Determining Who Will Respond to a Direct Mail Offer

By identifying the prospects who are most likely to respond to an offer, you can reduce campaign expenses and improve your response rate and ROI.

Every direct mail piece you send costs money. Beyond the initial design and data mining expenses, each individual letter costs money to print and postage to mail. That’s okay because more direct mail campaigns have a high return on investment, but there are ways to cut down on wasted mail to reduce costs to achieve a better response rate.

By only sending direct mail material to consumers who are more likely to respond or make a purchase, you reduce the number of letters printed and sent without hindering the quantity of responses.

Here are three steps you can use to determine which prospects are most likely to interact with your marketing material so you can target accordingly.

1. Run the direct mail numbers

The efficiency of direct mail campaigns can vary greatly depending on what you’re selling or the goals you’re trying to achieve.

According to research initially conducted by the Data and Marketing Association (now part of the Association of National Advertisers), direct mail gets a 5.1% response rate per household.

While the specific rate can vary based on your industry and the type of direct mail material you’re sending — oversized direct mail has a response rate of 6.6% — there are always strategies you can implement to improve the performance of your company’s mail over its competitors.

For example, if you usually send out 100,000 pieces and end up with a 1.2% response rate, that’s 1,200 leads with which to work. If you’re able to send 75,000 pieces and still receive 1,125 responses, that gives you a 1.5% response rate with an improved ROI. If each letter costs you 35 cents to send, you could save $8,750 in this scenario.

The success of this situation depends on how much those 200 fewer responses might have spent if they did respond. If the anticipated sales form that group would be less than $8,750, you’ve found a way to make your next campaign more efficient.

Keep in mind that those savings can be reinvested into more targeted mailing at a higher ROI. The point is not to cut mailing overall, but to focus your investment on the people one your lists who are most likely to pay off.

Direct mail is a numbers game. By analyzing your data and figuring out how to achieve a similar volume of responses while reducing your mailings, you stand to make more money. Calculate your ROI now using our Direct Mail Calculator.

2. Dig into your deep customer data

As you move forward with tracking response rates and building better prospect models, these efforts will compile a ton of data that can be used to make future mailings more efficient.

Going through that data manually is next to impossible because there’s so much of it, which is why it’s a good idea to develop an algorithm to assist with the process. Direct mail data is every bit as rich as Big Data, and there are profits to be found by exploring it with the latest data science methods.

Each prospect on your mailing list has displayed past behaviors that are likely to predict their future actions. Using data science, we can develop an algorithm to identify factors that make it unlikely for a particular consumer to respond to your next offer and remove that person from the mailing.

For example, data might suggest that some customers on your list won’t act unless an offer includes a discount of over 25%. If you’re currently sending a coupon for a 15% discount, you might want to exclude households who normally hold out for a better deal.

You can also break your mailings down by geographic or demographic information. If a particular age group or location hasn’t responded favorably to a specific type of offer in the past, sending more pieces, particularly in mass amounts, might not provide the best return.

If customers in a particular age group or location reacted favorably to your last 15% off campaign, concentrate your resources on those people to maximize your return.

Remember, the more data you collect and the more testing you do, the more success you’ll find.

3. Modify your mailing list

The great thing about today’s direct mail is that almost everything can be automated. In the past, you might have had to go through every piece of data individually and manually remove specific people from a mailing, but that’s no longer the case.

By developing an algorithm to skip recipients that meet specific criteria, you can automate this process, improving overall direct mail ROI with minimal additional investment.

Gunderson Direct is available to assist you in compiling and analyzing this kind of data. We’ll help you determine the most efficient ways to analyze and optimize your direct mail campaign and identify the best path forward for each offer you’re presenting. Visit our contact page to learn more or to begin your first campaign.