Data Quality – Understandability

Customer knowledge is only useful if the underlying data has high quality.

The first criteria to fulfill for data to have high quality is being understandable.

Having understandable interaction reports answers two questions, what interaction happened, and where.

When you’re manually tagging, fulfilling this criterion is simple, as you’re only tagging a small subset of all interactions.

This problem occurs more prominently when you scale your analytics by automating it.

The sheer amount of data makes it difficult to pinpoint where things happened, as it’s easy to have data repeated for different interactions.

Component Analytics solves the what question is by reporting the Interaction Component.

And the where question is answered by the Module.

– Samy

* Yesterday I called this Predictability. Predictability is a side effect of being consistent and structured, criteria 2 and 3 respectively. Therefore I changed it to understandability.