Data consistency behind a customer experience program fulfils a few critical requirements. It supplies quality information not only regarding the data and data sources, but also regarding the models we use for analysis. An information system that keeps track of customer demands must be self-adjustable. Where it comes to a limit, it needs to issue an alarm.
Consistency of information is required across the corporation to ensure the expected efficiency effects in support and automation. Whenever the impact of of touchpoints or the success of journeys changes, there are reasons for a justification of a critical structure update. New attitudes come up, consumer behavior changes. Our data must be able to tell the story. If not, we need to add the missing links.
Consistency is a requirement, but inconsistency also tells an interesting story. Actually in many cases the more interesting information is the pattern of change in touchpoint impact. What is the reason behind the kind of change that is going on? How has the change developed over time? Can we use it for a scenario forecast? For a trend analysis?