How Organizations Select Digital Analytics Products

Thanks Adam, this is a superb list and it is cool that you brought up some of the less obvious ones like executive relationships, agencies compromised by license kickbacks, or how NOT helpful customer review sites usually are. I also agree that current use cases are way more important than eventual future “more advanced” ones. I would say though that implementation covers more than “just” the data collection part (which, as you write, can be migrated more easily these days thanks to Tag Management Systems and Data Layers). There is also the part of the “connections around the analytics product”, this data import here, that agency report there, this database or all the data scoence models built off of special exports or even the raw data feed of the analytics tool etc, that backend integration with the Content Management system to automatically create tracking links or to display report data in the article you’re editing etc, that daily script that compares analytics and backend data to verify data quality, that decibel or qualtrics integration, that product view and conversion feed to your pricing tool, and so on. All these integrations are often a huge additional load on the “implementation” and need to be taken into account.

This may be the most brilliant post I have seen from you, and that says a lot. You have covered the tech selection/review process from every angle I could think of, and a few that I had forgotten about despite my experience as consultant, vendor and practitioner/manager. I'm really glad you lead with the most important point that people and process are far more determinant of success than technology in any branch of analytics. This is something I stress with my students. This post should be required reading for everyone who makes purchase decisions in this space as well as those who sell to them.

Great read Adam, thanks!