## Marketers, How Valid Is Your Test? Hint: It’s Not About the Sample Size

The validity of a test is not tied to the size of the sample itself, but rather to the number of responses that you get from that sample. Choose sample sizes based on your expected response rate, not from tradition, your gut or convenience.

A client I worked with years ago kept fastidious records of test results that involved offers, lists, and creative executions. At the outset of our relationship, the client shared the results of these direct mail campaigns and the corresponding decisions that were made based on those results. The usual response rates were in the 0.3 to 0.5% range, and the test sample sizes were always 25,000. If a particular test cell got 130 responses (0.52%), it was deemed to have beaten a test cell that received 110 responses (0.44%). Make sense? Intuitively, yes. Statistically, no.

In fact, those two cells are statistically equal. With a sample size of 25,000 a 0.5% response rate, your results can vary by as much as 14.7% at a 90% confidence level. That means that there was a 90% chance that the results from that test could have been as much 0.55% or as little as 0.43%, making our test cell results of 110 responses (0.44%) and 130 responses (0.52%) statistically equal. I had to gently encourage the client to consider retesting at larger sample sizes.

There are statistical formulas for calculating sample size, but a good rule of thumb to follow is that with 250 responses, you can be 90% confident that your results will vary no more than +10%. This rule of thumb is valid in any medium online or offline. For example, if you test 25,000 emails and you get a 1% response rate, that’s 250 responses. Similarly, if you buy 250,000 impressions for an online ad and you get a 0.1% response rate, you get 250 responses. That means you can be 90% confident that (all things held equal) you will get between 0.9% and 1.1% in the email rollout,  and between 0.009% and 0.01%, with a continuation of the same ad in the same media. (Older editions of Ed Nash’sDirect Marketing — Strategy, Planning, Execution contain charts that you can reference at different sample sizes and response rates).

A smaller number of responses will result in a reduced confidence level or increased variance. For example, with a test size of 10,000 emails and a 1% response rate (100 responses), your variance at a 90% confidence level would be 16%, rather than 10%. That means you can be 90% confident that you’ll get between 0.84% and 1.16% response rate  with all things being held equal. Any response within that range could have been the result of variation within the sample.

Marketers are not alone in using their gut rather than statistics to determine sample sizes. Nobel Laureate Daniel Kahneman confesses in his book “Thinking, Fast and Slow“:

“Like many research psychologists, I had routinely chosen samples that were too small and had often obtained results that made no sense … the odd results were actually artifacts of my research method. My mistake, was particularly embarrassing because I taught statistics and knew how to compute the sample size that would reduce the risk to an acceptable level. But I had never chosen a sample size by computation. Like my colleagues, I had trusted tradition and my intuition in planning my experiments and had never thought seriously about the issue.”

The most important takeaway here is that the validity of a test is not tied to the size of the sample itself, but rather to the number of responses that you get from that sample. Choose sample sizes based on your expected response rate, not from tradition, your gut or convenience.

## How to Take Your Direct Mail List Targeting to a New Level

There are some new technologies out there that can help you better define your direct mail targeting by adding attitudinal data. What is attitudinal data? It is the attitudes, preferences, motivations and beliefs that are behind the consumer decisions driving response. When you are able to add this to your list, you can really drive response.

Your direct mail list targeting is extremely important. The better you are able to target the right people, the better your response rate will be. There are some new technologies out there that can help you better define your targeting by adding attitudinal data. What is attitudinal data? It is the attitudes, preferences, motivations and beliefs that are behind the consumer decisions driving response. When you are able to add this to your list, you can really drive response.

Consider this, if you’re trying to drive donations or acquire new members, you will want to identify potential donors who are highly predisposed to your specific cause and likely to donate regularly. You can also find people who are attracted to your specific campaign message and have the highest propensity to respond. Just because two people might look the same based on demographics and behavior does not mean they are. Let’s say you have two people who live in the same neighborhood, drive the same type of car, are in the same income bracket and have kids under 10. Traditionally, these people are sent the same message and expected to respond the same way. However, consider that they are individuals and may not find the same creative attractive. They also do not share the same motivations, or like the same offers or causes.

Check out these list targeting options:

## Standard List Rental

How it works:You already know your customers’ demo or behavioral profile, so you buy a list that matches that profile (Women aged 25-45 with children at home & HHI \$80k+).

Why you’d use it: It’s cheaper, it’s simpler, and that really matters to you.

## Syndicated Lifestyle Segments (e.g., Claritas, Mosaic)

How it works: You match your customer file to syndicated lifestyle segments to provide broad demo, behavioral, lifestyle and attitudinal profiles.

Why you’d use it: Superior to standard list rentals for most applications, and provides valuable profiling insights on your customers.

## Standard Response Model

How it works:You match your customer file to a consumer database, and your analytics provider builds a custom response “look-alike” model to find consumers with similar characteristics to people who’ve responded in the past.

Why you’d use it: You want to reliably and consistently repeat your past success.

## Custom Attitudinal Modeling (e.g., Twenty-Ten)

How it works: Matches your responder file to a custom consumer attitudes database and builds a customer hybrid attitudinal/behavioral model that identifies consumers most likely to have the attitudinal predisposition to respond to your ad.

Why you’d use it: You want to build on past successes and realize significant improvement in targeting accuracy.

The ability to differentiate between people and only send your mailer to the person most likely to donate or purchase from you will significantly increase your campaign response and ROI. The same thing applies if you are selling products or services.

One of the common misconceptions about data targeting is that it is expensive. When you consider the lift you can get with targeting accuracy that increases your results, you can find that it more than pays for itself. So whether you choose syndicated segments from Claritas, or purchase intent data from Experian, including this additional layer to your list creation will help you optimize targeting, increase campaign engagement and boost response.

Marketers have considered it hard to budget for new list testing. However, with the right vendors, you can try out altitudinal data with a test run at no cost. The typical response increase with custom attitudes in your direct mail targeting is 20% to 80%. Are you ready to get started?

## Marketing Success Metrics: Response or Dollars?

It’s tempting to ask about whether marketing success metrics should be response rates or money. But you don’t need to ask marketers what they want. Basically, they want everything.

It’s tempting to ask about whether marketing success metrics should be response rates or money. But you don’t need to ask marketers what they want. Basically, they want everything.

They want big spenders who also visit frequently, purchasing flagship products repeatedly. For a long time (some say “lifetime”). Without any complaint. Paying full price, without redeeming too many discount offers. And while at it, minimal product returns, too.

Unfortunately, such customers are as rare as a knight in white armor. Because, just to start off, responsiveness to promotions is often inversely related to purchase value. In other words, for many retailers, big spenders do not shop often, and frequent shoppers are often small item buyers, or worse, bargain-seekers. They may just stop coming if you cut off fat discount deals. Such dichotomy is quite common for many types of retailers.

That is why a seasoned consultants and analysts ask what brand leaders “really” want the most in marketing success metrics. If you have a choice, what is more important to you? Expanding the customer base or increasing the customer value? Of course, both are very important goals — and marketing success metrics. But what is the first priority for “you,” for now?

Asking that question upfront is a good defensive tactic for the consultant, because marketers tend to complain about the response rate when the value target is met, and complain about the revenue size when goals for click and response rates are achieved. Like I said earlier, they want “everything, all the time.”

So, what does a conscientious analyst do in a situation like this? Simple. Set up multiple targets and follow multiple marketing success metrics. Never hedge your bet on just one thing. In fact, marketers must follow this tactic as well, because even CMOs must answer to CEOs eventually. If we “know” that such key marketing success metrics are often inversely correlated, why not cover all bases?

Case in point: I’ve seen many not-so-great campaign results where marketers and analysts just targeted the “best of the best” segment — i.e., the white rhinoceros that I described in the beginning — in modeled or rule-based targeting. If you do that, the value may be realized, but the response rate will go down, leading to disappointing overall revenue volume. So what if the average customer value went up by 20%, when only a small group of people responded to the promotion?

A while back, I was involved in a case where “a” targeting model for a luxury car accessory retailer tanked badly. Actually, I shouldn’t even say that the model didn’t work, because it performed exactly the way the user intended. Basically, the reason why the campaign based on that model didn’t work was the account manager at the time followed the client’s instructions too literally.

The luxury car accessory retailer carried various lines of products — from a luxury car cover costing over \$1,000 to small accessories priced under \$200. The client ordered the account manager to go after the high-value target, saying things like “who cares about those small-timers?” The resultant model worked exactly that way, achieving great dollar-per-transaction value, but failing at generating meaningful responses. During the back-end analysis, we’ve found that the marketer indeed had very different segments within the customer base, and going only after the big spenders should not have been the strategy at all. The brand needed a few more targets and models to generate meaningful results on all fronts.

When you go after any type “look-alikes,” do not just go after the ideal targets in your head. Always look at the customer profile reports to see if you have dual, or multiple universes in your base. A dead giveaway? Look at the disparity among the customer values. If your flagship product is much more expensive than an “average” transaction or customer value in your own database, well, that means most of your customers are NOT going for the most expensive option.

If you just target the biggest spenders, you will be ignoring the majority of small buyers whose profile may be vastly different from the whales. Worse yet, if you target the “average” of those two dichotomous targets, then you will be shooting at phantom targets. Unfortunately, in the world of data and analytics, there is no such thing as an “average customer,” and going after phantom targets is not much different from shooting blanks.

On the reporting front — when chasing after often elusive targets — one must be careful not to get locked into a few popular measurements in the organization. Again, I recommend looking at the results in every possible way to construct the story of “what really happened.”

For instance:

• Response Rate/Conversion Rate: Total conversions over total contacted. Much like open and click-through rate, but I’d keep the original denominator — not just those who opened and clicked — to provide a reality check for everyone. Often, the “real” response rate (or conversion rate) would be far below 1% when divided by the total mail volume (or contact volume). Nonetheless, very basic and important metrics. Always try to go there, and do not stop at opens and clicks.
• Average Transaction Value: If someone converted, what is the value of the transaction? If you collect these figures over time on an individual level, you will also obtain Average Value per Customer, which in turn is the backbone of the Lifetime Value calculation. You will also be able to see the effect of subsequent purchases down the line, in this competitive world where most responders are one-time buyers (refer to “Wrestling the One-Time Buyer Syndrome”).
• Revenue Per 1,000 Contacts: Revenue divided by total contacts multiplied by 1,000. This is my favorite, as this figure captures both responsiveness and the transaction value at the same time. From here, one can calculate net margin of campaign on an individual level, if the acquisition or promotion cost is available at that level (though in real life, I would settle for campaig- level ROI any time).

These are just three basic figures covering responsiveness and value, and marketers may gain important intelligence if they look at these figures by, but not limited to, the following elements:

• Channel/Media
• Campaign
• Source of the contact list
• Segment/Selection Rule/Model Score Group (i.e., How is the target selected)
• Offer and Creative (hopefully someone categorized an endless series of these)
• Wave (if there are multiple waves or drops within a campaign)
• Other campaign details such as seasonality, day of the week, daypart, etc.

In the ultimate quest to find “what really works,” it is prudent to look at these metrics on multiple levels. For instance, you may find that these key metrics behave differently in different channels, and combinations of offers and other factors may trigger responsiveness and value in previously unforeseen manners.

No one would know all of the answers before tests, but after a few iterations, marketers will learn what the key segments within the target are, and how they should deal with them discriminately going forward. That is what we commonly refer to as a scientific approach, and the first step is to recognize that:

• There may be multiple pockets of distinct buyers,
• Not one type of metrics will tell us the whole story, and
• We are not supposed to batch and blast to a one-dimensional target with a uniform message.

I am not at all saying that all of the popular metrics for digital marketing are irrelevant; but remember that open and clicks are just directional indicators toward conversion. And the value of the customers must be examined in multiple ways, even after the conversion. Because there are so many ways to define success — and failure — and each should be a lesson for future improvements on targeting and messaging.

It may be out of fashion to say this old term in this century, but that is what “closed-loop” marketing is all about, regardless of the popular promotion channels of the day.

The names of metrics may have changed over time, but the measurement of success has always been about engagement level and the money that it brings.

## Political Direct Mail for the Win!

During the 2016 election cycle, there was more political direct mail than ever before. The United States Postal Service and The American Association of Political Consultants (AAPC) wanted to see how people viewed political mail, so they did a study about direct mail and its impact on voters. There are so many takeaways that can help you create political direct mail to win.

During the 2016 election cycle, there was more political direct mail than ever before. The United States Postal Service and The American Association of Political Consultants (AAPC) wanted to see how people viewed political mail, so they did a study about direct mail and its impact on voters. There are so many takeaways that can help you create political direct mail to win.

In 2018 we often get asked, does direct mail still work? YES! Here are a few facts about direct mail to show you the power you can harness:

• People check their mail at the first opportunity, which is nearly every day. You can reach your voters in a timely fashion without being forgotten.
• 86% of people go through the mail and make sure that nothing of value is being thrown out.
• 73% of people prefer direct mail over other marketing channels.
• Mail may be the best way to share new information about you as a candidate or an issue.

Radio and television do not allow you to target your prospects effectively. Your message ends up in front of people who cannot even vote for you. With direct mail, you have access directly to people who are able to vote for you. Take advantage of it! You can segment them into types of voters, propensity to vote and so much more.

When sending direct mail to voters, include important information about the election, such as voting deadlines for absentee ballots. Yes, you can target people who vote absentee with a different message than people who vote at the polls. You can also provide registration deadline information. Of course, include in the mail piece who you are, what you stand for and why people should vote for you. People keep mail that provides important information; get your mailer to stick around longer.

When polled about political mail voters responded with:

• 82% want to know where the candidate stands on issues
• 74% want a contrast with an opponent on issues
• 73% want to know a candidate’s voting record and any past statements made
• 60% want to see a list of who endorses the candidate.

We suggest that you use large format mailers to grab attention. According to a DMA 2017 response rate report, oversized pieces have been shown to increase response rates by 10.4%, producing the best overall response rate. You need to keep your text concise and easily scanned. Use bold, color and contrast to draw the eye to your important content. The easier you make it for people to quickly understand what you are saying, the better you are able to get your point across. Direct mail is better understood, remembered and acted upon more than digital channels. Add direct mail to your marketing mix to harness the votes you need to win.

Want to increase the time people spend with your mail pieces? Make them interactive. Add elements such as video, augmented reality, die cuts or endless folds to engage people. Video allows you as a candidate to speak directly to each voter about how you stand on issues and how you are different from other candidates. You can add special coatings or textures to really enhance the sensory reach of your mail piece. There are so many fun ways that direct mail can stand out that no other channel can do.

Are you ready to get started on your campaign?

## Fueling the Little Engine That Could

In our compulsion to always be in the fast lane, it’s easy to forget that once upon a time, direct mail was our principal medium of marketing communications and not incidentally, made some of its best practitioners millionaires.

Summer Gould’s recent useful article, “How Direct Mail Is Your Little Engine That Could,” is a helpful reminder for those of us who like to believe we are always at the leading edge of technology-driven marketing. In our compulsion to always be in the fast lane, it’s easy to forget that once upon a time, direct mail was our principal medium of marketing communications and not incidentally, made some of its best practitioners millionaires.

That said, it is also worth recognizing that while the little engine can chug along and “snail mail” gives us the opportunity to put varied and interesting messages into the hands of potential consumers, that little engine needs a good deal of fuel and that fuel is increasingly expensive. According to Ms. Gould: “The average prospect needs to see your mail piece seven to 10 times before buying from you. So a well-planned direct mail program includes multiple drops with various mailers and postcards.”

That’s an expensive statement and raises the question: How much fuel do we need to get the little engine up and over the hill to bring us an order? Perhaps Gould is being too pessimistic. Seven to 10 mailings to get a purchase is almost certain to be wildly expensive and not economic unless your product is very, very expensive.

One way of looking at this is to calculate the cost-per-order (CPO) at different response rates and numbers of mailings to reach the desired response. In this case, 44 sales. Using Bizo and Epsilon data, the DMA’s benchmark says that “direct mail achieves a 4.4 percent response rate.” While that is a higher average return than is informed by my experience, let’s go with it, anyway.

As we can see, direct mail at a 4.4 percent response rate, for every thousand mailed at a total cost of \$1,000 per thousand, the marketer would have 44 orders on a single mailing, each costing \$22.73. Assuming he could afford to spend 25 percent of his revenue for marketing, he would need at least a \$91 or higher product price to justify just a single mailing. Each one thousand mailing would cost the marketer about \$1,000. Whether we like it or not, that’s the cost of the little engine’s fuel. And if he had to mail the prospect three times to get the same 44 orders, his order cost would rise to \$68.18 which would suggest that his product selling price would have to exceed \$250.

On a CPM basis, as we know, email is likely to be only approximately 1/10 as expensive. Email costs are so varied that it is difficult to establish meaningful comparisons, but \$10 per thousand emails sent is as good a rule of thumb as any. Using as our baseline industry average open and “clickthrough” rates, we see that to achieve that same 44 sales, converting clickthroughs to sales at 70 percent, it would be necessary to email 10 times. Even so, the total bottom-line cost would be only just under \$100.

In this head-to-head comparison, on the basis of pure cost and response, the little engine would have been overwhelmingly beaten by email. The risk:reward ratios certainly favor email.

As we all know, CPO is only one variable. Of high importance is the comparative ease and speed of email, the ability to test quickly and accurately with small quantities and best of all, the ready availability of comprehensive data permitting large quantities to be analyzed and segmented quickly and easily. But as the figures demonstrate, just opting for email because it is much “cheaper per thousand” doesn’t address the key marketing economic issue: How much do we have to pay for an order and can we afford it? Looking at the entire smorgasbord of media from this perspective is essential.

While marketing costs per thousand and response percentages follow more or less predictable patterns, how much any product or service, single sale, continuing sale or subscription can afford to acquire a new customer depends totally on its own economics; how much the marketer is prepared to risk and how soon he expects to get his investment back.

Direct mail may well be the little engine of choice for many good reasons. But before taking a ride on it, it would be prudent to compare its costs and risks to other media.

## The Power of Purchase List Targeting

It’s important to have a trusted purchase list source. You should be informed of where the company gets its data, how often the data is updated and its policies on bad data. Once you have a good source, you need to take on the challenge of choosing your list options.

Since your response rate is directly related to who you are sending mail to, purchasing a mailing list can be a real challenge. There are so many options to choose from that it can be overwhelming. But first, it’s important to have a trusted purchase list source. You should be informed of where it gets the data, how often the data is updated and its policies on bad data. A couple of big purchase list players are Experian and Acxiom — you can check them out, as well as many other reputable list brokers. Once you have a good source, you need to take on the challenge of choosing your list options.

Top industry list option examples include:

• Nonprofit: Income, net worth, age, children, causes donated to in the past, organization membership, fundraising engagement, location
• Retail: Number of children, income, age, gender, apparel purchase habits, brands, online shopping habits, location
• Political: Children, homeownership, voting propensity, location, age, political party affiliation
• Entertainment: Age, income, children, hobbies, purchase history, location, marital status
• Healthcare: Age, income, number of children, location, gender, homeownership
• Education: Age, income, gender, highest level of education, location, interests

You may pick from demographics as well as psychographics. There are so many options, make sure to give yourself time to look over what will target your best potential customers. You want to get the right offer to the right people — the more targeted your list, the better response you are going to get. Marketing personas are fictional representations of your ideal customers, so if you have mapped personas beforehand, it will be easier to make your selections.

You can pre-map customer personas by taking a look at your best customers: Who are they? The more details you have, the more accurate the persona will be. Look for trends in how your customers find you and what they buy. Make sure you are capturing important information about customers in your data so that you can use it to build your personas. You should also interview customers to obtain key answers directly from the source. Too many assumptions can cause you to create an inaccurate persona.

Once you know the personas you are looking for, choosing the right selections for your list becomes easier. Select the options that best represent your customers. The more characteristics you pick, the better targeted your list will be. But keep in mind that more selections often result in a higher-priced purchase list. So make sure you only use the options that really reach your target.

Your list is now ready! Your final ingredients for successful direct mail are your creativity and your offer. Don’t spend all your time on the list and forget these other two components — without all three working together, your direct mail will not generate the response you are looking for. Make your offer clear and concise. Make your creative design catching, but not overwhelming. Give people a reason to read your direct mail.

## Benchmarking: There’s No Such Thing as an Average 2% Response Rate

It seems easy enough to answer the question: How to know if a marketing campaign measures up? But managing client expectations (whether they’re internal or external) is sometimes more fuzzy

It seems easy enough to answer the question: How to know if a marketing campaign measures up?

Often enough, there are predefined business objectives, acceptable margins for profit and cost, and a marketing return on investment that is straightforward enough to calculate. If one is able to know any and all of these markers, then one can know if a marketing campaign, or even a single tactic, is making the grade.

But managing client expectations (whether they’re internal or external) is sometimes more fuzzy. And a marketing execution doesn’t always go according to plan, prompting investigations on what might have gone wrong. (I’m still surprised how testing is underutilized, for example.)

On the happier end of the spectrum, stellar results might prompt a whole other set of questions: “Did we really beat the long-standing control? This campaign performed gang-busters, how does it measure up to efforts of our industry peers? Is this campaign award-worthy?”

As a public relations professional in the world of direct response, I’ve often been asked to help an agency or marketing client understand how good or bad a particular marketing result might be. When the question is about results that are less than expected, there is often internal wrangling about the creative, the list and/or the strategy — any of which might be the culprit. When the results are fantastic, clients often want to know, are we beating whatever the competition may be up to.

In both scenarios, among go-to options are various industry research sources. Anyone who has a subscription to Who’s Mailing What! archive (direct mail, email), or taps eMarketer or Econsultancy (digital and mobile information), or steps up to Gartner, Forrester and the like for subscriptions to qualitative reporting, certainly has access to great data and idea stores.

I personally keep a copy of “DMA Statistical Fact Book” (annually published) and “DMA Response Rate Report” close at hand. The “DMA Response Rate Report’s” 2015 version is recently published, and is available at the DMA Bookstore. Both are understandably Direct Marketing Association top-sellers.

The “DMA Response Rate Report” aggregates data from respondents — providing a true benchmarking resource. And it breaks response data out by media, and by industry (selling cars is not selling clothes) which gives marketers a helpful guide of what to shoot for and expect. It’s worth a whole other post to delve into its insights, but IWCO Direct and SeQuel Response recently offered some. A quick inspection of the report can let marketers know what they might expect from an otherwise well-executed campaign.

And I’m happy to say to some clients, too, as another benchmark, that they should enter the International ECHO Awards. It’s perhaps the best way to be recognized for achievement (beyond the paycheck). With judges inspecting the world’s best in data-driven advertising, an ECHO trophy says that a marketing team, agency or organization knows its stuff. This year’s competition deadline for entering is July 10, and DMA is offering a Webinar on May 19 to give tips and insights from the judges themselves (speaking will be yours truly, joined by fellow Target Marketing blogger Carolyn Goodman of Goodman Marketing Partners and Smithsonian’s Karen Rice Gardiner). Have only five minutes to spare? You can always hear directly from Carolyn here about the entry process.

Enter early and often! I’d love to point to your campaign as a “benchmark” later this year.

## Stimulating Awe, Goosebumps and Chills in Copy

When your copy stimulates awe, your customer should experience a physiological reaction like goosebumps or chills. A physical reaction comes from stimulation of the mind. And the positive emotion of awe is more likely to move a person to action. Direct marketers and copywriters have the opportunity to create these physical sensations with awe-inspiring copy

When your copy stimulates awe, your customer should experience a physiological reaction like goosebumps or chills. A physical reaction comes from stimulation of the mind. And the positive emotion of awe is more likely to move a person to action. Direct marketers and copywriters have the opportunity to create these physical sensations with awe-inspiring copy.

The link between positive moods and the physiological reaction we get with goosebumps is proven. So if you give your prospects goosebumps, surely you can sell more.

Research at the University of California, Berkeley between emotions such as compassion, joy, and love, versus the levels of interleukin-6 (IL-6)—a secretion which causes inflammation in the body—finds that those who regularly have positive emotions have less IL-6. Researchers noticed the strongest reaction with one particular emotion:

Awe.

You may not think of creating awe and wonderment when writing copy, but you should. Dacher Keltner, a psychology professor and the senior author of the study, gave examples of awe by saying “Some people feel awe listening to music, others watching a sunset or attending a political rally or seeing kids play.”

So what is this emotion called “awe?” Look at a dictionary and you’ll be told it’s “an overwhelming feeling of reverence, admiration, and fear, produced by that which is grand, sublime, or extremely powerful.” It can also result in a subconscious release of adrenaline.

An adrenaline rush causes the contraction of skin muscles and other body reactions. Adrenaline is often released when you feel cold or afraid, but also if you are under stress and feel strong emotions, such as anger or excitement. Other signs of adrenaline release include tears, sweaty palms, trembling hands, an increase in blood pressure, a racing heart or the feeling of ‘butterflies’ in the stomach.

If you create a strong new memory in your message that reminds your audience of a significant event, with the adrenalin rush they may feel goosebumps or chills. Past awe emotions can resurface with the right triggers.

Most importantly, how do you spark awe in your direct marketing campaigns?

• Stimulate emotions that recall a strong past positive memory
• Use powerful visuals that accompany copy that paint a picture
• Stir memory that resonates so strongly that it “feels” right

For your next marketing campaign, deliver that sense of awe so your customer feels goosebumps and chills. And there’s a chance you may feel them, too, as you look at your response rate.

## LinkedIn InMail Changes: What B-to-B Sellers Should Do Next

The new LinkedIn InMail changes are in effect—leaving sales reps and managers upset and confused. InMail just got much more expensive for average B-to-B sellers. However, you can now access a nearly unlimited supply of InMail credits under the new policy—by making one small change to how you craft InMail messages.

The new LinkedIn InMail changes are in effect—leaving sales reps and managers upset and confused. InMail just got much more expensive for average B-to-B sellers. However, you can now access a nearly unlimited supply of InMail credits under the new policy—by making one small change to how you craft InMail messages.

Yes, I said nearly unlimited. No, I’m not kidding, nor risking my integrity.

There is a way to send 100 InMail messages and get 193 credits back (for you to re-use again).

Briefly, What Changed and Why?
When InMail was introduced, LinkedIn’s “guaranteed response” policy rewarded spammy messages. Oops. So, as of January, LinkedIn gives InMail credits (that you buy) back—BUT only for InMails that earn a response in 90 days.

This is radically new.

Under the old system if you did not receive a response within a week, the InMail credit you purchased was given back. LinkedIn guaranteed a response. However, this rewards you for failing.

For example, let’s say you purchased 50 InMails and sent them. A (poor) 10 percent response rate allowed you to earn credits and send over 400 InMails per month. Thus, the policy increased the amount of spammy InMail messages being sent. The system rewarded it.

What the New Policy Means to You
Going forward, you will receive a credit (get your money back) for each InMail receiving a response within 90 days. You can re-use the money to invest again … and again and again. But if you earn no reply (or a poor response rate) your money is wasted.

LinkedIn’s old InMail policy rewarded sellers who weren’t successful with InMail.

LinkedIn’s new InMail policy rewards you (only) for writing messages that get good response. How good?

If you send 100 InMails per month, with a steady 20 percent response rate, you will end up with about 125 total InMails to send-based on InMails credited back to your account.

How to Send 100 InMails and Get 193 Credits Back
If you’re an average InMail user, you’re seeing credits vanish lately. But there is a way to send 100 InMail messages and get 98 returned to you. Or even 193 credits back (for you to re-use again).

How? Write effective InMail messages.

For example, let’s say you earn a 50 percent response rate on your first batch of 100 InMails sent. Over time (as you use the InMail credits returned to you) you earn a total of 98 credits. Not bad. You get nearly all of your investment back for re-use.

But what if you were really good? Let’s say you earned a 70 percent response rate to your InMail messages? Hey, it’s possible. I have students who earn 73 percent response rates.

With a 70 percent response rate, you would earn 193 InMail credits (of your original 100) to re-use for prospecting.

In actual practice the math is a bit messy, due to the delays between prospects responding and LinkedIn’s re-issuing credits. But you get the picture.

Should You Stop Using InMail?
As much as it may hurt, your never-ending stream of InMail credits were part of LinkedIn’s lack of foresight. If you are considering investing in InMail you’re in luck. Learn from this experience. Most B-to-B sellers who invested in LinkedIn Sales Navigator (and InMail) are complaining loudly. Many are resigning accounts.

And they should.

As Darwin said, “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.”

Change for the better.

What to Do Next
LinkedIn’s InMail policy change is another signal. Another warning. A reason to abandon fairy-tale beliefs like:

• Email prospecting doesn’t cost anything when it fails-or under-performs
• It’s mostly a numbers game
• Getting response and appointments means sending more emails

Yes, it is a numbers game. Just like cold-calling. But what is the basis of an effective cold-call routine?

An effective communications process. More specifically: A systematic, repeatable, scalable way to turn calls in to leads. I recently described this technique—gave next steps and templates to help make it easy.

If you aren’t serious about learning an effective process, you won’t experience predictable success.

“Lazy individuals will still be able to send indifferent InMails, but they won’t be rewarded for it.” says Bruce Johnston of The Practical Social Media blog.

“The new InMail system will reward people with imagination that experiment to get optimal response rates,” says Johnston.

Whether you pay cash for LinkedIn InMail credits or send standard emails to prospects … if it doesn’t work, it costs you. Cash or wasted time-time you should have spent doing something productive!

How do you feel about LinkedIn’s new InMail policy? What do you intend to do about it, looking forward?

## Top 5 Ways to Personalize Direct Mail

If I were to ask a group “What would interest you and capture your attention with a direct mail piece?” I guarantee that I would get lots of different answers. All of us have opinions, some stronger than others on certain subjects, but those opinions are what drive each of us. The power of direct mail is that we can create individually personalized pieces so that Tom has an offer that interests him, and Sue has a different offer that interests her. The best part is that the pieces can look identical except for the offer message. This can help you save money while increasing your response rate.

If I were to ask a group “What would interest you and capture your attention with a direct mail piece?” I guarantee that I would get lots of different answers. All of us have opinions, some stronger than others on certain subjects, but those opinions are what drive each of us. The power of direct mail is that we can create individually personalized pieces so that Tom has an offer that interests him, and Sue has a different offer that interests her. The best part is that the pieces can look identical except for the offer message. This can help you save money while increasing your response rate.

How To Use Personalized Data:

1. Name: The quickest and easiest way to start personalizing is to include the name. Not just in the address block, but as part of the offer. Use first name so that you are using a conversational tone. This should not be your only form of personalization on the piece, but it helps to include the first name. (Just make sure that it is the right name!)
2. Gender: If you have an offer that appeals differently to women than to men, this can be a great way to segment your offer. In many cases women look at products and services differently than men. Use that to your advantage with targeted offers. (Make sure that your data on gender is correct, sending the wrong message can make people angry)
3. Past Purchase/Donation History: Use what you know about each person to personalize their offer. If they bought peanut butter, reference that when offering jelly. If they made a donation previously, note that donation amount and ask if they can help with an increased amount this year. (Make sure that you make logical associations between a past purchase and a current offer. Don’t send me an offer for coffee when I bought tea, it may mean that I don’t like coffee.)
4. Reminders: If there is an average use time for your product or service, create incremental reminders to customers that they should be ready to buy again. Include a coupon for another purchase, and make sure to have an expiration date to create urgency. (Be careful not to over remind people. Sending too much direct mail can have a negative effect.)
5. Location: This can be used to entice people to join their neighbors and buy the same things. (The “Keeping Up With the Jones'” mentality) Point out that others on the block have purchased your product or service, and they should not miss out.

The trick to doing this correctly is the database. You need to be collecting information about your customers/prospects in order to give them better offers. The better the offer, the less likely it will be considered junk mail and thrown away. Do not waste your money sending direct mail to people who don’t want it. Your database is your goldmine. Treat it with the utmost care and constantly make changes to it.

If you don’t have much information in your database, start small. Look at the list above and see what you can do with the information you do have. There are profile list services out there to help you learn more about your customers. If you use list profile services, remember the information is more of a generalization to categorize people. Do not use the information as a fact, since it could lead you to assume incorrectly about what people like and dislike. Personalization can be the catalyst to catapult your direct mail response to the next level.