Eight Unconventional Ways To Measure The Success Of Your Direct-Mail Campaign

Marketers want results – but more than that, marketers (or the people who write marketers’ checks) want numbers that show results.

When the tool is direct mail, the numbers would seem to be pretty straightforward, along the lines of:

• • How many people took advantage of the offer?
  • How many people called the number?
  • How many people clicked on the QR code?
  • How many people bought the product?
  • How many people mailed back the form?
  • How many people write a check?
  • How many people redeemed the coupon?

However, not every mailing is quite that straightforward – and there are many more ways of measuring the success of a direct-mail campaign than those classic fulfillment numbers.

For instance, have you ever considered the following as measures of direct-mail success:

• • Web visits by time period
  • Other web analytics
  • Survey results
  • Competitive activity
  • Product analytics changes
  • A/B test results
  • Social profile views/invites
  • Other social analytics

Those are a lot of different – and maybe even unconventional – ways of looking at direct-mail performance. They need to be examined individually.

Web visits by time period

Especially if you’re mailing locally you have a pretty good idea of when a mailing hits. While direct mail has a longer “tail” than many other types of marketing, the majority of actions will still take place in a 24-hour window right after receipt.

Google Analytics gives you all the tools you need to analyze what happens to your website’s traffic in that crucial window after a mailing was sent. You can see, among other things:

• • How many people visited your site
  • Where they came from geographically
  • The exact time of day they visited
  • Where they went on your site
  • Any conversions they made (if you have conversion tracking set up)

Looking at web behavior at time periods beyond the short window of activity after a mailing was received can also help point up any long-term changes in web behavior.

A good way of measuring this is to look at web analytics from the month before your mailing and compare it to the month after. Six months after the mailing, repeat the analysis over matching six-month periods.

For nationwide mailings where there’s a longer window of activity, measure an entire week as your “hit” period, and base your comparisons off of that. Either way, short-term and longer-term time-based measurements can give you some real insight into fundamental changes your mailing may have wrought.

Other web analytics

As long as you’re measuring changes in web behavior and activity, don’t forget to look at the activity of new users.

If you have Google Analytics set up, go into Audience>Behavior>New vs. Returning and you’ll be able to see not only the changes in the numbers of new users over time, but you’ll be able to drill into those new visitors and see where they go, what they do, and whether they convert.

Start the measurement on the day you think your mailing hits and track it over at least a 30-day period. This will tell you the impact of your mailing on web behavior, especially as it affects those all-important new customers.

Sure, someone clicking on a QR code is awesome … but people visiting your site and scouting around is pretty important too.

Survey results

There aren’t a lot of direct-mail campaigns that merit their own followup survey, but regular brand surveys are a great idea, no matter the size of your business.

You should always be benchmarking your brand awareness and brand favorability, and one component of that is measuring the effectiveness of your promotional efforts.

It is absolutely acceptable, and a great idea, to survey customers and other audiences about whether they saw your mailing, and what they thought of it.

You can then analyze brand-favorability and brand-awareness scores by people who saw your mailing and people who didn’t, and look for differences.

Is it important if people who saw your mailing like your company or brand better than those who didn’t? Absolutely. So set up a survey and ask the question.

Competitive activity

This one’s pretty simple: After you do a mailing, does your competitor do a mailing too? Is the offer similar? Does it seem like they’re sending to the same people, using a similar call to action, or otherwise copying you?

Gathering competitive intelligence can be a catch-as-catch-can process. If you’re part of the target audience, mailings may just come to you; otherwise, if you’re in the financial, healthcare, or insurance sector, consider using a tool like Competiscan to get a handle on what your competition is up to.

Product analytics changes

Sales is the ultimate arbiter of many product-based direct-mail campaigns, but there are many other changes in product dynamics that can indicate a successful mailing.

For instance, if you’re promoting a consumer packaged good, sell-in (wholesale sales) may not increase, but sell-through (retail sales) might. You may also see more interest across your product line after a promotion focused only on one product. It’s also possible (though not easy to measure) that your product may receive more favorable shelf placement after a promotion.

If you’re promoting a product via direct mail, it’s important to have as clear a picture as possible of your product before the promotion starts so you can compare its post-promotion status.

Again, if your direct-mail campaign improves product-related behaviors that aren’t sales, that’s still great – because sales are almost sure to follow.

A/B results

If you’re not A/Bing the behaviors of the people who didn’t receive your mailing versus the behaviors of the people who did, or people who received one version of a mailing versus people who received a different mailing … you really should.

We all like to think we know our customers implicitly, but we’d all be better off if we walked around wearing T-shirts that read, “I am not the target audience.”

Our customers are not ourselves. We need to assume we don’t know our customers as well as we think we do, and test multiple messages with our audiences.

Sometimes it’s as simple as not mailing to a portion of our customer base and watching them to see if they behave differently than the audience that received the mailing.

Remember, A/B tests need to be as neutral as possible, and you need to be as dispassionate as possible when considering the results. The data is the data, let it speak, and believe it.

Social profile views/invites

Post-mailing, are more people checking out your company’s profile on LinkedIn or Facebook, or are more people sending you LinkedIn invites? Seems pretty basic, but it’s one of the most direct ways of seeing a mailing’s impact on brand.

As with so many other metrics we’ve talked about, it’s important to understand your numbers before the mailing so you can properly identify significant changes.

It’s also important to have a plan in case social numbers spike. It could be a stronger move into paid social, or more social video to engage new visitors. You may never launch the plan, but you should at least have it ready to go – just in case.

Other social analytics

You should be measuring a raft of social analytics, including impressions, engagements, reach, favorability, and so forth. All of them are constantly changing, so one more time, benchmark before your mailing starts and compare and contrast your key social measurements over similar periods pre- and post-mailing.

More advanced analytics or competitive analysis might require a tool like Sprout Social, but you can learn a lot through the platform analytics provided by Facebook, Instagram, and even Twitter.

No matter how you choose to measure your direct-mail campaign, keep your eyes on the $100,000 question(s): what changed, and why, and when … and can we attribute any of it to the campaign?

Here’s hoping all your changes are positive.

 

By Jim Felhofer 12/02/21