10 Elements of a Squeeze Page

For those of you who haven’t heard this term, a squeeze page is basically a short landing page with one main purpose — to “squeeze” the email address out of the visitor to that page.

10 Elements of a Squeeze Page
“10,” Creative Commons license. | Credit: Flickr by Paul Downey

For those of you who haven’t heard this term, a squeeze page is basically a short landing page with one main purpose — to “squeeze” the email address out of the visitor to that page.

In other words, it’s a promotional page with the goal of lead generation (or “list-building”).

Smart marketers like to balance their online mixes and do both direct-to-sale efforts (i.e. selling a product) along with list-building (i.e. lead gen) efforts.

But not all squeeze pages are created equal.

Some are very short and pithy, with a headline and call to action … more ideal for mobile phone viewing. While others have longer copy to convey the value proposition of why the prospects need to give their email addresses.

Your target audience, delivery platform, message, offer and other variables will determine which format you may want to test.

But generally speaking, over the many years I have been creating successful squeeze pages for both consulting clients and top publishers alike, I would have to say that I’ve noticed 10 key elements that help make a winning squeeze page and get conversions.

Here they are:

  1. Gets Your Attention. It’s very important for a good squeeze page to have a strong headline, coupled with an eye-catching masthead image. This is when good persuasive copywriting skills comes into play with creative design.
  2. The Offer. You need to show the reader why they need to sign up and give you their email address … WHAT are they getting out of it? Typically it’s some kind of bonus, such as a free .pdf report, free white paper, free e-newsletter … free something. And that freebie needs to answer a question the prospect may have, solve a problem and teach them something they don’t know. All of the bonus benefits and the value proposition need to be outlined in the body copy in a clear, easy-to-read format (usually bullets).
  3. Why Listen to You? It’s also important to briefly outline WHY the prospect should listen to you. What makes you the expert? Why you are uniquely qualified? In a paragraph or less, it’s a good idea to introduce yourself and your credentials to the reader. Again, strong copywriting comes into play here to persuade the reader that it’s imperative to hear what you have to say and give you their email address.
  4. Visually Appealing. Call-to-action buttons that are bright and catch your attention (i.e. orange, yellow, red), a thumbnail of a free bonus report, a starburst showing the $ value of the free report, a headshot of the expert, and other relevant graphic enhancements are great ways to keep the reader engaged and move the eye down the page.
  5. If you have testimonials that speak to your expertise, use quote boxes and add short, strong testimonials. One or two that have a “wow” factor are best.
  6. No Distractions. As mentioned earlier, squeeze pages have one simple goal: to collect an email address. So it’s important not to have other clickable links on the page or navigation. You want to keep the readers focused on only giving you their emails and clicking “submit.” Don’t have background noise.
  7. Contact Information. At the bottom of the squeeze page, I like to add a brick-and-mortar physical address of the business, as well as the business Web address — that’s un-clickable. If you have a BBB logo or other logo that represents an award, accolade or accomplishment, it helps adds prestige, authenticity and promotes consumer confidence.
  8. Legal Mumbo-Jumbo. It’s important to remember, especially if you’re in the health or financial publishing space, to add the necessary disclaimers specific for that industry. In general, you may want to add something along the lines of: “The information and material provided on this site are for educational purposes only.”
  9. Anti-Spam Pledge. Under the email collection fields and above the call-to-action button, it’s a best practice to add some anti-spam verbiage to alleviate any concerns to the reader that the email may be sold or rented. Some even have a text hyperlink to their privacy policy.
  10. The More You Ask, The Less You Get. It’s a general rule of thumb that for each information field you ask the prospect to give, i.e. first name, email address, etc., you will get fewer responders. Some people ask for mailing address, age and other demographic information. That will deter some prospects and dampen response. However, the ones who do answer have demonstrated a real interest and are more qualified than just visitors who gave their email. So think about your ultimate goal for the squeeze page when determining how much information you’re going to ask for.

The squeeze page is only the beginning.

A good, strategic list-building campaign will have many elements that all work together to get a prospect’s attention (the ad); get them to sign up (the squeeze page); help them bond with the guru or editor; become educated in the publication’s mission; and, ultimately, get the subscriber to convert to a buyer of a paid product.

This is called the onboarding process. And an effective onboarding process is the beginning of the sales funnel that should end with more voluminous conversions in a shorter time-frame than if you don’t have an onboarding process in place.

So evaluate your business. See how many leads (#) you’re bringing in on a monthly basis, at how much ($) per lead, and how quickly these leads are converting to buyers.

Then decide if squeeze pages and setting up an onboarding process are right for you.

Good luck and happy prospecting!

5 Shades of Pop-Up Email Acquisition

As marketers, one of the biggest challenges we face is growing our marketing list at a rate higher than our attrition. On average, companies report an attrition rate of about 20 percent, which means in order to show a growth of just 10 percent per year, we need an actual growth of 30 percent. That’s a lot of growth and yet many of us simply have not developed a concrete plan to achieve this goal

As marketers, one of the biggest challenges we face is growing our marketing list at a rate higher than our attrition. On average, companies report an attrition rate of about 20 percent, which means in order to show a growth of just 10 percent per year, we need an actual growth of 30 percent. That’s a lot of growth and yet many of us simply have not developed a concrete plan to achieve this goal.

In the age of shiny, new objects, we have at our disposal tools, widgets, scripts, and doo-dads all designed to entice, encourage, beg, and withhold in order to garner the most valuable of data: our prospects’ email address. I’ve tried all of these approaches I’ll describe below, either on our site or on a client’s site, and there’s not one right answer. The big question is: Why do pop-ups work?

Most of us swear we hate subscriber pop-ups; they’re annoying; they make us want to leave the site immediately—but is this actually true? Studies show it’s simply not. The web abounds with case studies by companies of all sizes who verify their pop-ups are effective conversion tools and there’s a reason: pop-ups—though annoying—jolt your visitor with a persuasion technique called pattern interrupt. This identifies a situation where something unexpected happens after your brain has become lulled into a rhythm. You can interrupt a pattern with just about any unexpected or sudden display, movement, or response. When you interrupt the visitor, they usually experience momentary confusion, and sometimes even amnesia. This confusion state causes the visitor to become open to suggestion—they become willing to trade this uncomfortable state for clarity offered by another state. Your clear call to action displayed in a pop-up offers them a path to end their confusion.

With that said, and understanding how a pop-up works, you then need to choose the right pop-up approach. You’ll find some pop-ups are better aligned with your business than others, but that knowledge is usually gained through trial and error. If you’re using a CMS site such as WordPress, Joomla, or Drupal, you can test any/all of these approaches simply by installing plug-ins. With HTML, it become more difficult as you sort through different jQuery or JavaScript tools, but it’s not so difficult as to deter you. In the end, pop-ups are a great way to chip away at your pursuit of 30 percent growth.

On-enter Gated
Of all the annoying pop-ups, on-enter gated is the one I personally find the largest deterrent from continuing my engagement with a site. Figure 1 in the media player at right is an example is from JustFab.com, and their pop-up experience begins the moment you land. A pop-up first offers product options you must click through so they can build a profile of your style preferences. With that done, you complete the form shown in figure 1 before being allowed to continue your shopping experience. You cannot dismiss this pop-up without providing the required information. I suffered through this process only to be able to capture this screen shot, but I can tell you I have abandoned every other site that required me to log in to view their content. Similarly, I nearly always abandon a site that allowed me to read part of an article and then withheld the ending until I proffered my email address.

On Enter
For me, pop-ups on enter like the one shown in figure 2, are far less annoying than on-enter gated. These pop-ups might display as soon as you land, after a period of time, or after you begin scrolling. These have a dismiss icon, so you can close the box without providing the information. If you choose this route, you’ll want to do some testing around the ideal time to let pass before displaying. I’ve found giving the reader 15 to 30 seconds to get a taste for the content produces better results. If you ask for their email address before they have determined the value of your site, you may scare them off.

Header (or Footer) Notification
Header or footer notifications are far less intrusive, and thus could prove to be less effective. It’s easy to miss a message displayed at the very top of the page since the visitor’s eye is more typically drawn to the area that usually displays the menu bar. If you choose a header or footer notification like the one shown in figure 3 from infyways.com, try using a heat map to ensure your visitors are even looking at the notice before you decide the effectiveness of this approach.

On Exit
The on-exit pop-up (figure 4), displays automatically as someone makes a move to leave a site. I like these pop-ups because it’s the what-have-I-got-to-lose? approach. Displaying a message after your visitor has already decided to leave your site is a great way to cause them pause and reconsider what they’ve just read. Was it really of no value? Did it have value only today? Did it have long-term value? If so, would they like to be notified of new, similar content?

Scroll-Triggered Pop-up
This pop-up (figure 5) is triggered to display along the bottom edge (configurable) of the visitor’s browser window as they scroll down the page. It will display on any/all pages of the site, so it’s effective even if they’ve clicked a link directly through to a landing page.

A/B Testing and Analytics
There are probably as many approaches as there are businesses and websites, but this list is a good overview. Don’t stop at just installing the form or plug-in, without analytics and careful monitoring, you’re not getting smarter about what works and what doesn’t. If you’ve installed a subscriber pop-up plug-in and you’re not getting sign-ups, first make sure the product is working properly and then check your analytics. Are you actually getting traffic to the page where you’ve included your capturing system? Using a heatmap, are people viewing it? Lastly, these products are not mutually exclusive. Try lots of approaches all at once—that in itself can be the A/B test: which product is most effective on which pages?

Most of these products will capture your prospects into a database of some sort, but automating the passing of leads into your email system will make the entire process more valuable to you. By passing the data automatically, you can also create instantaneous auto-responders welcoming your new subscriber. While you’re shopping for a product, ensure you check to see if it supports your chosen email-automation platform, and if not, look to see how you can automate this process. We use Zapier and have found we can directly support the client’s application about 90 percent of the time.

For most of us, we have a methodical approach to building a marketing campaign and I think this same approach can be used as a plan for growing your list:

  1. Define a measurable goal
  2. Choose tools you will use for measuring success/failure of the effort
  3. Outline with metrics are important to showing success/failure
  4. Define A/B testing points
  5. Analyze results

If you’ve had success with a particular product, please share your experience in the comments below. I’m always eager to learn about new products that can make me a better marketer—as I’m sure this blog’s readers are as well.

‘Forgotten’ Unsubscribes – Is This a New Trend?

With Black Friday now behind me, I ran a quick count and found 131 emails sent by retailers with whom I had unsubscribed. I was more than a little surprised to have received this many emails and wondered: Are these retailers counting on me having forgotten I had unsubscribed? Is this a new trend?

With Black Friday now behind me, I ran a quick count and found 131 emails sent by retailers with whom I had unsubscribed. I was more than a little surprised to have received this many emails and wondered: Are these retailers counting on me having forgotten I had unsubscribed? Is this a new trend?

The CAN-SPAM Act is very clear on the issue of how businesses should present and handle unsubscribes. It reads in part, you cannot charge a fee, require the recipient to give any personally identifying information beyond an email address, or make the recipient take any step other than sending a reply email or visiting a single page on a website as a condition for honoring an opt-out request.” In other words, it should be easy and it should be permanent. The retailers who have sent me an email in the last few days have done far more damage than good – though I admit, my diligence in tracking unsubscribes goes well beyond that of the typical subscriber—most people probably do forget having unsubscribed.

I’ve divided my 131 Black Friday marketing emails into three categories (remember, these are not business correspondence messages or transactional messages, for which opt-out rules differ in the US, as well as Canada and the EU):

  1. Retailers with whom I had done business, but not subscribed (permitted to send transactional messages only).
  2. Retailers with whom I had done business, subscribed, and later unsubscribed (permitted to send transactional and marketing messages until revoked).
  3. New retailers with whom I had concluded business and explicitly opted out of marketing messages at the time of transaction (permitted to send transactional message only).

Of these emails:

  • 6 provided no unsubscribe link or information (which is allowed by the CAN-SPAM Act, if they are using the reply-to process for unsubscribing)
  • 26 provided an unsubscribe link requiring me to visit a web page to set my preferences
  • 19 provided both an unsubscribe link and a preferences link

Past Relationships
So let’s take a look at these vendors’ approaches and assess the value of each:

Several years ago I bought hosting services from Glob@t. On the 28th and again today, I received emails from this vendor. I unsubscribed from their messages just once when our relationship ended, and yet Black Friday seemed to have provided the perfect opportunity—as deemed by their marketing department – to reactivate an unsubscribed name and send a message.

In this case their message actually did exactly as they hoped: I became re-engaged. Of course, they had no idea, but yesterday I spent three hours on a tech-support call with my current vendor, and had decided to start shopping hosting vendors. Glob@t’s email came at an opportune time, but that’s not to say I wasn’t annoyed by it—I certainly was. Nonetheless, I clicked the link to check out their hosting packages, and after checking pricing, I returned to the email to unsubscribe. I will monitor their messages to ensure I remain unsubscribed this time around.

New Relationships
Three weeks ago I made a purchase from eBay of a hard-to-find item, which launched an onslaught of emails. I have received one or more every day since the date of purchase and in each I have clicked the unsubscribe link. Their unsubscribe text at the bottom of those emails reads in part,

Learn more to protect yourself from spoof (fake) e-mails.

eBay Inc. sent this e-mail to you at [myemailaddress] because your Notification Preferences indicate that you want to receive general email promotions.

If you do not wish to receive further communications like this, please click here to unsubscribe. Alternatively, you can change your Notification Preferences in My eBay by clicking here. Please note that it may take up to 10 days to process your request.

What I find interesting about their unsubscribe text is the presentation. By starting out with a “learn more about spoofing” link, they have attempted to befriend me by offering tips on protecting myself. They are my concerned about me—or so it would seem.

Next they offer to unsubscribe me by clicking the link and when I do click it, I receive an unsubscribe confirmation and information on how to re-subscribe should I wish to.

Their unsubscribe text does let me know it may take up to ten days to process my request, but I have to wonder: Why is this? Every company using an email-automation system knows unsubscribes are immediate. What’s up with the ten-day delay? My guess is they hope within the next ten days they will be able to send me an email that will re-engage me. (Terrible idea.)

After more than ten days of continuing to receive one or more emails every day, I clicked the set my preferences link, which requires—you guessed it—a log in. The purchase I made was completed as a guest. I did not wish then, nor do I wish now, to create an account with them. I’ve had one cause (ever) to make a purchase from them, and didn’t see it happening again. If it did, I could make a decision at that time about whether or not an account would be necessary. This too is an annoying approach: require the user to create an account to unsubscribe. (Terrible idea number two.)

After two weeks of emails, I’m now so irritated by their entire process it will adversely affect my decision to ever buy from them again, even if the item I am seeking is less expensive, more available, or even exclusively available. I will remember their lack of respect for my wishes and it will deter me. I guess they’re not as friendly as they first seemed.

As marketers, staying engaged with your constituents is more than betting on their short-term memory loss. It’s about honoring the relationship and their wishes. I remembered Glob@t and would have come back to their site when my vendor shopping began, but knowing they do not honor my unsubscribe status has tainted my view of their business practices. My purchase from eBay was exactly the right product, delivered on time, and in great condition. My positive experience would have led me back to them at some point in the future, but their emailing practices have put them on my own do-not-call list. If the new trend is to make a brand more memorable by being annoying, I opt out.

Moving Upstream on Cart Abandonment

After speaking at a conference on the topic of email automation for your online store, I was approached by more than a dozen people with the same question: “If someone abandons their cart, how can the store stay in touch with the shopper?” It’s impossible to contact anonymous visitors—their anonymity means you’ve not yet collected their email addresses and thus you have no way to reach them

After speaking at the WooCommerce Conference on the topic of email automation for your online store, I was approached by more than a dozen people with the same question: If someone abandons their cart, how can the store stay in touch with the shopper?

It’s impossible to contact anonymous visitors—their anonymity means you’ve not yet collected their email addresses and thus you have no way to reach them. Perhaps they were just price shopping or researching. Perhaps they were distracted before completing their purchase. Perhaps they didn’t like your site’s shopping cart experience. Whatever the reason, they’ve slipped away, and you’ve been left with the promise of a sale that’s not yet complete.

According to Business Insider, this is the case with 68 percent of shoppers—those who leave their carts before checking out—and about $4 billion in abandoned carts the world over. The good news is they also estimate up to 62 percent or $2.52 billion is recoverable with automated marketing. Does that mean you simply need to give up hope of reaching those wallets and focus on the known visitors? Well, no. It simply means you need to develop a strategy for teasing away those email addresses. It means you need to move your request upstream.

There are myriad possible tactics of this strategy, but the path you choose depends upon your business, your product and the tools you have for implementing your ideas. No matter which path you choose, be prepared to A/B test like a madwoman until you’ve found the top three triggers and use all three. Don’t settle for just one approach. Meet your potential customers with the sign-up tool of choice—which means giving them options. Let’s look at some ideas. I’m going to call these interrupters, but I’m pretty sure I’ve borrowed the phrase from someone brilliant:

Interrupters can be any sort of dialogue, window, link or button interrupting the user’s shopping excursion and redirecting them to a simple (usually pop-up) form collecting only their email addresses, for instance:

  • Interrupt the product-browsing session with a tool enabling them to upload a photo of a room they are decorating in which they can drag and drop their selected item into place. It doesn’t have to be a perfect UX, just provide them with a rough idea of how the Egyptian vase they added to their cart might look next to their lime-green sofa.
  • After the first product has been added to the cart, interrupt with a message such as, “Wow! That’s a great find! We can save it in your cart for as long as you like. Let’s give your cart a name. Please type your email address.” You could extend this process with a dialogue after each product, displaying different messaging or, go for funny, and provide humorous commentary. Be sure to also provide a checkbox for prevent the message from displaying again.
  • Provide an online calculator allowing them to figure out how much of a product to buy. Let them use the calculator and then offer to save their work using just their email address. You could also offer to email their calculations or illustrations to the address they provide. We used this approach on our personal profiler – they can use the profiler online all day long, but if they would like to print their profiles, we will send the PDFs to their inbox.
  • Offer to send them links to download the installation instructions, case study, or watch a video.
  • Offer to save their cart when they click the browser’s close button.

Be sure you are interrupting your shopper with something of value. Popping up a subscriber window might be a bit annoying on its own, but a subscriber window with an offer of free shipping on the order they are building is going to win some favor.

According to a CouponCabin.com survey, 73 percent of U.S. adults are more likely to shop online where free shipping is offered, and, further, 93 percent of online shoppers said they would spend more if free shipping were offered.

Resist the temptation to interrupt visitors with a long form, or even your regular check out form, or you risk adding to your abandonment rate. Also, be sure to pass the information you collect directly into their account page—don’t make them provide you with their email address again if they continue the checkout process.

Interrupters can easily become annoying, so go slowly and don’t get greedy. You want to be able to capture as many anonymous visitors as possible, but there’s also great potential to drive shoppers away at the same time. It’s a delicate balance, but well worth the effort. Remember, there’s $4 billion dollars out there, and some of that can be yours.

Not All Databases Are Created Equal

Not all databases are created equal. No kidding. That is like saying that not all cars are the same, or not all buildings are the same. But somehow, “judging” databases isn’t so easy. First off, there is no tangible “tire” that you can kick when evaluating databases or data sources. Actually, kicking the tire is quite useless, even when you are inspecting an automobile. Can you really gauge the car’s handling, balance, fuel efficiency, comfort, speed, capacity or reliability based on how it feels when you kick “one” of the tires? I can guarantee that your toes will hurt if you kick it hard enough, and even then you won’t be able to tell the tire pressure within 20 psi. If you really want to evaluate an automobile, you will have to sign some papers and take it out for a spin (well, more than one spin, but you know what I mean). Then, how do we take a database out for a spin? That’s when the tool sets come into play.

Not all databases are created equal. No kidding. That is like saying that not all cars are the same, or not all buildings are the same. But somehow, “judging” databases isn’t so easy. First off, there is no tangible “tire” that you can kick when evaluating databases or data sources. Actually, kicking the tire is quite useless, even when you are inspecting an automobile. Can you really gauge the car’s handling, balance, fuel efficiency, comfort, speed, capacity or reliability based on how it feels when you kick “one” of the tires? I can guarantee that your toes will hurt if you kick it hard enough, and even then you won’t be able to tell the tire pressure within 20 psi. If you really want to evaluate an automobile, you will have to sign some papers and take it out for a spin (well, more than one spin, but you know what I mean). Then, how do we take a database out for a spin? That’s when the tool sets come into play.

However, even when the database in question is attached to analytical, visualization, CRM or drill-down tools, it is not so easy to evaluate it completely, as such practice reveals only a few aspects of a database, hardly all of them. That is because such tools are like window treatments of a building, through which you may look into the database. Imagine a building inspector inspecting a building without ever entering it. Would you respect the opinion of the inspector who just parks his car outside the building, looks into the building through one or two windows, and says, “Hey, we’re good to go”? No way, no sir. No one should judge a book by its cover.

In the age of the Big Data (you should know by now that I am not too fond of that word), everything digitized is considered data. And data reside in databases. And databases are supposed be designed to serve specific purposes, just like buildings and cars are. Although many modern databases are just mindless piles of accumulated data, granted that the database design is decent and functional, we can still imagine many different types of databases depending on the purposes and their contents.

Now, most of the Big Data discussions these days are about the platform, environment, or tool sets. I’m sure you heard or read enough about those, so let me boldly skip all that and their related techie words, such as Hadoop, MongoDB, Pig, Python, MapReduce, Java, SQL, PHP, C++, SAS or anything related to that elusive “cloud.” Instead, allow me to show you the way to evaluate databases—or data sources—from a business point of view.

For businesspeople and decision-makers, it is not about NoSQL vs. RDB; it is just about the usefulness of the data. And the usefulness comes from the overall content and database management practices, not just platforms, tool sets and buzzwords. Yes, tool sets are important, but concert-goers do not care much about the types and brands of musical instruments that are being used; they just care if the music is entertaining or not. Would you be impressed with a mediocre guitarist just because he uses the same brand of guitar that his guitar hero uses? Nope. Likewise, the usefulness of a database is not about the tool sets.

In my past column, titled “Big Data Must Get Smaller,” I explained that there are three major types of data, with which marketers can holistically describe their target audience: (1) Descriptive Data, (2) Transaction/Behavioral Data, and (3) Attitudinal Data. In short, if you have access to all three dimensions of the data spectrum, you will have a more complete portrait of customers and prospects. Because I already went through that subject in-depth, let me just say that such types of data are not the basis of database evaluation here, though the contents should be on top of the checklist to meet business objectives.

In addition, throughout this series, I have been repeatedly emphasizing that the database and analytics management philosophy must originate from business goals. Basically, the business objective must dictate the course for analytics, and databases must be designed and optimized to support such analytical activities. Decision-makers—and all involved parties, for that matter—suffer a great deal when that hierarchy is reversed. And unfortunately, that is the case in many organizations today. Therefore, let me emphasize that the evaluation criteria that I am about to introduce here are all about usefulness for decision-making processes and supporting analytical activities, including predictive analytics.

Let’s start digging into key evaluation criteria for databases. This list would be quite useful when examining internal and external data sources. Even databases managed by professional compilers can be examined through these criteria. The checklist could also be applicable to investors who are about to acquire a company with data assets (as in, “Kick the tire before you buy it.”).

1. Depth
Let’s start with the most obvious one. What kind of information is stored and maintained in the database? What are the dominant data variables in the database, and what is so unique about them? Variety of information matters for sure, and uniqueness is often related to specific business purposes for which databases are designed and created, along the lines of business data, international data, specific types of behavioral data like mobile data, categorical purchase data, lifestyle data, survey data, movement data, etc. Then again, mindless compilation of random data may not be useful for any business, regardless of the size.

Generally, data dictionaries (lack of it is a sure sign of trouble) reveal the depth of the database, but we need to dig deeper, as transaction and behavioral data are much more potent predictors and harder to manage in comparison to demographic and firmographic data, which are very much commoditized already. Likewise, Lifestyle variables that are derived from surveys that may have been conducted a long time ago are far less valuable than actual purchase history data, as what people say they do and what they actually do are two completely different things. (For more details on the types of data, refer to the second half of “Big Data Must Get Smaller.”)

Innovative ideas should not be overlooked, as data packaging is often very important in the age of information overflow. If someone or some company transformed many data points into user-friendly formats using modeling or other statistical techniques (imagine pre-developed categorical models targeting a variety of human behaviors, or pre-packaged segmentation or clustering tools), such effort deserves extra points, for sure. As I emphasized numerous times in this series, data must be refined to provide answers to decision-makers. That is why the sheer size of the database isn’t so impressive, and the depth of the database is not just about the length of the variable list and the number of bytes that go along with it. So, data collectors, impress us—because we’ve seen a lot.

2. Width
No matter how deep the information goes, if the coverage is not wide enough, the database becomes useless. Imagine well-organized, buyer-level POS (Point of Service) data coming from actual stores in “real-time” (though I am sick of this word, as it is also overused). The data go down to SKU-level details and payment methods. Now imagine that the data in question are collected in only two stores—one in Michigan, and the other in Delaware. This, by the way, is not a completely made -p story, and I faced similar cases in the past. Needless to say, we had to make many assumptions that we didn’t want to make in order to make the data useful, somehow. And I must say that it was far from ideal.

Even in the age when data are collected everywhere by every device, no dataset is ever complete (refer to “Missing Data Can Be Meaningful“). The limitations are everywhere. It could be about brand, business footprint, consumer privacy, data ownership, collection methods, technical limitations, distribution of collection devices, and the list goes on. Yes, Apple Pay is making a big splash in the news these days. But would you believe that the data collected only through Apple iPhone can really show the overall consumer trend in the country? Maybe in the future, but not yet. If you can pick only one credit card type to analyze, such as American Express for example, would you think that the result of the study is free from any bias? No siree. We can easily assume that such analysis would skew toward the more affluent population. I am not saying that such analyses are useless. And in fact, they can be quite useful if we understand the limitations of data collection and the nature of the bias. But the point is that the coverage matters.

Further, even within multisource databases in the market, the coverage should be examined variable by variable, simply because some data points are really difficult to obtain even by professional data compilers. For example, any information that crosses between the business and the consumer world is sparsely populated in many cases, and the “occupation” variable remains mostly blank or unknown on the consumer side. Similarly, any data related to young children is difficult or even forbidden to collect, so a seemingly simple variable, such as “number of children,” is left unknown for many households. Automobile data used to be abundant on a household level in the past, but a series of laws made sure that the access to such data is forbidden for many users. Again, don’t be impressed with the existence of some variables in the data menu, but look into it to see “how much” is available.

3. Accuracy
In any scientific analysis, a “false positive” is a dangerous enemy. In fact, they are worse than not having the information at all. Many folks just assume that any data coming out a computer is accurate (as in, “Hey, the computer says so!”). But data are not completely free from human errors.

Sheer accuracy of information is hard to measure, especially when the data sources are unique and rare. And the errors can happen in any stage, from data collection to imputation. If there are other known sources, comparing data from multiple sources is one way to ensure accuracy. Watching out for fluctuations in distributions of important variables from update to update is another good practice.

Nonetheless, the overall quality of the data is not just up to the person or department who manages the database. Yes, in this business, the last person who touches the data is responsible for all the mistakes that were made to it up to that point. However, when the garbage goes in, the garbage comes out. So, when there are errors, everyone who touched the database at any point must share in the burden of guilt.

Recently, I was part of a project that involved data collected from retail stores. We ran all kinds of reports and tallies to check the data, and edited many data values out when we encountered obvious errors. The funniest one that I saw was the first name “Asian” and the last name “Tourist.” As an openly Asian-American person, I was semi-glad that they didn’t put in “Oriental Tourist” (though I still can’t figure out who decided that word is for objects, but not people). We also found names like “No info” or “Not given.” Heck, I saw in the news that this refugee from Afghanistan (he was a translator for the U.S. troops) obtained a new first name as he was granted an entry visa, “Fnu.” That would be short for “First Name Unknown” as the first name in his new passport. Welcome to America, Fnu. Compared to that, “Andolini” becoming “Corleone” on Ellis Island is almost cute.

Data entry errors are everywhere. When I used to deal with data files from banks, I found that many last names were “Ira.” Well, it turned out that it wasn’t really the customers’ last names, but they all happened to have opened “IRA” accounts. Similarly, movie phone numbers like 777-555-1234 are very common. And fictitious names, such as “Mickey Mouse,” or profanities that are not fit to print are abundant, as well. At least fake email addresses can be tested and eliminated easily, and erroneous addresses can be corrected by time-tested routines, too. So, yes, maintaining a clean database is not so easy when people freely enter whatever they feel like. But it is not an impossible task, either.

We can also train employees regarding data entry principles, to a certain degree. (As in, “Do not enter your own email address,” “Do not use bad words,” etc.). But what about user-generated data? Search and kill is the only way to do it, and the job would never end. And the meta-table for fictitious names would grow longer and longer. Maybe we should just add “Thor” and “Sponge Bob” to that Mickey Mouse list, while we’re at it. Yet, dealing with this type of “text” data is the easy part. If the database manager in charge is not lazy, and if there is a bit of a budget allowed for data hygiene routines, one can avoid sending emails to “Dear Asian Tourist.”

Numeric errors are much harder to catch, as numbers do not look wrong to human eyes. That is when comparison to other known sources becomes important. If such examination is not possible on a granular level, then median value and distribution curves should be checked against historical transaction data or known public data sources, such as U.S. Census Data in the case of demographic information.

When it’s about the companies’ own data, follow your instincts and get rid of data that look too good or too bad to be true. We all can afford to lose a few records in our databases, and there is nothing wrong with deleting the “outliers” with extreme values. Erroneous names, like “No Information,” may be attached to a seven-figure lifetime spending sum, and you know that can’t be right.

The main takeaways are: (1) Never trust the data just because someone bothered to store them in computers, and (2) Constantly look for bad data in reports and listings, at times using old-fashioned eye-balling methods. Computers do not know what is “bad,” until we specifically tell them what bad data are. So, don’t give up, and keep at it. And if it’s about someone else’s data, insist on data tallies and data hygiene stats.

4. Recency
Outdated data are really bad for prediction or analysis, and that is a different kind of badness. Many call it a “Data Atrophy” issue, as no matter how fresh and accurate a data point may be today, it will surely deteriorate over time. Yes, data have a finite shelf-life, too. Let’s say that you obtained a piece of information called “Golf Interest” on an individual level. That information could be coming from a survey conducted a long time ago, or some golf equipment purchase data from a while ago. In any case, someone who is attached to that flag may have stopped shopping for new golf equipment, as he doesn’t play much anymore. Without a proper database update and a constant feed of fresh data, irrelevant data will continue to drive our decisions.

The crazy thing is that, the harder it is to obtain certain types of data—such as transaction or behavioral data—the faster they will deteriorate. By nature, transaction or behavioral data are time-sensitive. That is why it is important to install time parameters in databases for behavioral data. If someone purchased a new golf driver, when did he do that? Surely, having bought a golf driver in 2009 (“Hey, time for a new driver!”) is different from having purchased it last May.

So-called “Hot Line Names” literally cease to be hot after two to three months, or in some cases much sooner. The evaporation period maybe different for different product types, as one may stay longer in the market for an automobile than for a new printer. Part of the job of a data scientist is to defer the expiration date of data, finding leads or prospects who are still “warm,” or even “lukewarm,” with available valid data. But no matter how much statistical work goes into making the data “look” fresh, eventually the models will cease to be effective.

For decision-makers who do not make real-time decisions, a real-time database update could be an expensive solution. But the databases must be updated constantly (I mean daily, weekly, monthly or even quarterly). Otherwise, someone will eventually end up making a wrong decision based on outdated data.

5. Consistency
No matter how much effort goes into keeping the database fresh, not all data variables will be updated or filled in consistently. And that is the reality. The interesting thing is that, especially when using them for advanced analytics, we can still provide decent predictions if the data are consistent. It may sound crazy, but even not-so-accurate-data can be used in predictive analytics, if they are “consistently” wrong. Modeling is developing an algorithm that differentiates targets and non-targets, and if the descriptive variables are “consistently” off (or outdated, like census data from five years ago) on both sides, the model can still perform.

Conversely, if there is a huge influx of a new type of data, or any drastic change in data collection or in a business model that supports such data collection, all bets are off. We may end up predicting such changes in business models or in methodologies, not the differences in consumer behavior. And that is one of the worst kinds of errors in the predictive business.

Last month, I talked about dealing with missing data (refer to “Missing Data Can Be Meaningful“), and I mentioned that data can be inferred via various statistical techniques. And such data imputation is OK, as long as it returns consistent values. I have seen so many so-called professionals messing up popular models, like “Household Income,” from update to update. If the inferred values jump dramatically due to changes in the source data, there is no amount of effort that can save the targeting models that employed such variables, short of re-developing them.

That is why a time-series comparison of important variables in databases is so important. Any changes of more than 5 percent in distribution of variables when compared to the previous update should be investigated immediately. If you are dealing with external data vendors, insist on having a distribution report of key variables for every update. Consistency of data is more important in predictive analytics than sheer accuracy of data.

6. Connectivity
As I mentioned earlier, there are many types of data. And the predictive power of data multiplies as different types of data get to be used together. For instance, demographic data, which is quite commoditized, still plays an important role in predictive modeling, even when dominant predictors are behavioral data. It is partly because no one dataset is complete, and because different types of data play different roles in algorithms.

The trouble is that many modern datasets do not share any common matching keys. On the demographic side, we can easily imagine using PII (Personally Identifiable Information), such as name, address, phone number or email address for matching. Now, if we want to add some transaction data to the mix, we would need some match “key” (or a magic decoder ring) by which we can link it to the base records. Unfortunately, many modern databases completely lack PII, right from the data collection stage. The result is that such a data source would remain in a silo. It is not like all is lost in such a situation, as they can still be used for trend analysis. But to employ multisource data for one-to-one targeting, we really need to establish the connection among various data worlds.

Even if the connection cannot be made to household, individual or email levels, I would not give up entirely, as we can still target based on IP addresses, which may lead us to some geographic denominations, such as ZIP codes. I’d take ZIP-level targeting anytime over no targeting at all, even though there are many analytical and summarization steps required for that (more on that subject in future articles).

Not having PII or any hard matchkey is not a complete deal-breaker, but the maneuvering space for analysts and marketers decreases significantly without it. That is why the existence of PII, or even ZIP codes, is the first thing that I check when looking into a new data source. I would like to free them from isolation.

7. Delivery Mechanisms
Users judge databases based on visualization or reporting tool sets that are attached to the database. As I mentioned earlier, that is like judging the entire building based just on the window treatments. But for many users, that is the reality. After all, how would a casual user without programming or statistical background would even “see” the data? Through tool sets, of course.

But that is the only one end of it. There are so many types of platforms and devices, and the data must flow through them all. The important point is that data is useless if it is not in the hands of decision-makers through the device of their choice, at the right time. Such flow can be actualized via API feed, FTP, or good, old-fashioned batch installments, and no database should stay too far away from the decision-makers. In my earlier column, I emphasized that data players must be good at (1) Collection, (2) Refinement, and (3) Delivery (refer to “Big Data is Like Mining Gold for a Watch—Gold Can’t Tell Time“). Delivering the answers to inquirers properly closes one iteration of information flow. And they must continue to flow to the users.

8. User-Friendliness
Even when state-of-the-art (I apologize for using this cliché) visualization, reporting or drill-down tool sets are attached to the database, if the data variables are too complicated or not intuitive, users will get frustrated and eventually move away from it. If that happens after pouring a sick amount of money into any data initiative, that would be a shame. But it happens all the time. In fact, I am not going to name names here, but I saw some ridiculously hard to understand data dictionary from a major data broker in the U.S.; it looked like the data layout was designed for robots by the robots. Please. Data scientists must try to humanize the data.

This whole Big Data movement has a momentum now, and in the interest of not killing it, data players must make every aspect of this data business easy for the users, not harder. Simpler data fields, intuitive variable names, meaningful value sets, pre-packaged variables in forms of answers, and completeness of a data dictionary are not too much to ask after the hard work of developing and maintaining the database.

This is why I insist that data scientists and professionals must be businesspeople first. The developers should never forget that end-users are not trained data experts. And guess what? Even professional analysts would appreciate intuitive variable sets and complete data dictionaries. So, pretty please, with sugar on top, make things easy and simple.

9. Cost
I saved this important item for last for a good reason. Yes, the dollar sign is a very important factor in all business decisions, but it should not be the sole deciding factor when it comes to databases. That means CFOs should not dictate the decisions regarding data or databases without considering the input from CMOs, CTOs, CIOs or CDOs who should be, in turn, concerned about all the other criteria listed in this article.

Playing with the data costs money. And, at times, a lot of money. When you add up all the costs for hardware, software, platforms, tool sets, maintenance and, most importantly, the man-hours for database development and maintenance, the sum becomes very large very fast, even in the age of the open-source environment and cloud computing. That is why many companies outsource the database work to share the financial burden of having to create infrastructures. But even in that case, the quality of the database should be evaluated based on all criteria, not just the price tag. In other words, don’t just pick the lowest bidder and hope to God that it will be alright.

When you purchase external data, you can also apply these evaluation criteria. A test-match job with a data vendor will reveal lots of details that are listed here; and metrics, such as match rate and variable fill-rate, along with complete the data dictionary should be carefully examined. In short, what good is lower unit price per 1,000 records, if the match rate is horrendous and even matched data are filled with missing or sub-par inferred values? Also consider that, once you commit to an external vendor and start building models and analytical framework around their its, it becomes very difficult to switch vendors later on.

When shopping for external data, consider the following when it comes to pricing options:

  • Number of variables to be acquired: Don’t just go for the full option. Pick the ones that you need (involve analysts), unless you get a fantastic deal for an all-inclusive option. Generally, most vendors provide multiple-packaging options.
  • Number of records: Processed vs. Matched. Some vendors charge based on “processed” records, not just matched records. Depending on the match rate, it can make a big difference in total cost.
  • Installment/update frequency: Real-time, weekly, monthly, quarterly, etc. Think carefully about how often you would need to refresh “demographic” data, which doesn’t change as rapidly as transaction data, and how big the incremental universe would be for each update. Obviously, a real-time API feed can be costly.
  • Delivery method: API vs. Batch Delivery, for example. Price, as well as the data menu, change quite a bit based on the delivery options.
  • Availability of a full-licensing option: When the internal database becomes really big, full installment becomes a good option. But you would need internal capability for a match and append process that involves “soft-match,” using similar names and addresses (imagine good-old name and address merge routines). It becomes a bit of commitment as the match and append becomes a part of the internal database update process.

Business First
Evaluating a database is a project in itself, and these nine evaluation criteria will be a good guideline. Depending on the businesses, of course, more conditions could be added to the list. And that is the final point that I did not even include in the list: That the database (or all data, for that matter) should be useful to meet the business goals.

I have been saying that “Big Data Must Get Smaller,” and this whole Big Data movement should be about (1) Cutting down on the noise, and (2) Providing answers to decision-makers. If the data sources in question do not serve the business goals, cut them out of the plan, or cut loose the vendor if they are from external sources. It would be an easy decision if you “know” that the database in question is filled with dirty, sporadic and outdated data that cost lots of money to maintain.

But if that database is needed for your business to grow, clean it, update it, expand it and restructure it to harness better answers from it. Just like the way you’d maintain your cherished automobile to get more mileage out of it. Not all databases are created equal for sure, and some are definitely more equal than others. You just have to open your eyes to see the differences.

Focus Group of One

If you’re sending your marketing campaigns without benefit of A/B or multi-variant testing—most companies admit to fewer than five tests per month—you are effectively acting as a focus group of one. You are assuming all of your constituents feel the same way about your campaign as you do. Big mistake.

If you’re sending your marketing campaigns without benefit of A/B or multi-variant testing—most companies admit to fewer than five tests per month—you are effectively acting as a focus group of one. You are assuming all of your constituents feel the same way about your campaign as you do. Big mistake.

Most of us have a least a bit of familiarity with A/B testing and have integrated it into some of our deployments. Testing subject line A against subject line B is likely the most common test, but with A/B testing you can go so much further—both simple and complex—for instance:

  • Best time of day for sending each of your email types (e.g., newsletter, offers)
  • Best day for sending each type of email
  • Frequency of sending each type of email
  • Length of subject line
  • Personalization within the subject line
  • Personalization within the message
  • Squeeze page vs. landing page
  • Conversion lift when video, demo or meeting booking are included
  • Diagnosing content errors
  • Challenging long-held behavior assumptions
  • Calls to action
  • Color
  • Format and design
  • Writing style (casual, conversational, sensational, business)
  • From name and email address (business vs. personal)

A/B and multi-variant testing enable you to learn what makes your prospects, leads, subscribers and customers tick. When you adopt a consistent testing process, your accumulative results will provide you with the knowledge to implement dramatic changes producing a measurable impact across campaigns, landing pages, websites and all other inbound and outbound initiatives.

We have a client whose singular call to action in every email is to discount their product, and each offer is more valuable than the last. When I asked how well this worked, they admitted, the bigger the discount, the more they sold. When pressed, however, they could not tell me the ROI of this approach. Sure, they sold more widgets, but at the discount level they offered, they also made far less profit.

I suggested an A/B-laden drip campaign offering no discounts, and instead providing links to testimonials, case studies, demos of their product, book-a-meeting links, and other inbound content. In this way, we were changing their position from asking for the business to earning the business. While I admit this usually lengthens the sales cycle, it also means money is not being left on the table unnecessarily.

For this client, the change in approach was simply too dramatic and they found they couldn’t stick with it long enough to gather the data needed to make long-term business decisions. The limited of data they were able to collect in the first few emails did show, however, an inbound approach deserved strong consideration by their organization.

Not all A/B testing need be this dramatic—we could have started them off with a less-committed approach. My takeaway was: You don’t have to learn it all now; A/B testing can be integrated in a small way. Whether you go all out or an occasional test, A/B data is useless if you do not set measurable goals. Measurable goals mean you will establish:

  • Required return on investment
  • Vehicle (email, direct mail, other)
  • What to test
  • Audience
  • Time frame
  • Testing protocol
  • How to integrate what you’ve learned into future campaigns

If your email application does not support A/B testing, you can use a more automated approach. Simply create two versions of your marketing campaign and divide your list randomly in half—unless, of course, what you’re testing is something within your list, such as gender or locale.

I often am in search of information well beyond opens, clicks and visits, so I turn to Email on Acid for email heat maps and Crazy Egg for landing page and website heat maps. While these are effective on live pages and campaigns, it’s not required you deploy A/B testing to a live audience. Testing can be just as effective with a small focus group, just be sure it’s not a focus group of one.

PPC Shockers and Secrets

Pay per click (PPC), particularly Google AdWords, is a marketing channel that can produce profitable results for your business, whether your goal is lead generation or sales. I have been managing PPC for businesses, as an in-house marketing leader as well as marketing consultant, for over a decade now. Though the years, I have noticed many secrets to success that I wanted to share—especially with business owners and marketers that haven’t tried PPC yet.

Pay per click (PPC), particularly Google AdWords, is a marketing channel that can produce profitable results for your business, whether your goal is lead generation or sales.

I have been managing PPC for businesses, as an in-house marketing leader as well as marketing consultant, for over a decade now.

Though the years, I have noticed many secrets to success that I wanted to share—especially with business owners and marketers that haven’t tried PPC yet.

First, I’d like to clear the air about a big shocker … or actually a fallacy … that you need a big budget to run an effective PPC campaign.

You don’t. If you happen to have a large budget, your ads will be shown more and you can spread out your ad groups and test different types. With a smaller budget, you do need to be more judicious with your efforts. But if you market smarter, not broader, your campaigns can still produce positive results.

I have run PPC campaigns with total monthly budgets of $1,000. I have run campaigns with total daily maximum budgets ranging from $25 to $50. These campaigns brought in both sales and leads, despite their limited spending. But they do require active management, strategic thinking, deep PPC knowledge and refinement/optimization.

The PPC Tri-Pod
What is going to determine the cost and return of your campaign are three simple things I call the “PPC Tri-pod”, as it supports your entire PPC efforts:

  1. Keywords
  2. Creative (or banner ad, if it’s running on the display network)
  3. Redirect URL

So in order for you to get the most bang for your buck with PPC, you should be aware of a few things regarding the PPC Tri-pod:

Keywords. The more popular the keyword, the more cost per click (CPC) it’s going to have. So it’s very important to do your keyword research before you start selecting your keywords as you’re setting up your campaign.

I like to use Keywordspy.com. The “lite” version is free, but you can also upgrade to the full version and see more results and have more capabilities for a monthly fee. Google used to have its Keyword External Tool, which has since morphed into Google AdWords Keyword Planner. You need a Gmail account to access this free tool.

Either of these tools will allow you to enter keywords or keyword phrases and then view popularity (actual search results), as well as what the average CPCs are. This is important for your keyword selection and bidding. You can also type in your “core” or focus keywords and get additional ad group/keyword ideas. To help refine your search terms, you can also choose broad match, broad match modifier, phrase match, exact match and negative match.

If you pick a word that is too vague or too under-searched, your ad will not see much (or any) action. Impressions will either not be served, or if they are served (in the case of a vague word), it may cost you a high CPC. In addition, a vague keyword may not be relevant enough to get you a good conversion rate. Because you pay by the click, your goal is to monetize that click by getting an instant conversion. And conversions, my friends, will be the role of the landing page. I’ll talk about that more in a moment.

Creative. This is your text ad (or banner ad, if you’re running in AdWords’ display network). For Google to rank your ad favorably, and more importantly, for you to get the best conversion results possible—there needs to be a relevancy and synergy between your keyword, text ad and landing page. Google will let you know if you’re not passing muster by your ad’s page position and quality score. Once you’ve carefully researched and selected your ad group keywords, you’ll want to make sure those keywords are consistent across the board with your ad and landing page. Your text ad has four visible lines with limited character count:

  1. Headline (25 Characters)
  2. Description Line 1 (35 Characters)
  3. Description Line 2 (35 Characters)
  4. Display URL (35 Characters)

Your keyword must appear in your text ad, as well as follow through and appear in the content of your landing page.

This will give you a good quality rank with Google, but also help qualify the prospect and carry the relevancy of the ad through to the landing page. Why is this important? It helps maintain consistency of the message and also set expectations with the end user. You don’t want to present one ad, and then have a completely different landing page come up.

Not only is that a “bait and switch,” but it’s costly. Because you’re paying for clicks, a great ad that is compelling and keyword rich, but not cohesive to your landing page, will not convert as well as one that is. And your campaign will actually lose conversions.

Redirect URL. This is your landing page. Different goals and different industries will have different formats. A lead generation campaign, which is just looking to collect email addresses to build an opt-in email list, will be a “squeeze page.” This is simply a landing page with a form asking for first name and email address in return for giving something away for free—albeit a bonus report, free newsletter subscription or similar. It got its name because it’s “squeezing” an email address from the prospect. Some retail campaigns will direct prospects directly to e-commerce sites or catalog pages (as opposed to a sales page). Direct response online marketers will drive their traffic to a targeted promotional landing page where it’s not typically a Web page where there’s other navigation or distractions that will take the prospect away from the main goal. It’s more streamlined and focused. The copy is not technical, it’s compelling and emotional, like promotional copy you would see in a sales letter. The anatomy of your redirect URL will vary on your goal and offer. It will take optimization and testing to see what’s working and what’s not. And that’s par for the course. If you’re testing, I suggest elements that scream and not whisper, such as long copy vs. short copy, or headlines and leads that are different themes. However, no matter what your goal, whether it’s going for the sale or the email address, you still need keyword consistency between all creative elements.

Tips And Tricks For Maximum ROI
Whether you have a big or small budget, there are a few things I’ve learned during the years that help the overall performance of a PPC campaign. Some of these are anecdotal, so if you’ve seen otherwise, I suggest testing to see if it makes a difference to your particular industry.

Ad and Landing Page. In general, I have noticed that shorter, to the point, landing pages produce better results. And the rationale is quite obvious. People searching the Web are looking for quick solutions to a problem. This means your creatives have to not only be keyword rich, but compelling and eye-caching. You have seconds to grab a Web surfer’s attention and get them to click. In the same sense, the landing page has to be equally relevant and persuasive, and typically shorter in copy. Keep in mind Google has many rules surrounding ad copy development. So write your text ads in accordance to its advertising policy.

Price Point. Again, in my personal experience, most Web surfers have a price threshold. And that’s items under about $79. When running a PPC campaign, think about price points that are more tolerable to “cold” prospects; that is, people who haven’t built a relationship with you or know anything about you. They have no brand loyalty. They don’t know you from Adam. So getting a sale at a lower price point is an easier sell than a product you have that costs hundreds of dollars. Luxury items or items with strong recognition and brand loyalty are the exception to that rule. As a direct response marketer, I urge you to price test and see for yourself.

Campaign Set-up. There are a few tactics I notice that help with ad exposure, clicks and saving money. When you’re setting up your campaign you can day-part, frequency cap and run ad extensions. Day parting allows you to select the hours of the day you’d like your campaign to run; ad extensions allow you to add components to your text ad to help visibility and call to action—such as location, site links, reviews and more; And frequency capping lets you set a threshold on how many times you’d like a given person to see your ad (based on impressions).

PPC Networks. It’s smart not to put all your eggs in one basket. In addition to Google AdWords, try running campaigns on other PPC networks, such as Bing/Yahoo, Adroll (retargeting through Facebook), Advertising.com/AdSonar.com, SiteScout.com (formerly Adbrite.com), and Kanoodle.com. Then see where you get the best cost per click, cost per conversion and overall results.

I’ve only touched the surface here. There are more tactics and features that can help a PPC campaign’s performance. So get yourself familiar with it, read up on the best practices, and don’t be afraid to put your toe in the water. As with any marketing tactic, some channels will work for your business, and some won’t. But you won’t know unless you test. Just remember the foundation of success hinges on the PPC Tri-Pod. The possibilities are endless.

The World Needs More Glennas

I’ve worn glasses since the seventh grade. And I celebrated a new level of euphoria when I purchased my first pair of contact lenses as a senior in college. But the fact remains, when I take out my contacts at night, I still need to wear glasses. So imagine how I suddenly got a pit in my stomach when I went to put on my glasses while spending the night in a NY hotel room, only to discover they were not in my suitcase

I’ve worn glasses since the seventh grade. And I celebrated a new level of euphoria when I purchased my first pair of contact lenses as a senior in college.

But the fact remains, when I take out my contacts at night, I still need to wear glasses—to see the TV, to make sure it’s the dog I’m letting in before I retire, and to ensure my kids are actually brushing their teeth from my not-so-secret vantage point down the hallway.

So imagine how I suddenly got a pit in my stomach when I went to put on my glasses while spending the night in a NY hotel room, only to discover they were not in my suitcase – or in my purse. I emptied the entire contents of both, and after squinting carefully at every single item, I reached the frightening conclusion that I had left them somewhere in my travels.

Between this moment and the last time I saw them, I had driven in a rental car, sat in an airport, flown on a plane, taken a train, taken a bus and walked 12 blocks in Manhattan. My glasses could have fallen out of my bag anywhere!

I started the task of retracing my steps, already convinced I would need to fork over a few hundred bucks for a new pair.

Since I had spent the weekend at my alma mater in Canada, I called the hotel in Ottawa and left a message for the head of housekeeping. After several phone calls back and forth and a thorough dissection of my previous room, the woman reported that my glasses were not found.

My next call was to the car rental company at the Ottawa airport, and luckily, the phone was answered by Glenna. She was pleasant enough, and promised to look in the “lost and found” and asked if I would please hold. About 15 minutes later she came back on the line and reported she had my glasses in her hand! While they were not in the lost and found, she had gone back into my rental vehicle and found them under the passenger seat.

“Will you be able to swing by and pick them up this week?” Glenna inquired.

“Um … no … I have no plans to return to Ottawa anytime soon.” I responded, “Any chance you could Fed Ex them to me in San Francisco?”

Glenna pondered that question for a few seconds, and hesitated, only fleetingly, before asking how that might work.

I explained that if she could give me her email address, I’d be happy to email her all the delivery details including my Fed Ex number, and that all she’d need to do would be package them up, fill out the form, and drop the box in a Fed Ex box. She agreed and gave me her email address.

It turns out that sending an international shipment of a pair of glasses is NOT that easy!

Glenna contacted Fed Ex, and they sent her a form to fill out, including something called the “Drop Ball” test. It seems Fed Ex needs to have proof of impact resistance, “within the meaning of 21 cfr 801.410″—whatever that means. However, it didn’t seem to deter Glenna!

She dutifully completed the forms, completed the Drop Ball test, and emailed me the tracking information.

Today, a Fed Ex box arrived from Glenna. Inside was a Fed Ex envelope (smart girl—she used it as “bubble wrap” to protect my glasses). But she went one step further. Inside the envelope was another box (turns out it was a Kleenex box), wrapped with a ton of paper and taped up tightly. And inside the Kleenex box was my (very expensive) pair of glasses.

Glenna had done everything she could think of to protect them and make sure they arrived without a scratch.

How does this all relate to marketing?

Brands spend millions of dollars trying to acquire and retain customers. But if you have a bad brand experience, you tend to bad-mouth the brand and never do business with them again. And in a world of crappy customer service, with workers who often just don’t seem to care, Glenna stands out as someone who will always go that extra mile.

So thank you Glenna—and thank you Budget Rent-A-Car for hiring Glenna. It goes without saying that I’m now a loyal Budget user for life!