When I speak with product teams about the best practices for building analytical applications, there's one story I always tell. It's about how in those first few projects I made a maswive number of mistakes, but I managed to do one thing right: I wrote down what I learned from all those mistakes. It occurred to me that perhaps the best use of those lessons isn't keeping them all to myself, parceling them out over time in presentations here and there. Maybe it's better to combine them all into a series of learnings that I can share with others.

And that's what I've done.

I started by writing down each of the failures that I made — and there are a lot of them — and the associated lesson learned. I soon realized that, rather than a blog post, this would be more of a Homeric epic. A bit more than I was willing to undertake.

So I took another approach. For this series of blog posts, I've taken what I've learned about building analytic applications and consolidated them into a few categories. Well, more than a few. More like nine categories. The idea is that, rather than a bunch of dense text, this will be more of a series of checklists that when combined, can help a product team avoid some of the missteps on the path to a successful analytic application.

Here’s what I’ll be covering in this series:

  • Checklist 1: Planning the project
  • Checklist 2: Have you considered the logistics?
  • Checklist 3: Data Readiness Basics
  • Checklist 4: Analytics Technology— What’s the Plan?
  • Checklist 5: Product Strategy
  • Checklist 6: The Engagement Model
  • Checklist 7: Pricing & Legal Readiness
  • Checklist 8: Marketing & Operational Readiness
  • Checklist 9: The Launch

Each of these checklists has 7-10 items for you to consider when deploying analytics as a customer-facing application or even inside your own business. The first section, “Planning the Project,” covers the basic tasks that many teams skip right over and will be out next week.

I hope you find this new series useful!