Direct Mail KPIs: How To Analyze Direct Mail Results Using 5 Key Metrics

As the leading direct mail automation platform, we spend a lot of time analyzing direct mail metrics and KPIs to deliver a state-of-the-art experience for marketers.

And the question that comes up often is, “can I just skip analyzing direct mail results? Isn’t it good enough to work from your gut feeling?

This reminds me of an old joke that goes something like this: “I know I’m wasting half of my marketing budget. The trouble is, I don’t know which half.”

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Measuring the right KPIs is what separates struggling from best-in-class marketers.

But why? Because direct mail is so effective nowadays because you can easily target prospects with pinpoint precision while tracking delivery and response to each mailing. With that detailed level of data, you have access to essential information that can help you focus more of your marketing budget on your most likely prospects — and eliminate the high cost of targeting prospects unlikely to become a customer.

Other media doesn’t offer such precision. For example, with online advertising you can measure clicks, but with click fraud on the rise, you are never really sure if your numbers are accurate. Other offline media such as TV, radio and print give you estimated impressions, and not much more.

Modern automation tools give you direct mail results that are laid out in real time, easy to digest dashboards, with detailed delivery and response data captured at the individual recipient, as well as campaign level.

Turning data into insight: Specific KPIs to analyze direct mail results

Direct marketers use a variety of key performance indicators (KPIs) to track results. Here are a few of the most common ones marketers use, how to calculate them, and how to use them to analyze results. All are based on the use of some trackable code in your mailing. This can take the form of a personalized URL, special offer redemption code, or other personalized response device so you can be clear exactly who responded.

For example, this postcard for an organic makeup online retailer includes a unique code for responding to a special offer — buy two get one free.

The incentive for using the code at all is that it’s required to take advantage of the offer, an essential component of any direct mail package in part because it helps you capture key data.

Once you gather your results, you can use a variety of metrics to help you analyze direct mail results.

Response rate: Simple direct mail outcome calculation

The recent surge in direct mail marketing is being driven by the recognition that response rates are high, especially compared to standalone email campaigns.

Response rate is probably the most common way to analyze direct mail results, most likely because it’s the easiest one to evaluate. Simply divide the quantity you mailed by the number of responses received. For example, if you sent 10,000 pieces and received 300 responses, your response rate is:

300 / 10,000 = .03 or 3.00%

A deeper view of specific response rates offers a lot more insight. Most direct marketers test a variety of attributes: lists, creative, format, and offer to name a few. And you can calculate response rates for each attribute you test.

Let’s say you run a grocery store that offers delivery service and you want to test two offers. One for a first delivery free and another offer that’s a bit more enticing, first delivery free and $10 off a first order. If your 10,000-piece mailing was split in half to test these two offers, you might find that response rates for each test were quite different:

Offer	First delivery free	First delivery free plus $10 discount	Total
Mailing quantity	5,000	5,000	10,000
Responses	100	200	300
Response rate	2.00% (100/5,000)	4.00% (200/5,000)	3.00% (300/10,000)

Here we can see that while the entire mailing delivered a 3% response rate, that was the average between one test cell that brought in twice the response (4%) as the other test cell (2%).

Conversion Rate

While certainly relevant, response rates alone do not completely measure direct mail results. After all, a free trial offer won’t be successful in the long run if those who respond do not convert into customers. So you can use another metric, the conversion rate, to give you more perspective on direct mail performance.

Indeed, high response rates mean little if few convert into customers. A lower response rate might be more successful if a larger number actually become paying customers.

You’ll need to define what a “conversion” actually represents. In this example, let’s assume that a conversion is defined as a prospect who signed up for the service after receiving the initial offer and then agreed to pay the full price for a second order.

If in this example 150 prospects were so impressed with the service that they agreed to pay for at least a second delivery, that would mean that half of the respondents to your initial mailing converted. To calculate the conversion rate, you simply divide the number of prospects who converted by the responses you received to your initial mailing:

150 conversions / 300 responses = 0.50 or 50%

But you should definitely dig a bit deeper into your conversion rate because those rates may be higher or lower based on variables you might test. In this case, two offers were tested.  The conversion rate for each may have been quite different, perhaps as shown here – a 50% conversion rate overall but one group converting at a rate much higher than the other:

Offer	First delivery free	First delivery free plus $10 discount	Total
Mailing quantity	5,000	5,000	10,000
Responses	100	200	300
Response rate	2.00% (100/5,000)	4.00% (200/5,000)	3.00% (300/10,000)
Conversions	80	70	150
Conversion rate	80% (80/100)	35% (70/200)	50% (150/300)

You can see that while the most appealing offer got more responses, the conversion rate was only half that of the other offer. This demonstrates that sometimes sweetening your offer too much may actually negatively impact results. It also reveals that reviewing response rates alone doesn’t give you the full picture of how to analyze your direct mail results.

Cost per response and cost per conversion

Ultimately, allocating your budget most effectively depends on your revenues (and profit, of course) – and what it actually cost you to deliver those direct mail results.

Let’s assume that in this example, the mailing costs totaled 80 cents per piece – or $8,000 for a 10,000-piece mailing. To calculate cost per response, divide that cost by the number of responses. Overall for this example, the cost per response was almost $27 each:

$8,000 mailing cost / 300 responses = $ 26.67

Yet given that the response rate to each offer was different, the cost per response varied as well:

Offer	First delivery free	First delivery free plus $10 discount	Total
Mailing quantity	5,000	5,000	10,000
Cost (at 80 cents each)	$4,000	$4,000	$8,000
Responses	100	200	300
Response rate	2.00% (100/5,000)	4.00% (200/5,000)	3.00% (300/10,000)
Cost per response	$40 ($4,000/100)	$20 ($4,000/200)	$26.67 ($8,000/300)

As you can see, the more appealing offer generated responses at half the cost as the other offer.

But remember, the conversion rate for that more enticing offer was not as high. You’ll see that when you calculate the cost per conversion, which is the cost of the mailing divided by the number of conversions. For the entire mailing, the cost per conversion was just over $53 each:

$8,000 mailing cost / 150 conversions = $ 53.33

Once again, however, response and conversions varied by offer so the cost per conversion outcome varied as well:

Offer	First delivery free	First delivery free plus $10 discount	Total
Mailing quantity	5,000	5,000	10,000
Cost (at 80 cents each)	$4,000	$4,000	$8,000
Responses	100	200	300
Response rate	2.00% (100/5,000)	4.00% (200/5,000)	3.00% (300/10,000)
Cost per response	$40 ($4,000/100)	$20 ($4,000/200)	$26.67 ($8,000/300)
Conversions	80	70	150
Conversion rate	80% (80/100)	35% (70/200)	50% (150/300)
Cost per conversion	$50.00 ($4,000/80)	$57.14 ($4,000/70)	$53.33

The difference in the cost per conversion between each offer doesn’t seem too wide, but in this example, the total cost of mailing and fulfilling the offer were different. That brings us to another key indicator we need to consider – cost per acquisition — what it costs to acquire a customer.

Cost per acquisition: Direct mail results that measure customer growth

So far, the direct mail outcomes in this example considered the costs of the direct mail, but not the cost of fulfilling the offer.

If it costs more to make a more appealing offer, the cost to acquire a customer may be higher. Once again, if a new customer is defined as a prospect who ordered again at least one more time, then it’s necessary to evaluate the total cost – marketing and fulfilling the offer – to decide if your direct mail program is meeting expectations.

In this example, we’ll assume that offering a free delivery costs $10 and, of course, the addition of a $10 discount for the second offer adds yet another $10 to the cost of fulfilling that offer.  For this example 100 respondents received a free delivery which cost $1000 ($10 x 100). Another 200 respondents received both a free delivery and a $10 discount, each costing $20 for a total of $4000 ($20 x 200). All of these expense plus the cost of the mailing itself totals $13,000.

To calculate cost per acquisition, divide this total cost by the number of customers acquired (or conversions):

$13,000 total cost (mailing and offer fulfillment) / 150 customers acquired = $ 86.66

Count All Expenses

For the entire campaign, accounting for mailing and fulfillment expenses, the cost per acquisition was about $87 each, but of course, each offer performed differently. Here’s a summary view of all of these key performance indicators – with the cost per acquisition in the last row of the table:

Offer	First delivery free	First delivery free plus $10 discount	Total
Mailing quantity	5,000	5,000	10,000
Responses	100	200	300
Response rate	2.00% (100/5,000)	4.00% (200/5,000)	3.00% (300/10,000)
Cost per response	$40 ($4,000/100)	$20 ($4,000/200)	$26.67 ($8,000/300)
Conversions	80	70	150
Conversion rate	80% (80/100)	35% (70/200)	50% (150/300)
Cost per conversion	$50.00 ($4,000/80)	$57.14 ($4,000/70)	$53.33 ($8,000/150)
Mailing cost (at 80 cents per mailing)	$4,000	$4,000	$8,000
Offer fulfillment cost ($10 per delivery and $10 per discount given)	$1,000 ($10 x 100)	$4,000 ($20 x 200)	$5,000
Total cost	$5,000	$8,000	$13,000
Cost per acquisition	$62.50 ($5,000/80)	$114.29 ($8,000/70)	$86.67 ($13,000 / 150)

Now the analysis can really begin: Is $114 or so worth acquiring a new customer? Is $62.50 too much? Ultimately that depends on your profit margin and additional repeat business you might expect from customers acquired through direct mail.

Lifetime value

An ongoing business that could last for years could spend $200 or more to acquire a customer. But to decide whether that’s profitable, there are another direct mail results metric to consider – the lifetime value of a customer. That depends on many variables and will be the subject of one of my future posts.

Meanwhile, you can see that however you measure direct mail performance, if you’re testing offers, lists, creative execution, and formats, a review of each test cell helps you decide which strategies and tactics actually work best – and provides information that’s far more valuable than overall response alone.

Check out Postalytics

Postalytics is the leading direct mail automation tool designed to help marketers:

• speed up direct mail production with triggered and quick turn batch campaigns
• integrate direct mail with email & digital via CRM and Marketing Automation
• measure, track and analyze direct mail outcomes for both delivery and response

Postalytics offers a free plan, along with subscriptions for marketers that want to scale their marketing.