You may have a promotional strategy that is run weekly or even daily that forces you to create the largest universe without fatiguing the base. Very short turn-arounds are required to operate this with any frequency. You now want to build lifecycle indicators into this strategy and then remove some from this promotional stream for specific stages of the lifecycle. The original intent is to be smarter about key points of time where an interaction has the most impact, yet this is more fluid than promotional marketing. A lifecycle could be defined as early lifecycle, pre-purchase, could be trial driven, could be market driven, could be lifestage, or post-purchase. The scenarios are endless. You now have a promotional strategy and a lifecycle strategy, both driven on the premise of "relevance" as the catalyst to timing and content.
Let's say you automate portions of early lifecycle, high-impact points, potential switch or conversion indicators. Do you still expose this audience to the same "in-market" promotions that are taking place through promotional streams? And how will you do this when content is so fluid, business rules so dynamic and targeting is so last-minute?
I've talked to hundreds of marketers about these challenges in this space and the problems are persistent. No tools will solve this alone, but they can help.
More seamless decision management tools would help with distributing decision-making so you can evolve business rules and be in a position to publish them through programs and business units. Better workflow management and content management would allow you to potentially leverage content more seamlessly across programs and the subsequent needs to manage the flow of approvals for faster turn-around. Better modeling could help you inform not only what is in your daily or weekly promotion, but what's automated in a self-learning capacity. Better testing functionality would allow you to program test scenarios seamlessly without having to customize one-off tests that rarely scale. Better integration with Web analytics will allow you to tie direct causal relationships between email and the point of conversion and what paths are best optimized.
I wish there was a perfect solution for every business scenario, yet for the foreseeable future we will have to rely on integration to pull scale and strategy off. It will be a people and priority challenge. The first step in improvement is recognition of the real challenges ahead of us.
Make sure you don't go to a gunfight with a butter knife.