I recently read that to manage customer journeys, those journeys must be defined and accessible. Doesn’t this sound simple and awesome? The problem is that it does not reflect the reality in which most large organizations operate.
Journey management and journey analytics remind me of the chicken and the egg – which comes first? There are journeys you inherently need to manage – onboarding, upgrades, and complaint resolution, for example – and analytics are necessary to monitor and improve those. But there are also important customer journeys and paths that you only discover through analytics and exploration. Are transitions between specific support channels proving to be critical, for example? Or do I just ignore this question if the journey was not previously defined for me?
Hopefully these few examples demonstrate that journey management and analytics must go hand-in-hand. One of the biggest challenges to-date of enabling this has been getting your data into one place. In some cases, portions of data from a single channel might live in multiple stores. In other cases, data from a single channel may live in isolation in a single repository. And in some cases, bits and pieces of data from multiple channels are transformed or duplicated across multiple stores to the point where their lineage is almost impossible to ascertain.
Thankfully, Teradata has recognized this challenge as an opportunity for innovation.