Direct mail marketing campaigns are built around results. That’s why direct mail data is everything when it comes to your print marketing efforts. So how do you evaluate and learn from the outcomes of each campaign? By analyzing four key elements. Here’s how you can apply data management for direct mail success.


1. Direct Mail Data: Response Rate


direct mail response rateAs its name suggests, your response rates for direct mail refer to those recipients on your mailing list who respond to your direct mailing. Studies show that the average response rate for a company’s “house list” is an impressive 9%. These are your people, so it’s more likely that they’ll be responsive to your message. If, however, you rent a list, you can expect a slightly lower response rate of about 5%. Of course, your numbers will vary based on your industry, type of business, product/service, etc.


Data Management for Direct Mail: Calculating Response Rate


Now that you know the general information about response rates, let’s do a bit of figuring so you can track your direct mail marketing metrics. You simply divide the number of responses you received by the total number of direct mail pieces you sent. Let’s look at an example. Let’s say you sent out a 25,000-piece mailing from a rented list and you received 1,200 responses. Your response rate would be 0.048%. That’s pretty close to the average for this type of list.


Naturally, you may be wondering what a “response” actually means. Well, it depends on what you request with your call to action (CTA). Here are some of the most popular and effective ways to monitor your direct mail campaigns.


Promo Code


For each campaign, include an obvious, exclusive promotional code. This is the best way to follow your responses using data management for direct mail—whether a recipient is calling you, visiting your website, or visiting a retail location. In any instance, they should mention the promo code from the mailing to receive the benefit. Each time the promo code is recorded, that’s a response.


Phone Number


A dedicated phone number is also a great way to measure your response rate. With this method, all calls to that number reference a specific campaign. There’s no need to ask for promo codes (unless you want to) to identify the calls, though. It’s as simple as setting up a specific phone number that forwards to your primary business line. You’ll determine your response rate by the number of calls to that dedicated number. The only drawback is you’ll need to staff the line to handle the calls.


QR Code


Include a QR code and add it to your direct mail piece. (It’s probably wise to add a few words near it with simple instructions like: Scan this with your smartphone.) When people take a picture of it, they arrive at a unique landing page for the campaign. From there, you can check the direct mail data from your website stats to view the number of visitors you had and what they did when they arrived at the page. Savvy marketers will create a unique QR code for each recipient. When the code is scanned, you’ll have real-time information that connects the recipient to your campaign. Then you’ll know who “responded.” It’s achieved via variable data printing, aka VDP. At MSP, our state-of-the-art printers process a unique QR code from your database of recipients that changes for each mailpiece printed. Each recipient has their own QR code.


Landing Page URL


Print a landing page URL on your direct mail piece. Why is this a good idea when they can just scan a QR code? This form of personalization (also known as a PURL) works because people like seeing their names in print. When you add someone’s name to your brand’s URL (Eg., they feel like they’re part of your campaign—that they have their own presence within your brand. It’s a powerful inclusion, plus you can track it like you would a QR code. Still, this method is becoming less popular because recipients have to physically type the URL into a web browser. But it’s something to consider when you’re assessing who your audience is. Do the majority have smartphones? Do they use their smartphones to regularly scan codes and augmented reality? It goes back to understanding your audience and what they like.


2. Direct Mail Data: Cost per Acquisition


cost per acquisitionMaybe you’re getting new customers (that’s great), but what is it costing you to get those new patrons? You need to determine your cost per acquisition to see if the success you’re experiencing is truly successful. With this information, you can compare your direct mail data across all your marketing channels to prove what’s most successful—direct mail, email, print ads, pay-per-click, social, etc.


Data Management for Direct Mail: Calculating CPA


To figure out your CPA, take the total cost of your campaign and divide it by the total number of orders you received. Let’s go back to our previous example, the 25,000-piece mailing. In this instance, it isn’t necessary to know the number of mail pieces, but you will need to know the total cost of the campaign and how many responses you received. So we’ll come up with a random number. Let’s say you spent $20,000. We know you had 1,200 responses, so let’s just say there were 750 orders. The CPA would be $26.67 (rounded off). This is very close to the direct mail average of $26.40.


Keep in mind, you might have a higher CPA for direct mail than other marketing channels. But you’ll also likely have better response rates and ROI. The benefits usually far outweigh the additional expenses over other marketing channels.


3. Direct Mail Data: Customer Lifetime Value


customer lifetime valueIf your brand is like so many others, you’re probably spending 5-25x more to find new customers than to concentrate on keeping your current ones. Of course, it’s always important to seek out new customers via your marketing campaigns, but never at the cost of your current patrons. Don’t alienate them by ignoring their needs. Remember, if you don’t keep your current customers happy, there’s another brand that will.


Calculating your customer lifetime value (CLV) is somewhat more complex than the previous examples. But it’s an important chunk of direct mail data to measure. Your CLV uncovers the amount of profit you can expect from a customer during their lifetime with your brand. The longer a customer keeps buying from your company, the higher their CLV. In essence, you’re looking at the value of a customer’s revenue and comparing it to your brand’s predicted customer lifespan. Many brands use CLV to signify their most valuable segment of customers.


Bottom line: you want to serve your current customers with the products and/or services they like so they’ll continue to spend more money with your brand.


Data Management for Direct Mail: Calculating Customer Lifetime Value


The easiest method of calculating a customer’s lifetime value is to take the average purchase value and then multiply it by the average number of purchases. Once you have your average customer lifespan, you can multiply it by the customer value to arrive at the CLV.


It’s marketing science and it looks like this:


  • Customer Lifetime Value = Customer Value x Average Customer Lifespan
  • Customer Value = Average Purchase Value x Average Number of Purchases


Let’s examine a hypothetical example, inspired by a real-world study from Kissmetrics and HubSpot to fill in these amounts. We’re going to measure the purchasing habits of five of your customers to arrive at your customer lifetime value.


Average Purchase Value


Let’s say you have a franchise restaurant business with locations across the U.S. Your average customer buys from one of your locations 4x per week and spends $12. (They’re slightly addicted. Good for you.) Your average purchase value would be $3. Once you have the average purchase value for one customer, you repeat the process for the other five. Then you add each average together and divide it by the five customers surveyed to arrive at the average purchase value.


Average Purchase Frequency Rate


How many visits does your average customer make per week? We’re going to set that at four visits per week. So 4x is the average purchase frequency rate each week.


Customer Value


We know how much a customer spends and how often they visit, right? So now we have enough information to find the average customer’s value. So the next step is to multiply the average purchase value of all five customers by their average purchase frequency rate. This will tell you how much they’re worth per week.


Average Customer’s Lifetime Span


If you want to calculate your average customer’s lifetime span, you’d have to look at the number of years each person has been a customer. Then you can average the values together. In the Kissmetrics example, they listed the customer value at 20 years. If your brand doesn’t have 20 years of direct mail data to work with, you can estimate your customer lifetime span by dividing one by your churn rate percentage.


Customer’s Lifetime Value


Finally, we’ve arrived at the number we set out to discover in the first place—customer lifetime value.  Start by multiplying the average customer value by 52. (We measured weekly habits so that’s why we’re using 52 to get the annual average.) Then multiply that number by the customer’s lifetime span to get your customer lifetime value.


The important thing to remember is you don’t need to frustrate yourself with lots of calculations. CLV is very useful as direct mail data. But the most important thing to understand is the value a customer provides over their lifetime relationship with you. Focus on retaining them via all your marketing channels. Improve your customer’s onboarding experience. Underpromise and overdeliver. Complement your products and services with more relevant products and services. (Would you like fries with that?) Build your relationships with your customers and make sure your customer service experience is second to none.


4. Direct Mail Data: Return on Investment


direct mail ROIFinally, we have the vital direct mail data that shows you whether your campaign was financially successful or not. It’s your return on investment (ROI). According to studies, the average ROI for a direct mail campaign is somewhere in the 18-20% range, so you can use those figures to compare your business’s success. At least it gives you something to shoot for if you haven’t sent a lot of direct mail campaigns.


Data Management for Direct Mail: Calculating ROI


To arrive at your all-important return on investment figure, subtract the money you spent on your campaign from your total revenue. Simple, right? Then, divide that number by the campaign cost (yes, that same number again). Here’s an example. If you made $8,000 on a campaign and you spent $6,500, your number would be $1,500. Now take that number ($1,500) and divide it by $6,500. You’d have an ROI of 23%, which is a little above the industry average. Well done!


Analyze Your Direct Mail Data with MSP’s Direct Mail Panorama


The best way to analyze your direct mail data is with the help of the industry’s most revolutionary software system: MSP’s Direct Mail Panorama. This innovative data management for direct mail program will give you more control over and a better understanding of your direct mail marketing campaigns. You’ll integrate every element of your direct mail marketing efforts from start to finish. Plus, you’ll have a “panoramic” view of all your direct mail data. This allows you to improve from one campaign to the next with reduced management time and improved speed to market. Contact an MSP representative to talk about how we can help you analyze your direct mail data like never before.

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