Merchandise That "Starts Orders"

Online marketers do a great job of following "where" a customer goes when she visits a website.

Catalog marketers do a great job of understanding "which" items "start an order".

Why not apply old-school catalog techniques to the data-rich environment known as your e-commerce website?

Here are three orders, from three different customers:

Customer #1:

• Item #1
• Item #2
• Item #3

Customer #2

• Item #1
• Item #3
• Item #4

Customer #3

• Item #3
• Item #4
• Item #5

In many order entry systems, as items are added to the shopping cart, or are recorded by the contact center agent, the items are added to the database in the same order as requested by the customer. If this is the case, you can conduct an analysis called the "order starter" analysis. Your mission is to identify the items that "start" orders.

Let's analyze the five items ordered by these three customers.

• Item #1 = Average of 1.0: (Appeared 1st, 1st)
• Item #2 = Average of 2.0: (Appeared 2nd)
• Item #3 = Average of 2.0: (Appeared 3rd, 2nd, 1st)
• Item #4 = Average of 2.5: (Appeared 3rd, 2nd)
• Item #5 = Average of 3.0: (Appeared 3rd)

In terms of "starting orders", item #1 was the item most likely to start orders, as it had the lowest average "position" in each order. Item #1 was the first item listed in both orders it appeared in.

Now look at item #3. This was the best selling item, it appeared in each order. However, its average position was second. Therefore, this item not the top priority of the customer. The customer wanted something else, and complemented their order with this item.

Compare item #1 to item #4. Item #4 always appeared later in the order. We assume that this item doesn't "start" orders.

In cataloging, it is frequently desirable to put items in the first twenty pages of the catalog that sell high unit volume and have very low order starting scores. I've analyzed catalogs that significantly missed plan, and found that the lack of high-volume, low-order-starting scored items in the first twenty pages are the cause for sub-optimal performance.

In online marketing, there are countless items that are buried deep within the site, selling a small number of units because the item has no way to be "advertised" to a large audience. By analyzing the order-starting score, the online marketer can move items with low scores to landing pages that receive a decent amount of traffic. This gives items a fighting chance to "start orders'.

This is an example where you don't need a rocket scientist to make improvements. Spend a few minutes with your SAS programmer today, and learn which items customers start orders with.