CJA Journey Canvas, Fallout Touchpoints w/ Same Timestamp

[JaniceAk]

Hi all,

Wondering how Journey Canvas or Fallout visualization treats journeys with touchpoints that have the same timestamp? There is a use case to understand how many people open, click/unsubscribe after an email is sent, but the email events are timestamped to the disposition date--meaning each sent, open and click action (when it happens on the same day) has the exact same timestamp.

When using these disposition elements in a Freeform table to count People or Events etc., the numbers are accurate and match the dataset; but when I try to build out a journey in Canvas or Fallout, the numbers on the sequential touchpoints after the starting point (e.g. Sent) are slightly off (oftentimes less) than the freeform table. I presume it's because it cannot consistently interpret one disposition after the other because they have the same timestamp, but wondering if there's any other ideas. Why is that, and wondering if there are any workarounds other than altering the dataset's timestamp?

[Vinay_Chauhan]

Hi @JaniceAk 

You’re right, the difference you’re seeing is likely due to the identical timestamps. In CJA, both Journey Canvas and Fallout visualizations rely on clear event ordering to determine how people move from one touchpoint to the next.

When multiple events (like sent, open, and click) share the exact same timestamp, CJA can’t reliably interpret which occurred first. As a result, the platform may not sequence them correctly, causing the downstream touchpoints in your Fallout or Journey view to appear lower than the counts in Freeform (where the events are simply aggregated without order dependency).

Freeform tables count all matching events, while Fallout and Journey visualizations apply stricter sequencing rules - and identical timestamps create ambiguity in that sequence.

You can try the following - 

• If you can, add a small offset or sequence field to differentiate events that currently share the same timestamp.

• Or, use a sequential segment or define event order by event type (e.g. Sent -> Open -> Click) rather than relying purely on timestamps.

• As a validation step, you can continue using Freeform as your source of truth for counts and use Fallout primarily for directional insights.

If the timestamps can’t be changed in your source data, defining logical ordering within the dataset (like a “disposition rank” field) is often the most reliable fix.

Let me know if that works.