Direct marketing is a science that can be tracked to the penny and continuously improved. Misunderstanding of lists and selects is the industry’s greatest weakness.
1. 99% of Direct Mail is sent Standard Rate (bulk mail) without returns. List sellers rarely receive complaints as mailers rarely know their delivery rate and very few lists even guarantee deliverability rates. Those with a guarantee limit it to the cost of the list so never cover lost/wasted postage and printing costs.[Read more…] about Direct Mail Facts
Traditional Compiled Business and Consumer Lists:
1. We strongly suggest your primary source to obtain your current-month, retail, compiled business data is from the largest compiler, and your primary source for current-month compiled consumer data is Epsilon/Equifax. We are certain their accuracy, conservative models, and (in most cases) coverage better meets the needs of most marketers than do their competitors’ lists.[Read more…] about Business & Consumer Lists
1. Many are not what they seem. Please read about traditional compiled lists (above) as the same pitfalls apply to nearly all compiled specialty lists.[Read more…] about Compiled Specialty Lists
Nearly every marketer knows that if there are subscription lists available for your target audience you should at least test them. This is often the only option (beyond slug-titles) for reaching specific individuals not available from traditional compiled list sources.
1. As with every list, be sure to use every appropriate select on each new campaign. Where applicable, buy the 30 or 60-day hot list names in addition to narrowing your list as much as possible when testing any mailer for the first time.
Buying the most current names as well as selecting the most specific audience available assures your first test is your best test. If your mailing is successful, you can test less specific, less expensive lists against that benchmark whereas if you are not successful you’ll have to buy more targeted lists and run the tests again.
2. As with all list updates, buy immediately after the update, run fresh counts to verify it took place as scheduled, and plan your mail date accordingly. Try to be first hitting the new names on that list.
3. Controlled circulation publications (free to the subscriber) tend to include many inappropriate names such as salespeople. You must select by title, industry, company size, etc. to efficiently utilize controlled circulation lists. We also recommend avoiding home addresses if possible, and as a general rule find that the more expensive the subscription the higher the quality of the lead (and, again, controlled circulation subscriptions are free to the recipient).
4. Most subscription lists have demographics appended and identifying the source of the appended data will allow more accurate selections (allowing you to accommodate the compiler skews). Please see “Compiler Counts Compared” at the bottom of this page for obvious examples of compiler skews.
5. Where desired selects are not available on the subscription lists for your target audience, consider appending data from compiled list sources. While there are often restrictions on appending data, it may be acceptable just to “match” for elimination purposes.
6. Another option is to match the rented subscription list to a preferred compiled file (for as little as 1-cent per name) to verify you are reaching the desired audience and to eliminate those outside your targeted demographics.
The initial match is free. If it matches well you need not spend any money. If the match is poor you may want to append a data element to identify which records are and which are not within your target audience.
Response data is invaluable for targeting those with specific interests, life-stage events, and other demographics as there is often no other way to obtain this data. Response data is primarily gathered from surveys and product registration cards and is often enhanced with traditional compiled data yielding highly selectable, targeted lists.
1.Self-reported information tends to be exaggerated and is the source of a great deal of “junk mail.” Human nature often takes over and those completing surveys and product registration cards tend to overstate their income, understate their age, and exaggerate their interests and occupations.
In many cases, the responders have incentive to respond to receive coupons, web-site access, or some other free or discounted products or gifts, but have little reason to respond accurately.
2. Every available check and balance should be used to insure the responders match the targeted demographics.
As an example, while someone may check a survey box indicating an interest in international travel or food and wine, making them appear to be good prospects for high-end products, many will not have enough income to purchase high end goods.
While you can eliminate some unqualified prospects by selecting higher income ranges, the income is often also self-reported on the same survey and it may be (is often) overstated. Here a second select like net worth or income producing assets can eliminate many of the unqualified prospects. These data elements are not self-reported and are instead modeled by experts such as Claritas and CACI using housing, census, and other public record data.
3. Beyond self-reported information about interests and lifestyles, the compilers often create “models” to identify those likely to have similar traits. We have found this to be extraordinarily inaccurate in many cases and should be considered carefully.
When buying response type data from a website or reseller you’ll see the select but will never know whether it is all self-reported (with all its pitfall’s) or includes modeled data.As an example, Epsilon/Equifax has 5,000 dog owners in a town of 75,000 and InfoGroup (Donnelley) showed well over 25,000. They “model” or “infer” that because 51+% of households in a given zip code with certain demographics (single family homeowners within certain ages and incomes with children present, etc.) has a dog, all do. This is clearly untrue as some prefer cats, yet we find it typical of InfoGroup and other compilers’ data.
4. In addition to survey and product registration generated lists, seminar and trade show attendee lists and web-site inquirers are also widely available. Here again, there are many unqualified individuals in these lists and they must be carefully scrutinized.
Those attending business trade shows are often salespeople that sell goods similar to those offered by the booth vendors and have no purchasing power (or interest). Similarly, those attending consumer oriented trade shows (home shows, computer shows, auto shows, etc.), are not necessarily buyers and are just looking. Web site inquirers are especially suspect as many register false names and addresses. Obviously, “buyers” tend to be far more accurate than “inquirers” and “attendees”.
Obviously, those that find most of the addresses in a given area worth targeting can utilize saturation mailings saving a great deal on postage.
1. Residential saturation lists should be truly homogeneous from one source to another so can be purchased solely by price. Does everybody know Rural-Route addresses (and in most cases PO Boxes) are considered single family dwellings?
2. Careful scrutiny of the demographics of various carrier-routes allows saturation mailers to obtain saturation postage rates yet target only the most appropriate audiences. Targeting based on the demographics at the zip code level allows for saturation postage yet precludes the efficiencies available when targeting by carrier routes. You only need to saturate the carrier routes you wish-not entire zips.
3. Residential saturation lists with “names where available” allow for personalized mail on most addresses, and can greatly increase the response rate of many campaigns. However, the available names are always from out-of-date “wholesale” consumer lists, which are updated far less frequently than current-month consumer lists. Valassis, the largest saturation list compiler, doesn’t sell names.
In order to maximize the efficiency and effectiveness of names-where-available saturation mailings we recommend obtaining the complete saturation list (from any source) and then merging in the contact names from a current-month Epsilon/Equifax list.
4. Business saturation lists are rarely as complete as traditional current-month lists from the largest compiler. They have most of the business addresses but if the goal is to reach all businesses saturation lists miss the home based businesses and those utilizing PO Boxes, which are available from Dun & Bradstreet (about 20% of all businesses). If businesses and not residences are the target, we recommend merging a list from the largest compiler with a saturation list to ensure maximum coverage and the lowest available postage rates.
5. Combined residential and business saturation lists are so inexpensive that beyond mailing to out of business locations, their low cost often offsets the benefits of merging it with compiled names from the largest compiler (as the home-based businesses will be picked up in the residential saturation addresses).
With the USPS reporting over 25% of direct mail is undeliverable as addressed-junk mail abounds. Response rates have gone from 2+% a decade ago to less than 1%. Your undeliverable and miss-delivered mail will be greatly reduced if you obtain only current-month data from the most accurate sources and utilize the appropriate postal and demographic selects.
The differences in list selects from various sources are staggering. Nothing could be more “green” than mailing only to the appropriate prospects. Please see, “How to buy a list” for some free advice on obtaining the most accurate and appropriate lists.
Junk mail is the wrong offer sent to the wrong person. The right offer sent to the wrong person is no less junk than the wrong offer sent to the right person-it’s another person that won’t buy.
As mentioned throughout this site, with the USPS reporting over 25% of direct mail being undeliverable as addressed, and a large part of the delivered mail actually being miss-delivered (per the definition of junk mail, above), please read, “How to buy a list” for some free advice on obtaining the most accurate and appropriate lists.
Please click the pdf for extensive instructions, guidelines, and best practices on e-mail design and marketing.
International lists are, in many cases, far less accurate than domestic lists, yet many must rely on them. Of course searches of lists of lists should be performed to identify every potential source, and then they must be scrutinized at least as closely as any domestic lists, simply due to the increased postage and other marketing costs.
Please read “Tips on How to Buy a List” for advice on utilizing the most appropriate list selects and on avoiding the common pitfalls of many selects.
While InfoUSA also covers Canada, their consumer lists rely heavily on modeled data as privacy laws prevent household targeting. Further, their Canadian business lists have the same pitfalls as their US lists with skewed sales and employees and the inability to avoid most branch locations.
Beyond Canada, the largest business list compiler dominates the international business list community. In fact, a majority of advertised international lists are their lists re-packaged. Instead, we’ll obtain the data for you directly from their current-month international files at 20% to 30% off.
UCC lists (Uniform Commercial Code filings) are an invaluable resource for identifying competitor relationships with the availability of targeting by lender names, transaction dates, collateral, as well as traditional demographics.
Most important is that when searching by lender name the request must include every possible variation of the bank/lender name. Select the initials like B of A, Bk in addition to Bank, “and” as well as with an ampersand, First through Fifth in addition to 1st through 5th, and so on). Some of our requests have thousands of variations included-we’ve even overwhelmed the largest compiler’s ability to process them and now have to split-up large jobs.
We also recommend selecting an origination date within the past 5-years. The largest banks taught us that those older than 5-years tend to be too far out of date.
Extraordinarily popular among our largest banking clients, our contracts allow us to provide this data at 30% to 40% off.
Get your free list analysis to determine your list deliverability and accuracy according to various sources. All compilers offer this at no charge.
1. First, ask to have your list suppressed against various compiler lists. Ask they match your file only against their most deliverable records. This is imperative as your purpose is to verify they have the same records in their current month file and to determine whether your files meet your minimum deliverability standards. Their purpose for doing this for free is to try to sell you their unique records-those you don’t currently have in your database.
If a high percent are suppressed, all is well concerning deliverability.
2. At the same time find out how many unique records they have and verify your demographic parameters. This will identify your market penetration according to that source. Simply ask your same file be suppressed against their lists using your targeted selects.
As an example, if you target only households with $50K+ income or firms with $1mm+ sales, run your list against that subset, in your geography, to see if they match well. Of course, it is important to accommodate the skewed data offerings from various compilers, (please visit “Compiler Counts Compared” under TIPS ON HOW TO BUY A LIST for additional information on the huge skews in compiler offerings). You will see that our preferred compilers have far more conservative models than do their competitors.
If your file matches well you’ve confirmed that you are reaching the appropriate prospects (at least according to “that” source). If the records don’t match well, ask they run it against other subsets (those with lower income or lower sales in our example). This will identify where your records are falling, again according to that source.
If a significant number can’t be matched anywhere (in or outside of your parameters) it suggests your list may be out of date or otherwise contain records well outside of your target audience by demographics or location.
3. Before matching or suppressing we suggest you run your list through postal processing software. This costs only a couple of dollars per 1,000 for all 3 common processes (together) below. We also take several steps others don’t bother with or even know. Not only do we take the time to remove erroneous data, starting with symbols and overflowing field errors, we also “trim” extra spaces (a quick 5% improvement in accuracy), and re-assign misplaced data elements. We also run multiple addresses (both mail and physical (PO Boxes in most cases)) and run street “address 1” and “address 2” together and separately if present.
• NCOA (National Change of Address), which shows those that have moved in the past 4-years and provides a new address. This identifies some of your out-of-date names. If the new address is outside your geography or other parameters, delete the record or change the name to “Our Neighbors at” if the address is still an appropriate target.
• CASS (Coding Accuracy and Standardization Service), which standardizes and corrects addresses when it can.
• LACS (Location Address Correction Service), which changes old addresses to new ones, like rural routes to street addresses so the fire company can find them.
4. If appropriate, consider matching the names you have as well as a separate match on addresses only. This identifies whether you have the most current contacts versus address accuracy (again, according to that source).
5. SHOULD YOU FIND a significant number of your database records fall outside the income or sales (or whatever) ranges you are targeting, or if they don’t match the current-month compiler files well, you have a few choices to correct your list:
• Start from scratch and replace your list with the current-month compiler records (and, perhaps, for a small fee double verify or find unique records from the second-best source (accommodating the ever-present skews, of course)) as appropriate.
• If you buy the current-month list and wish to suppress your current list you’ll save money only buying unique records, but you won’t know how many bad records you still have in your in-house list. In order to get rid of those bad records, consider appending the least expensive data element the compiler offers before suppressing.As an example, compilers charge very little to simply flag the records that match their database or to append a simple, inexpensive data element such as zip code or zip+4. You’ll then delete the non-matching or non-appended records from your in-house files. You can send the balance back to them for suppressing when obtaining new, fresh records so you don’t pay for those you verified that you already have.
• Instead of starting from scratch or appending for deletion/suppression, etc., you may simply wish to have the compiler append the selects of interest to your in-house list. Send them your file, ask they append sales, or household income, or whatever is appropriate, and you’ll know which of your records are within your target parameters.
While we recommend always using the current-month files of Epsilon/Equifax and D&B for most purposes, you may be able to append this data element from a wholesale file at significant savings (up to 50%) and still obtain the desired results.
Beyond closings or name changes, business records change little from month to month due to the difficulty and cost of updating. If the florist had 5-employees last year the compiler won’t update that for years. If anything did change, it is likely now a 4 or 6-person florist. You can append number of employees and SIC codes from wholesale files with little risk.
Consumer records change frequently though financial demographics, such as income, are largely based on the property and that doesn’t change. You can append income from a wholesale file without much risk.
Please click below for a comparison between list sources and the services they provide.