The Istobe eCommerce Analytics Blog

Last week I wrote about the Istobe willingness to share with you some of the predictive models that we use in our fantasy drafts. Well, a week later and the Istobe world headquarters is just now kicking the empty pizza boxes to the side and emerging into full sunlight with one hand visoring our eyes. Indeed, it’s been a computer-heavy week running model after model in an effort to win the right to mock our peers.

My quarterback-selection model (like my running back, wide receiver, and tight end models), which I share with you today, is actually a series of regression models that use 27 different predictors to arrive at an estimation of how NFL quarterbacks will fare this year in the following categories:

• Completions
• Passing Yards
• Interceptions
• Passing Touchdowns
• Fumbles
• Rushing Yards
• Rushing Touchdowns

I used these categories to derive a fantasy value based on my league’s scoring system and urge you to the do the same.

The Highlights

1. Tom Brady will have another big season. He’ll ease back on the touchdowns and increase his interceptions. But the yardage? Off the hook. Check out those 5200 yards he’s going to pass for.

Read Quarterback Predictions for the 2008 Fantasy Football Season »

Omniture’s sales and marketing department are simply world class.  Not only are they beating the pants off of CoreMetrics, but they’ve sold a vision of complete information awareness that online retailers are eagerly buying into.  Almost every single one of our customers has bought Omniture or is about to.  And every single one of them has asked the same question.  Now what?

Read Congratulations! You’ve installed Omniture! Now What? »

Many customers have asked us to help them better understand the effect marketing messages have on their customer base. Almost everyone we know uses multi-channel marketing in one form or another - whether it’s email and web ads or email, web ads, and direct mail - most companies are using more than one medium to get their message out to new and existing customers. The problem many companies have is determining how and when to target each customer with the appropriate message.

Read Multi-Channel Marketing and the Zone of Influence »

I saw that some of my other brethren in the data analytics game broke out their parachute pants and shuffled MC Hammer into their blog lineup this weekend. And, of course, all of them had to make some snarky Hammer-based quip on how no one can touch his understanding of analytics or that Hammer was too legit to quit.

Read MC Hammer Declares Analyticstime »

I’m a big fan of Seth Godin, but his latest blog post, Ads are the new online tip jar, seems a bit shortsighted to me.  Seth argues that to support their favorite blogs readers should click on an ad to provide some small financial support to the blogger.  Taken to its logical conclusion, however, this strategy will only harm bloggers and other content providers in the long term.

Read Ads the New Online Tip Jar? Maybe in Small Quantities »

While working on a proposal the other day for a prospective customer, I decided that I’d go the extra length for him in an attempt to demonstrate where exactly the company could make up some ground in its effort to realize a bit more bang for its buck in its email marketing program. That is, the company wanted to make more money from its existing customer base. When I looked at the company’s email marketing statistics, I was surprised to find that their clickthroughs per purchase was much higher than any company I’d seen.

Read Clickthroughs Per Purchase is the Gold Standard for Targeted Email »

The blogosphere is awash in tips for doing email targeting.  Some are good (almost anything advocating testing email performance) but some are just flat out wrong.  Here are three commonly held tenets of email targeting that you should ignore.

Read 3 Email Targeting Myths »

One question that we constantly come up against is why online retailers shouldn’t blast their entire customer base with every email promotion they create. Granted, most companies use some form of segmentation to track email responses (the usual 0-12 month buyers vs. 12-24 buyers is a common example) , but besides being defined by arbitrary recency and monetary spend cut-offs, these groups have no real bearing how the customers contained in those groups will respond to a given ad. My colleague Matt wrote a nice entry about this back in July (see Does your email response rate depend on how many emails you send?), but I recently came across some new metrics that I think help drive the point home.

Read Timing and targeting: why you shouldn’t blast all your customers with every offer »

What’s not to like about fantasy football? It raises the importance of the unimportant football games (i.e., those games in which your team is not participating). It allows for some of the finest trash talking on the planet - with few repercussions for losing the Sunday match-up as long as you win the weekly war of words. And, most importantly, fantasy football gives Istobe yet one more opportunity to crunch data in an effort to predict outcomes. So in the next two weeks, we plan on crunching the last seven years of NFL player data in an attempt to predict this year’s fantasy workhorses.

Read Get Ready for the Ignite Fantasy Football Draft Predictions »

As a follow-up to Doug’s post about customer lifetime value yesterday, and the advent of our online customer lifetime value calculator, I wanted to revisit the most famous use of customer lifetime value in recent business strategy and practice: Gary Loveman and Harrah’s. Harrah’s developed sophisticated customer lifetime value models to predict the ultimate value Harrah’s could aspire to for each individual customer. Then Harrah’s used its well-known customer loyalty program to try to reach that value.

Read The Strategic Impact of Customer Lifetime Value: The Harrah’s Story »