My experience with postcard programs is that they are cost effective. Their potential scale is defined by the size of the profitable universe of website abandonments that a company’s website traffic generates each month. Therefore, the good news is that sending a postcard to a website dropout pays off; the bad news is that these programs are limited by the number of website abandonments a business has each month (which is a function of website traffic and the number of unique visitors the website generates). These programs could therefore increase overall revenues by 2 to 5%, but their scale is limited. The catalog should be large enough that a 2% increase in profitable revenue is significant to the bottom line and also large enough that the vendor running the postcard program can cover the fixed costs. A cataloger typically needs at least 100,000 unique visitors per month to work with a bouncing postcard provider.
Postcard bounce programs have scale limitations similar to the prospecting universe from cooperative databases.
Scale limits include:
- number of unique website visitors or cart abandonments each month;
- number of prospects, as opposed to previous buyers, who visit and abandon a site;
- number of website visitors that can be linked to a name and postal address;
- some programs also find similar households in their databases of potential clients; and
- response rates and dollar per pound, then determine the subset of postcards sent that are profitable.
All of these scale limitations mean that the size of a postcard program is quickly set and the plateau is reached quickly. This is similar to the plateau of website abandonment and shopping cart programs from providers such as Criteo.
- Objective: Identify a profitable prospecting universe to acquire new buyers.
- The measurement: Match back processing.
- Target lists: The biggest source is co-op databases, but website dropouts also provide a proven universe of prospecting names.
- Ladder: It depends. Finding a profitable prospecting universe and knowing scalability is determined by testing to where you fall below the variable break-even point.
Companies that run postcard programs for website abandoners run their own internal correspondence programs where they measure postcards sent against their response rate. Postcard incremental sales are measured by having opt-out panels where a portion of the universe is not mailed and the response rate for that unmailed universe is also measured. The true response rate for these posted postcards is the incremental revenue between the unposted and posted sets of website dropouts that are in-universe to receive posted postcards.
Smart cataloguers are also expanding their use of postcard marketing. Best practices may include:
- Sending to expired customers.
- Sending a postcard to unsubscribes by e-mail.
- Sending postcards to the best customers between catalog releases.
- Reach leads from a cooperative database model that can float on top of a mailing list model, but the cataloguer would have to wait for the next catalog delivery, which can take months.
- Hitting the website is dropping leads who didn’t buy right away on the first catalog delivery, but may engage and buy from a postal retargeting mailing long before the next catalog mailing to prospects.
Profitable postcard programs have opened catalogers’ eyes to this channel. Postcards can be printed in much smaller quantities than catalogs; it is difficult to cover the fixed costs of catalog runs if the print run is less than 100,000 or 200,000, whereas postcards can be printed with runs from 1,000 (or less!). With smaller print runs, cataloguers find opportunities to send mailings to niche merchandise within their customer base, special promotional offers, or to the best or newest buyers. Catalogers ask the question: What small segments can generate profitable incremental sales from a marketing contact with a postcard?
Catalogers’ best business practice for prospecting new customers is to send all prospecting universes that meet above the break-even point and not prospecting universes that fall below the break-even point and whose cash flow are not positive.
Catalogs are expensive to mail. Printing paper and postage add up to $0.70 to $1.00 or more to mail. Therefore, a catalog with a 50% merchandise margin must have leads that respond between $1.40 and $2.00 per catalog mail to break even and be cash flow positive. The typical catalog business model is to aim to send all leads that respond above the break-even point.
Why is “break even” the typical goal? If you post below the break-even point, you quickly lose a lot of money. If you post above the break-even point, your prospecting generates new buyers at or above the break-even point. Catalogers say you make prospecting money and get the lion’s share of your profits by mailing your buyer’s file.
Break-even point is measured in the catalog world as the cost of the catalog divided by the margin on merchandise. So you break even when response rates bring in a dollar per book that covers the cost of merchandise and the cost of mailed catalogs (hard cost of printing, paper, and postage). customer response file and each mailed segment is measured in terms of dollars per pound.
How do cataloguers find prospecting lists? Website abandonment programs take the names of those who abandon the site and send them a postcard. However, the largest prospecting universe usually comes from models created in catalog databases. Cooperative databases take catalog buyers and model them against other names in their database of catalog buyers.
How big are cooperative database catalog universes? It depends on the commodity category, but it’s simple to test in co-op prospecting universes by sending deeper into segments until the last segment drops below break-even.
How do cataloguers scale these proven prospecting universes?
- Test the depth until you know how deep you can send the last segment still above breakeven.
- Send the universe of proven profitable prospecting names as deep and as often as possible. The scale is a function of the size of proven prospecting universes multiplied by the number of times these prospects can be mailed in a season or year.
How cooperative databases build models determines the size of the profitable models they create. Cooperative databases are very effective in finding profitable leads for catalogs. Typically, they start with an array of similar catalogs and begin with mail-order customers who have purchased in the specific merchandise category. To be a potential buyer, you must have previously purchased by mail in the goods category. Thus, the universe of cabinetmakers begins with all those who have already purchased from a cabinetmaking catalog. Ditto for plus size women’s clothing, gardening, high-priced men’s clothing, food as a gift, power tools, vitamins for your horse, etc.
Next, the universe of buyers within the commodity category is refined. Recency of purchase, dollar amount spent annually on mail-order purchases, and purchase history from multiple catalogs are key variables. Then the co-ops run a series of models to find which households rise to the top. Households that score high in more than one of the models are generally the best prospects compared to a household that only scores high in one model. The next step is to rank the model segments and run tests within the segments to see the relative response rates of the segments and how far the model names can be sent profitably. This determines the profitable prospecting universe. The scale of a cooperative database of profitable and proven hotbeds is limited. The size of the universe can be increased by mailing more often or taking names from multiple co-ops (or taking prospecting names from any other proven source of profitable leads).
A cataloger’s best practice is to use all marketing programs that deliver new customers above the break-even point. Website dropout postcard programs from a direct marketer are proven to be cost-effective, measurable, scalable, and easily manageable.
The programs are testable, and catalogers should explore how these programs can add to their revenue, bottom line, and the number of new customers that can be profitably acquired.
Jim Coogan is the founder and president of Catalog Marketing Economics, a consulting firm specializing in catalog circulation planning.