eCommerce Analytics

Over the past two weeks, I’ve been watching the fallout from two important conferences taking place on the West Coast (where I would much rather be right now given the latest round of snow in Boston.)  The first annual Predicitive Analytics World ’09 was staged in San Francisco on Feb 18th and 19th and eTail West 2009 took place last week and drew in a host of e-Marketers from around the country. One common theme that I seem to be hearing from the blogs and articles I’ve read from both: make sure you’re using your customer data effectively and, most importantly, keep it simple.
Read Simplicity is Key for Marketing Analytics »

I somehow missed Brian K. Walker’s excellent end of year post Ten Themes for 2009: eCommerce Technology. It’s a good read and, given our focus, this prediction jumped out at me.

Predictive merchandising becomes ubiquitous, and the crowd begins to separate. “Predictive merchandising” is also referred to as “automated merchandising” or “personalized product recommendations”. Whatever term you like (or are marketing) we will see this area are the “product reviews of 2007”, where we go from stepped up interest and demand to a default feature. The incumbent concerns and cultural hesitations of merchants and marketers will be replaced with an enthusiasm for the improved customer experience and ROI.

I disagree wholeheartedly.

Read Forrester: Predictive Merchandising to Become Ubiquitous in 2009 (They’re Wrong) »

I have to admit that it’s been a while since I’ve written on this Istobe blog, but for good reason. My wife and I welcomed a little girl into the world (Vivian June) on December 28th and have been battling sleep deprivation and dirty diapers ever since (and yes, she’s definitely worth it).  The bad news is that I just haven’t had much time to read all of the news feeds and blog posts that I would have liked to over the course of the last few weeks. So, as I looked blurry eyed through my blog posts and news items this morning, I noticed a few articles that point out some important marketing trends for retailers in 2009:

Read Marketing Trends For Retailers in 2009 »

The core of Istobe’s technology is an engine that predicts the next product or product category that a customer wants, a la Amazon or Netflix. However, we try to make this technology more applicable to other processes within the retail realm, such as direct marketing and merchandising, by looking at actual sales data. The typical recommendation engine (like richrelevance) only lends itself to realities in the online world, since they take advantage of website data exclusively. The Istobe engine is a bit more universal, using actual sales transactions to build models and predictions. In either case, the goal of either approach is to predict the next best product for your customers. I’ve compiled a good starter kit containing three links for retailers and others who may be interested in learning about Next Best Product approaches.

Read Predicting the Next Best Product for Your Customers: A Hyperlinkset »

As you can tell from our blogs, we’ve been very social media focused this week. We’ve actually been watching the space for quite a while now, but recent events have really shown how the power of social media has changed the thinking of the mainstream marketing crowd. I’m sure many of you are aware of Motrin fiasco where women (and men) on Twitter expressed outrage at the portrayal of moms by the ibuprofen company (“Motrin moms,” a-Twitter over ad, take on Big Pharma–And win).  Additionally, many political pundits have credited Obama’s success with winning over 18-35 yr olds to his use of new and more cutting edge marketing mediums. The power of social media has certainly been proven out, but does your company need to worry about it and, if yes, how do we take advantage of it?

Read Twitter Me This: How Do Businesses Take Advantage of Social Marketing »

I was reading up on analytics technology today and ran across an interesting article at TDWI (The Data Warehousing Institute) which surprised me.  It was surprising due to the fact that it was a year old but was reporting the same results as today:  predicitve analytics solutions are still novel to many companies and unknown to even more.  Even after dozens, if not hundreds, of successful case studies show how predictive analytics are a low-effort, high ROI solution to help a company achieve strategic goals:

[P]redictive analytics can yield a substantial ROI. Predictive analytics can help companies optimize existing processes, better understand customer behavior, identify unexpected opportunities, and anticipate problems before they happen,” Eckerson writes. For six years running, he points out, a majority of TDWI’s annual Leadership Award winners have used predictive analytic solutions to achieve noteworthy business results.

Before we created our predictive analytics solution for email marketing we knew the benefits of predictive analytics solutions and we realized that marketing has many metrics and data points as well as a very strong set of historical data which we can and do use to build solid, accurate models of customer behavior and desire.   Why are users of predictive analytics still considered Early Adopters?

Read Predictive Analytics Provide Big Payouts For Early Adopters »

The other day I was flipping through the channels and landed on an episode of CSI.  I forget which flavor, it looked sunny and beachy so it was probably not the one in New York City.   Anyway, in this episode a murder took place and the only evidence seemed to be a passerby’s recollection of a license plate and hair color of the driver.  Not much to start with but as we all know that is enough for the CSI team.  

Read Marketing CSI »

I will be the first to admit that our industry, predictive analytics to support retail marketing strategies, is dense with technical words, phrases and methodologies all wrapped up into various umbrella groups or plans such as “Market Segmentation Analysis”, “Customer Analysis”, “Predictive Marketing”, “Retail Pricing Strategy” etc. Although each sounds a bit different all of these approaches strive to reach the same outcome:

• Use available data to describe customers and understand their needs, wants and actions

and each takes a different approach but all the approaches are based on well established principles of computer science and statistics.

Read Market Segmentation Research: Science Fiction or Non-Fiction »

Since every news site and blog I look at seems to be focused on the economy, I felt it only appropriate that I change it up a bit from my usual analytics rants and write a post that looks at the recent financial concerns.

Read What’s happening: the economy and analytics »

Just a short post today to finish off our fantasy sports foray of the last week and a half. In case anyone else noticed, our quarterback predictions showed up on Yahoo, as well as other eminently reputable sites, as MIT-Based Startup Predicts Tom Brady Will Break 24-Year-Old Passing Record. Well, by now we know that this will never happen, with Brady unluckily succumbing to the dreaded torn ACL.

Read Tom Brady and What Might Have Been »