eCommerce 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’ve been reading a lot recently about the current squeeze on baby boomers and how this is affecting the traditional targeting methods used by many retailers. Noreen O’Leary over at AdWeek had a pretty good article last week on how the recession is weighing on the minds of boomers getting ready to retire – so much so that many have already curbed spending and are starting to discard brands that now seem too expensive or luxurious.  This is a huge problem for many retailers – baby boomers are the heart of many businesses and represent the best and most profitable segments. So what’s a retailer to do?

Read Appealing to Baby Boomers through Enhanced Cluster Analysis »

A couple of weeks back, I gave you a set of three hyperlinks that describe efforts to predict the next product that each of your customers will buy. Many companies that initially sprung up around this field have taken Amazon or Netflix and their collaborative filtering approach as the method for predicting what customers will like next. More strikingly, recommendation engine companies have patterned their offerings after Amazon and Netflix as well. That is, the output pieces are built around website infrastructure, meaning that the recommendations live online and are tailored specifically for customer visits. Alas, there are more than a few businesses that still make a majority of their money offline and need a solution that fits the non-electronic areas of their business. What about the merchandising arm that just wants to know how to determine the quantity of each product to buy from the manufacturer or wholesaler for the coming quarter?

Read Using Next Best Product Recommendations to Determine Inventory Levels »

As marketers, we only have a few levers to really impact the bottom line. We can acquire customers more cheaply, acquire more valuable customers, increase customer purchasing amount and frequency, and improve retention rate. We only have so many resources to devote to moving these levers.  Which one should get attention first?

Read Which Marketing Lever is Biggest? »

I’m sure many of you, like me, will be watching the inauguration on television today or possibly following it through one of the many websites that will broadcast it live. While this is certainly an exciting and interesting time in American politics, the presidential inauguration also marks an important event for mobile carriers. Millions of people intent on following the day’s events will chose SMS and text messaging as their primary media outlet of choice today. Verizon alone is expected to see over 1.4 billion text messages sent today (yes, billion) which will shatter the previous record of 803 million messages set on election day.

Read Inauguration May Be Dawn of New Mobile Age »

I’m a firm believer that SMS marketing as my blog posts such as Mobile Marketing - Five Steps to Start the Art and Master Targeted SMS and The Beginning of SSPs: SMS Finally Getting the Email Treatment attest. So I talk about it a lot as a great, new channel, even if only used as a higher form of email marketing. One thing I note to marketers is the fact that double opt-in gives you an automatically targeted audience. After all, the sheer work needed for a customer to double opt-in filters out - for the most part - those customers who will be offended by too many touches via their mobile phone. This, however, leads to the inevitable question: “Can you explain double opt-in to me? I’ve heard of it but I don’t exactly know what it is.” Understandable. Mobile marketing, after all, is still new. Well, today, you’re in luck. I’ll join the PacSun Mobile Alerts program and let you follow along so that you know exactly what double opt-in is…and what it looks like when initiated from a web site.

Read SMS Marketing: Double Opt-In Explained »

Well not definitively but some research by cognitive scientist Mark Changizi (R.P.I) suggests that product placement advertising actually makes a person desire to obtain the product more so than if one were to see a 30 second advertisement 10 times in a week for the same product. Why is this?

Read Product Placement Ads Much Better »

Last week in Weather Marketing we talked about ways to use freely available temperature and precipitation data to make sure you’re not marketing parkas to your customers in Texas. The rub was that the National Oceanic and Atmospheric Administration dosn’t exactly make the data available in the friendliest of formats. 

We’ve put our data manipulation skills to work and reworked the data in a way that will make it easy to import into a database table or append to your customer file. The following files provide the average annual and seasonal temperature (in Fahrenheit) and precipitation (in inches) for each state and for the US as a whole. It also lists standard deviation for each value in case you want to go super-nerdy on your analysis.

Have at it in the format of your choice!

Comma separated value: temp_and_precip_by_state.csv

Excel 2007: temp_and_precip_by_state.xlsx

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 »