How to Increase Your Direct Mail Response Rate
Although the average direct mail response rate is between just 1%-3%, this form of marketing is still one of the most effective tools available at your disposal. Sure, 3% sounds like a low number, but if you can get 30 responses from 1000 mailers, you can get an impressive return on your investment.
Of course, you’ll never earn that 3% response rate if you don’t understand what it takes to get someone to open, read, and act upon your sales letter. Here are some tips I’ve come up with to increase the response rate to your direct mail campaign.
• Hand write addresses—Your first goal is to have your letter stand apart from all the junk mail your recipients receive on a daily basis. Did you know about 44% of direct mail ends up in the trash can unopened? So, above all else, that letter needs to get opened. One of the best ways to do this is to add a personal touch to it. You don’t want it to look like junk mail or an advertisement. Hand writing the addresses on your envelopes makes them feel more personal and friendly.
• Use normal stamps—Another way to add a personal touch to your letters is to use actual postage stamps rather than postage meters that are commonly used for mass mailings. Sure, it might take a bit longer to stamp each envelope, but it will instantly separate your mailer from the rest.
• Offer irresistible freebies—People need an incentive to get off their butt and take the time to respond to your direct mail piece. It all boils down to answering the all-too-familiar question of “What’s in it for me?” Offer your customers a free gift card or a free sample of a product for responding to your offer. The more incentive someone has to act, the likelier it is that they’ll do it.
• Try buy one, get one free offer—72% of adults with a household income of $30,000 or less said they responded to direct mail that contained a buy one, get one free offer. If you have a product or service where it makes sense to try this offer, give it a shot. It could boost your direct mail response rate significantly.
• Create a landing page—A growing number of consumers prefer to respond online to direct mail pieces rather than by mail or phone. This means you need to provide your readers with this option, and sending them to your home page isn’t enough. Think of direct mail like a PPC or email marketing campaign; specific landing pages are necessary for earning the best response rate. Some direct mail experts even suggest using personalized urls for direct mail letters (e.g. JoeSmith.yourdomain.com).
Do you use direct mail marketing? What have you done to increase your conversion rate? Leave a comment with your best tips.
January 12th, 2010 at 2:22 am
Scoring a prospect database enables a direct marketer to significantly reduce unprofitable marketing communications. Predictive models often use regression based statistics to calculate the probability that a prospect belongs to a group, e.g., buyer vs. non-buyer. There are several statistical techniques including discriminant analysis, neural net, and logistic regression used as predictive models. The modeling technique we typically use is discriminant analysis, which is basically a type of multiple regression in which the dependent variable is categorical data representing group membership (buyer vs. non-buyer). The predictor variables can be anything: an account’s past purchases (recency of purchase, value of purchase), age, income, life-stage group, NAICS/SIC codes (for B2B), home type, ownership of similar products; recoding these variables as dummy variables (1 and 0’s to indicate if the prospect is or is not a member of the group) represents >90%of the time required to build a predictive model. (You'll need a statistical software package like SPSS or SAS to do this.)
When the discriminant model is run various outputs are provided including the percentage of prospects who were correctly assigned and, most importantly, a “structure matrix” which shows which variables are correlated most highly with group membership. Because we use the analysis to create lists for direct mail, or outbound telemarketing, we are primarily interested in the probability of buying the product or service we are marketing. Separate models are created for each product. By sorting records from highest probability score to lowest and converting each decile’s average probability score to an average sales rate (based on a small pilot campaign or recent history), we can estimate the number of new buyers that will result from a direct mail, e-mail or telemarketing campaign and the acquisition cost associated with each decile.
While models based on data for zip codes areas are less precise than models built on block group or household specific data, significant amounts of geo-demographic data can be downloaded FOR FREE from government sources such as the US Census bureau and NOAA (for weather data). Household specific demographic and life stage segment data from firms like Acxiom, Equifax, etc. significantly improve model accuracy but at a higher cost.
For more information, I recommend you get one of David Shepard Associates' excellent books on this subject, take one of his seminars (through DMA), or visit my site at ericnovakandassocaites.com.