Weekly order curves are affected by several different factors. Mail deliveries, the weather, time of year, etc., all affect mail delivery times. However, you, the catalog marketer, have the most influence over how soon orders start flowing after the initial mail date and peak order levels by the actions you take. A catalog business, large or small, is affected by the order curve and it is a topic that should be given consideration. The management of your business depends on it. This month, I want to touch on some of the factors that affect order curves and why they are important to your business.

Typically, orders will start flowing in 7 to 10 days after the initial mail date based on a normal 5-day mail distribution pattern. For example, if the initial mail date is December 31, week #1 for orders would be January 14. Some orders will start showing up towards the end of the prior week. However, the week of January 14, in my example, would be the first “full” week of order flow and the first week of the revenue/order forecast. Therefore, this is the week I would typically start forecasting order volumes.

Co-mailing programs affect the order curve and the postage amount you pay. The postage is predominately impacted by co-mailing. The order curve is more affected by distribution patterns, i.e., east-to-west or west-to-east, mail dates, in-home dates, etc. This process occurs during the binding/ink-jetting phase of catalog production. During the binding/ink-jetting stage the process is essentially the same as selective binding but instead of combining multiple mailing versions of the same catalog the printer combines multiple catalog titles into one mail stream. This causes more of the mail to qualify for the carrier route rate. This reduces your postage expense and it speeds the in-home delivery time of your catalog. From a cost savings perspective, co-mailing is a win-win. For example, the piece rate for 3 digit mail is $392 per M, the 5 digit rate is $335 and the carrier route is $249 per M. On a list pool size of 2.0 million, approximately 50% or 1.0 million pieces would qualify at the carrier route level. Of the remaining 1.0 million, approximately 40% or 400,000 would qualify at the 3-digit level and 600,000 at the 5-digit level. The chart below shows the typical savings based on a pool of 1.0 million and 2.0 million.

Point is pool sizes matter. In our example above, going from a pool size of 1.0 million to 2.0 million names will save an additional $25.75 per thousand. (The figures are gross amounts.) In addition to the savings another benefit of co-mailing is improved deliverability. More carrier route or 5 digit pallets will result enabling the catalogs to penetrate the postal system deeper (which could generate additional savings by going to more SCF’s). This will increase production flow through the postal system and alter your incoming order curve.

In a co-mail pool, the direction you mail also affects the order curve. For example, if your printer is located on the East Coast they probably mail West-to-East (especially if in-home dates are important). Obviously it takes longer for the catalogs to get to the West Coast compared with trucking books East-to-West. The mailing pattern also needs to be a part of the planning. If you and your printer are both located on the East Coast and if you mail East-to-West your catalog will arrive in-home sooner on a regional basis. This means you will begin to receive orders sooner.

Let’s take a look at typical order curves, by season, for a consumer catalog mailer. Please note the cumulative percent done by week. Also note how the percentage complete varies for the same week by season.

So much depends on the level of circulation and the actual in-home dates. Holiday is the fastest curve. The summer curve is the next fastest curve. Fall and spring follow. It is interesting to know that the demand revenue curve varies from the order curve for the first few weeks. The order curve is generally “faster” than the revenue curve by 1% to 5%. This means the average order size is slightly lower during the first seven or either weeks due to the fact that more impulse buying is taking place. But, it does mean that your revenue curve will vary slightly from your order curve; another important point to help improve the accuracy of your forecast.

Mail Dates vs. In-Home Dates

Order flow is greatly affected by how you mail, i.e., mail dates vs. in-home dates. Some catalogers prefer mailings that are based on in-home dates. Other use mail dates. From my experience, there is often confusion over which strategy to employ and why. Some catalogers tend to use these terms interchangeably while significant differences exist between the two methods. An in-home date occurs when the majority of the catalogs being mailed hit in-home within a four-day window. When a mailing takes place, the printer will stagger the distribution by day so that approximately 90% of the total mailing reaches all customers and prospects within four days of each other. A customer living in California will receive his or her catalog within four days of someone living in New York, for example. Mail dates are defined, as the day the mailing is to begin. The mailing generally takes place over a five-day period (if in a mail pool drop-ship program) beginning on the specified date. When in-home dates are used, the printer determines the actual release date of the mail. When mail dates are used, the cataloger specifies these dates. The most significant difference between in-home dates and mail dates has to do with the pace of the order volume that will result from each. When in-home dates are used, the order curve will peak more sharply and generally die-off more rapidly. Distributing catalogs using mail dates tend to cause the order curve to be flatter. There is still a peak, of course, but that order spike is not as pronounced and the order line is longer compared to when in-home dates are used. So why does this even matter? The use of in-home dates can cause call center staffing issues. When the order curve is more pronounced, additional people are needed during a shorter period of time to handle the volume of in-coming calls. What’s more, the call volume will tend to decrease at a faster rate which means you could be in an over staffed position (unless you mail more frequently as discussed later). Please refer to the graph. Here we have plotted the typical order curve for a mailer who uses in-home dates vs. a cataloger using mail dates. Note the differences in the curve and the “peak” day for each.

If there is no in-home requirement the chances are orders will be received more quickly from where they are being distributed and extended out over a longer period of time. If in-home dates are used, there will be more of a peak in order volume. With in-home dates, the order curve will be more compressed.

Cash flow, call center staffing, etc., are all affected by the order curve. Without proper planning, you can find your call center under staffed during peak order weeks and over staffed soon after. The direction you give your marketing person and printer is important to your business. There are other external factors that affect your order curve such as mail deliveries, your printer, etc. But my advice is to focus on those factors within your control.