and it tells you a story from both directions: which paths led into it, and where records go from it. Where Sankey shows you volume as a visual weight, Journey report shows you the actual map of connections—useful when you want to understand how customers are approaching a touchpoint and the rest within the larger business landscape, not just its traffic.

Example: Understanding a touchpoint's role

Zylker wants to know whether its "Product Simulation" touchpoint genuinely helps prospects decide, or if it's just a detour. In the Journey report, hovering over that touchpoint reveals it's fed almost entirely by "Comparator" visits and, in turn, leads overwhelming ly to "Add to cart." That two-sided view confirms Product Simulation isn't a dead end—it's a decision accelerator sitting right in the middle of the path.

Together, these three reports are self-scribed maps of your customers—through which you can decipher their activities without asking a single question directly.

Beyond the native maps: Building deeper analyses

Path, Sankey, and Journey reports tell you what happened. But once you want to measure it—compare it, trend it, set a target against it—you'd reach for Path Finder's analytics module. It carries the same seven chart types available across CommandCenter, but every one of them, applied to Path Finder, is really asking the same underlying question: what do the paths my customers discovered, on their own, actually tell me?

Let's explore each of them.

Line Graph

A line graph traces performance, growth, progression, and trends of one or more entities across two measures—with a mean line to anchor the average.

In Path Finder, a line graph tells you how long a discovered path took to progress through its touchpoints—not a designed sequence, but the one your customers organically walked.

Configuration parts of a line graph:
  1. The Path Finder configuration you'd like to analyze (Add report for)
  2. The data you want to use (Choose data)
  3. The measure you prefer (Measure)
Notes
Note: For a line graph, the data selected is duration, by default.

Example:Understanding the average time spent on touchpoints before entering the sales pipeline

Pre-pipeline touchpoints are where a business gets its first honest look at a prospect—before any sales rep steps in. By monitoring how long prospects linger across these early, organically discovered touchpoints, a business can identify which ones actually hold attention, compare different paths taken so far, and see how long most prospects take to become a qualified lead—including the time spent making key decisions along the way.

To build this:
  1. Give a name for the report
  2. Select the Path Finder configuration you'd like to analyze
  3. The data is already chosen for line graphs, and that is duration
  4. Select the measure from the options: Maximum, Minimum, or Average.
    For our example, we'd choose average time.

Bar Graph

Bar graph is a comparative study—two or more entities, set against each other, across measures and variables.

In Path Finder, the variables are your discovered touchpoints; the records are the customers who passed through them.

Example: Comparing time spent across pre-purchase touchpoints

Zylker wants to know where prospects actually spend their attention before converting—the "Pricing page" or the "Comparison page."

By selecting both as base touchpoints, choosing Duration as the data, and Average as the measure, Zylker can lay the two side by side.

To build a bar chart:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you'd like to analyze
  3. In Choose base stages, choose the touchpoints you want to analyze
  4. In Choose data field, select the data you want to measure.
    1. These points form the x-axis of your chart.
    2. Records displays the count of records at a touchpoint
    3. Duration indicates the time taken for each touchpoint
    4. Numeric field of an app gives you the flexibility to represent percentage, time, or any numeric value

      Note: Only merge fields created for number fields of that process are visible. If you create a merge field now, only records that visit that point of the path later will reflect it—merge field data isn't applied retroactively to records that have already crossed that config point.
  5. In the measure field, choose Average for the typical value, Minimum for the lowest, or Maximum for the highest
  6. In the group by field, select the touchpoint by which you want to group the analysis
  7. In the Filters field, add filters if required—say, records created during a particular period, or belonging to a specific segment

Pivot Report

A Pivot Report lets you look at a discovered path from two angles at once. By setting touchpoints and fields as rows and columns, you examine how a data point shifts at the intersection of two path attributes—the kind of pattern that stays hidden when you look at one dimension alone.

Example: Understanding conversion patterns across entry channels

ZylkerSure wants to know whether prospects who arrive via organic search behave differently from those arriving through referral—specifically, how their average time-to-quote compares across each eventual conversion touchpoint. Setting entry channel as the row and conversion touchpoint as the column, ZylkerSure discovers referral traffic reaches a quote nearly a day faster—a pattern no single-dimension report would have surfaced.

To build a pivot report:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you want to analyze
  3. In Select Rows, choose the touchpoint and field for your rows. Add multiple rows for a more granular comparison.
  4. In Select Columns, choose the touchpoint and field for your columns
  5. In Select Data, choose the field you want to analyze
  6. In Operation, choose how to summarize it: Average, Maximum, Minimum, Sum, or Count
  7. In Filters, add filters as required

Heat Map

A heat map reads a discovered path in color. The intensity tells you where records concentrate, and where a selected value swells or thins across touchpoints—so patterns surface visually before you ever read a number.

Example: Identifying where organic traffic concentrates

Zylker wants to see where prospects actually spend their time before converting—not guess at it. Choosing Records as the data and Count as the measure, the heat map lights up warm at "Products" and "Comparator," cooler at "Testimonials." Zylker didn't have to ask which touchpoints mattered most; the color told it.

To build a heat map:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you want to analyze
  3. In Choose Data, select Records, Duration, or a numeric field from an app
  4. In Measure, choose how to summarize the data—Count, when Records is selected, for instance
  5. In Color code, choose Warm to Hot or Hot to Warm to define how intensity should progress as the value
  6. increases
  7. In Filters, add filters if required

Progression Analysis

A Progression Analysis compares how records move between selected touchpoints of a discovered path. And because a discovered path isn't sequential the way a funnel is, a middle touchpoint can genuinely hold more records than an earlier one—the analysis reflects the strength of a touchpoint, not just its position.

Example: Understanding how prospects move between discovered touchpoints
Zylker wants to know how many prospects who land on an "Initial visit" touchpoint go on to reach "Demo requested." Selecting both, choosing Records as the data and Count as the measure, the progression analysis reveals the drop: out of 2,000 initial visits, only 340 request a demo—giving Zylker a real number to work against, not a hunch.

To build a progression analysis:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you want to analyze
  3. In Stages, select the touchpoints you want to compare. Add multiple touchpoints to analyze progression
  4. across more points in the path.
  5. In Choose Data, select the data you want to measure
  6. In Measure, choose how to summarize the selected data
  7. Repeat the configuration for each touchpoint you want to include

Goal Chart — On reaching a particular stage

A Goal Chart tracks how records progress toward a defined touchpoint goal, over time.

Example: Tracking progress toward a discovery goal

ZylkerSure defines "Quote requested" as its goal touchpoint and tracks the number of records reaching it across a selected date range. The chart shows a steady climb through the quarter—until a dip appears right after a pricing page redesign. That's not just a number; it's a prompt to investigate.

To build a goal chart:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you want to analyze
  3. In Define Stage Goals, select the touchpoint you want to track as a goal
  4. Add multiple stage goals if you'd like to track progress toward more than one touchpoint

Target Meter

Target Meter measures progress toward a defined target within a discovered path.

Example: Measuring progress toward a target

Zylker sets a target of 5,000 records reaching a "Qualified" touchpoint this quarter. Selecting Records as the data, Count as the measure, and 5,000 as the target, the meter shows 4,200 achieved—close, but a visible gap Zylker can now plan the last stretch around.

To build a target meter:
  1. Give a name for the report
  2. In Add report for, select the Path Finder configuration you want to analyze
  3. In Choose base stage, select the touchpoint for which you want to set a target
  4. In Choose Data, select the data you want to measure—Records, Duration, or a numeric field from an app
  5. In Measure, choose how to summarize the selected data
  6. In Target Value, enter the value you want to achieve
  7. In Filters, add filters if required
  8. Between the three native maps and these seven deeper analyses, Path Finder gives you two altitudes to work at: the map, for reading a path at a glance, and the measurement, for putting a number to what yousaw. Together, they turn a discovered path from a curiosity into something you can act on.