In brief: A cache is temporary storage for previously retrieved data or outputs that speeds up repeated access and reduces load on the original source.
How I use Cache in practice
With Cache I care about the trend and cause, not an isolated value. I break the result down by source, offer or customer type, but only as far as enough data remains for a sensible decision. Every dashboard should have a note next to the number describing what changed in measurement or operations.
What to watch out for
A number can look more precise than it really is. Cache can be distorted by poor implementation, consent, attribution rules, small data volumes or different definitions in tools. Optimising a metric without checking business results often means merely producing cheaper but worse activity.
Questions for a decision
- Exactly how do we calculate the value, and from which source?
- Which decision changes if the number rises or falls?
- What can distort or duplicate the measurement?
- What do we compare the value with so it has business meaning?