We've started an analytics service [1] focused on the operational aspects of automating analytics for life sciences. We've got good chops in both biotech/life

We've started an analytics service [1] focused on the operational aspects of automating analytics for life sciences. We've got good chops in both biotech/life sciences and software development ..and the default urge is to build a fully automated system and tools. however, what we're doing instead, is focusing on customer development at the front end - the "customer onboarding" process. This is involves a bunch of human interaction to understand exactly how customers are approaching their data and experimental processes - it feels a lot like consulting on the front end and definitely doesn't "scale". Over time, we'll start creating very specific tools that help a) make onboarding quicker and easier for the customer and b) reduce the onboarding burden on us - the key is to only do this when we have clear understanding of the required features and the ROI for developing them. Current customer feedback is very interesting it ranges from: "analytics still requires a lot of high-touch expert consulting" to "feature _______ is a simple feature that customers need right now ..make it, and that will lead to other feature insights and customer use." ...would love to hear any advice / thoughts ..we're in the struggle :) [1] Yukon Data Solutions https://yukondata.integralappsystems.services/t1/ https://yukondata.integralappsystems.services/t1/