ACM Ecommerce Conference

Last Friday I had the pleasure of attending the ACM Ecommerce conference in Chicago. I would like to thank John Riedl, the organizer, for putting the conference together and inviting me for the keynote. I had the pleasure of meeting members of the core technical teams from Amazon, Yahoo!, YellowPages, and researchers from great technical schools like Carnegie Mellon and Stanford.

This conference delved deeply into the algorithms and science underlying ecommerce. There were talks ranging from combinatorial auctions, revenue optimization and game theory applied to ecommmerce. My talk, which can be found on SlideRocket here, was titled "Investing in Algorithms". Below is an excerpt from my abstract:

In 2008, the software market is rapidly evolving towards Software-as-a-Service
and Cloud computing, and away from the on-premise delivery model. In exploring
these new models we will see that this is more than a business or delivery model
phenomena affecting ecommerce - it is a shift that fundamentally changes
expectations of what software can accomplish. In this model data is king.
Algorithms and analytics become significantly more relevant as the data is now
housed in a central location.

The talk let me highlight several key areas of investment for Hummer Winblad through the lens of a few of our portfolio companies. Because I gave the presentation in SlideRocket I was able to show how SaaS drives new sources of data compared to on-premise solutions. During the presentation I pulled up the historical data of a previous presentation that I had emailed to a different group - and show how many times the presentation was viewed and which slides the audience spend the most time reviewing. Hard data to collect with PowerPoint!

I then talked about Baynote as an example where SaaS companies can use their own products as part of the sales cycle. Baynote requires only a few lines of code to be integrated to a customers site to be up and running. Data is then fed back to the Baynote SaaS application and quickly the recommendation/search results can be surfaced. Baynote quickly gathers A/B testing to show the uplift of revenue. If you attempt this type of solution on-premise there is a limit to the data that a vendor will see, and you have many steps (procure hardware, configure hardware, install software, integrate product, etc) before these uplift effects could be shown.

The last theme I touched on in my talk was the ability of SaaS to provide closed loop actionable analytics. I highlighted our companies Omniture and Signal Demand as examples where the SaaS vendors can both make recommendations and stick around to quantify the results.