Lesson #2 Continued: Monetizing Data

Lesson #2 from my recent The Data Warehouse Institute (TDWI, August, 2008) keynote presentation covered "monetizing data." What I want to do on this post is to expand on that thought by providing some examples of how web 2.0 companies monetize data.

Monetizing Data: Targeting


"Delivering the right message to the right person at the right time at the right price" has always been the operating mantra of the world of Marketing. The goal of web or online marketing goes one step further: to deliver a single ad that compels the consumer to take action. And the web can leverage the wealth of sub-transactional and transactional data to create finely-focused behavioral targeting categories that help achieve this monetization objective.

Targeting is probably the most common way that web companies monetize data. Some companies make money via subscriptions and others aggregate and sell their data to businesses, but the focus of this posting is to discuss monetizing data via improved targeting.

Targeting and Analytics are really just different sides of the same coin:

• Targeting tells you what message to deliver to what audience.
  
• Analytics tells you what you can do to improve your targeting effectiveness.
  

The Analytics-to-Targeting relationship is a closed loop process; improved measurability (from analytics) yields improved relevance and audience insights (for targeting) and so on. Unfortunately, many web companies really don't understand or respect this linkage. They offer very compelling targeting products, but don't spend equal effort to offer very compelling analytic products that help to measure and optimize targeting effectiveness. Sort of like having a big block '68 Camaro and forgetting to put a dashboard or steering wheel on that baby!

Until next time! Decision Support 2.0

Web 2.0 Meets BI 2.0: Learning #1

I recently had the opportunity to speak at The Data Warehouse Institute (TDWI, August, 2008) on the topic of what happens when an old school data warehousing and Business Intelligence guy falls into the world of web analytics. I'm going to use this and the following posts to cover my 6 "learnings" from this experience. Plus I think that these learnings form a key basis for what I'm calling Decision Support 2.0.

Learning #1: Business Model Evolution

The old world technology business model was built around a product-based business model. That is, the product is packaged like a normal product - much like buying a laptop or even toothpaste - and sold as a product (with an on-going annual support contract). This model worked well when the industry was starting as it was a business model for which it was easier for Purchasing Departments to buy software / technology.

The problem with this business model was that an increasing percentage of total vendor resources need to be allocated to support and maintenance. This greatly inhibits investments. Also, this business model is that the rate of innovation is totally "you" dependent, which is why the Open Source movement is disrupting this business model.

The new world business model is services-based (e.g., subscriptions, etc.) as demonstrated by companies like SalesForce.com and Red Hat. Cloud Computing has the potential to really accelerate this model, and the result will be new innovation in the way of new products and services, as well as lower switching costs will enable customers to more easily adopt these new offerings. Unfortunately, the burden of business success still falls upon the users.

What we are seeing on the web is potentially a new, more disruptive business model - performance-based business model. With this model, the vendor only makes money when the customers make money, a real win-win scenario. In this model, vendors take on full responsibility for business execution success, and are rewarded accordingly! Massive amounts of data and computer power enabling new web business model.

Final note on this topic: it's not technology that's disruptive, it's the new business models that new technologies enable that are disruptive. It’s not technology that’s disruptive, it’s the new business models enabled by technology.

My next posting will cover the "secret sauce" that fuels what I am calling Decision Support 2.0

Welcome to Decision Support 2.0

Hey folks, this is my first attempt at blogging and hopefully I can do a decent job of sharing my learnings and observations about what life for the discipline of Decision Support looks like in a Web 2.0 world. Yes, I know that Decision Support is a term from the 80's (heck, we could go back another decade and try "Executive Information Systems"!), but there is so much that decision support looked to address that is still relevant today.

So let's have some fun with this and get going!

"Data, data everywhere but not a moment to think"

Watch this space!!