Often times the focus of ecommerce and online marketing is on conversions - making sales to your sources of traffic. But what about selling MORE to the people who already want to buy from you?

In the July 2007 edition of Business 2.0, the article “Rethinking The Recommendation Engine” discusses some of the latest in ecommerce cross selling and up selling technologies (aka recommendation engines).

According to Forrester Research, consumers spent $220 billion online last year and it is estimated that 10-30 percent of that is accounted for by recommendation systems. That is anywhere between 22 and 66 billion dollars!

So what is a recommendation system? The most recognized recommendation system is Amazon’s. Based on the items you have purchased and what you search for, they do some complicated calculations to find items that you might also like.

A ‘recommendation system’ is a friendlier name to the traditional sales terms of cross selling and up selling.
“Would you like to to super size that? Would you like fries with that?”
“If you love that shirt, take a look at this one. Do you want some new pants to go along with that as well?”

The article goes on to talk about some new recommendation platforms out there used by some heavy hitters.

• ChoiceStream - suggests movies and songs, used by Blockbuster, Comacst and iTunes
• CleverSet - Scans products descriptions, prices and ratings to make recommendations
• Aggregate Knowledge - Uses “supercomputers” to make connections between consumers and products - used by Overstock.com and WashingtonPost.com

These technologies are not well suited for the average online store. But that doesn’t mean you can’t, and shouldn’t, have some means of cross selling or up selling. Creating a simple recommendation system not only creates value by selling more, but it also enhances the customers’ experience, introducing new products and helping customers find what they may have forgot or need.

Here are some concrete recommendations for creating a simple system to capture that 10-30%, making the most out of your sales:

• Start simple - build in to your ecommerce platform a way for you, the store owner, to associate different products with one another
• Suggest similar and complimentary products - if they have a new pair of shoes in their shopping cart, suggest some shoe polish
• Get more complicated - make recommendations based on previous the buying patterns of the individual as well as other customers
• Up sell - show the higher end models of the same product
• Make recommendations along the way - show your recommendations on the product page, shopping cart page, checkout, and after checkout (do you need a car charger for that new iPhone?)
• Continue the dialog - follow up in the confirmation email with other items they might like or may have forgotten
• Monitor, analyze and adjust - constantly adapt to changing demands of your customers, especially if your software can’t