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 often feel that email is the neglected step child of retail marketing. We’ve all seen the news articles and blog posts that tout sexier marketing trends like Twitter and mobile marketing. Many retailers have already jumped on the social media and company blog bandwagon and will spend months planning and implementing these changes on their website. Yet, I so often run into marketers that are willing to throw together a weekly sales email in an hour and blast the same message to their entire customer list.  Why? Well, my guess is they are underestimating the “response” they get from email. Catalogers are quick to argue that offline communications drive online purchases, but how is online communication driving offline sales?

Read Why Getting Email Marketing Right is so Important »

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 »

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 »

With so many reports out there talking about why retailers are going to be taking such a hit this year, I thought it might be worthwhile to focus on the positive. The down economy has opened up several opportunities for retailers to try out new and interesting ways of reaching their customers.  I wanted to share a few of these with you.

• Read Surviving the Holidays: 5 Marketing Tips for Retailers »

First things first, no matter who you support, I hope all of you have either gone out to vote today, or are planning to go out to vote. Although I’m usually not this dedicated, I woke up at 6:30 this morning to try and make it to the polls by 7. I was hoping I might be able to get their before the crowds, but by the time I got there at 6:55, the line was already two blocks long. I’ve voted at the same polling station for over 10 years now, and I have to admit that I’ve never seen such an incredible turn out for any election thus far. It took me about an hour to make it through, which was actually less than what I originally thought, but glad I beat the long lines I know will be there later this evening.

Read Obama Leading in the Polls? Perhaps it’s Due to Better Marketing »

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 »

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 »

With today’s news that the retail sector is experiencing a slowdown, now is a better time than ever for multi-channel retailers to do two things: turn to cheaper forms of advertising (email) and use quick-return customer analytics to compete with gargantuan discounters like Wal-Mart that threaten to swallow retail whole. The truth is that Wal-Mart will continue to invest in analytics during the tough economy because they will see immediate ROI from understanding which customers are poised to buy, which items they want, and how much those customers are willing to spend. I can think of two, good reasons for smaller multi-channel retailers to follow suit.

Harvest your current customers
Most would say that the thick of a poor economy is a poor time to invest in new marketing projects. If these projects are tied to new customer acquisition, I might agree. It’s damned expensive to acquire customers and you tend to forget what you already have while you’re out prospecting, buying lists, etc. Sometimes, the answer is in front of you. In a poor economy, isn’t it imperative that you retreat to your base? Multi-channel retailers need to figure out ways to:

A. Not lose your current customers to competition (like Wal-Mart)
B. Harvest your existing customers by making them feel as though you understand them

Really, achieving B is the answer to question A. A redoubling of your customer service effort will always make your customers more loyal and less likely to jump ship. But we have to remember that larger players can always offer deeper discounts in an effort to combat your superior customer understanding. One way around this is to deepen your customer understanding on the marketing front with timely, personalized emails to your customer base. Ultimately, if you can address your customers’ needs first - make your customers offers at the cusp of when they need those products - then you are likely to win their business. This is the advantage that predictive models based on your customers behaviors provide you: the ability to beat your larger competition on timing as opposed to discounting.

Quick ROI
Customer analytics like those that Istobe proposes are great because the analysis takes advantage of data that you, as a multi-channel retailer, already possess. You’ve already got a record of your cusotmers’ purchases. In other words, there is no up-front infrastructure or talent investment. What this ultimately means is that your ROI emerges quickly. How quick? Well, let’s just say that you’re in the black (or, green) around month two. This is especially true if you’re already used to sending your customer data to a co-op database (like Abacus or NextAction); you’ve already made your data collection and transfer investment. Now it’s simply about turning those investments to a different use - customer development not acquisition - by focusing how that data helps you pull in the monetary margins in your current customer base.

As I discussed last week in Why Matchback Analysis Overstates the Importance of Catalogs, one of the most effective ways of figuring out how our direct marketing efforts drive online sales is to do holdout testing. Holdout testing is nothing more than a controlled experiment and, done correctly, is a low-risk way of producing the accurate results that matchback analysis can’t.

Let’s say we’re a cataloger and we want to know which of our online-only shoppers we can stop sending catalogs to. The simplest way to find out is to test it:

1) Separate the online-only customers into behavioral and demographic segments

If you already have a customer segmentation schema in place you can skip this step and use your existing segmentation instead. If you don’t have a schema, you have a couple of options.

You can do a manual segmentation by thinking about who your main customer groups are and what attributes they have. You can then developing rules based on those attributes to do segmentation (i.e., Age > 55, suburban address, often buy children’s items is classified as a grandparent).

If you want a more quantitative based approach and have a statistician or data miner on staff, consider using a clustering technique such as k-means or two-step. These will produce statistically sound groupings which are perfect for holdout testing. Sometimes, however, it’s no so clear what to call each group or what they look like.

2) Randomly choose a set of customers in each segment who will serve as the experimental group

One of the more common mistakes is selecting an experimental group that is needlessly large. We want to ensure the test doesn’t impact the business too much so it’s important to try to keep these groups small. This table to give you a rough idea of how big your sample should be per segment:

If you typically have a higher response rate you can afford a bigger margin of error in your testing. The reverse is also true. If your response rates are smaller, you’ll need a tighter margin of error in your testing to ferret out valid results.

3) Stop sending catalogs to the randomly chosen customers in each segment and track the results

For best results, run this test over a few months and see how the response rate of the control group who still receiving catalogs differs from the experimental group in each segment. If the experimental group’s response rate is only slightly smaller than the control group’s, the loss in revenue may be small enough that you can save money by not sending catalogs to that segment.

This experimental technique succeeds where matchback fails and helps you identify segments that no longer need your marketing dollars to spur spending. Finally you’ll know whether the catalog does indeed drive online sales.