Find Working Email Addresses in Under 30 Seconds

Using cold emailing as a prospecting tactic? Beware of 95 percent of the email lookup or “guesser” services out there. Most of these online tools promise to find email addresses of your targets — but end up providing invalid email addresses.

EmailUsing cold emailing as a prospecting tactic? Beware of 95 percent of the email lookup or “guesser” services out there. Most of these online tools promise to find email addresses of your targets — but end up providing invalid email addresses. Here is a better way to find email addresses of prospects using tools like Rapportive or new-comer Full Contact.

I’m literally showing you (see video below) how to guess anyone’s professional or “work” email address when prospecting for new business.

In under 30 seconds. Yes, really. Many times, in under 10 seconds and with good success.

Will This Help Me?
If you’re using cold emailing this approach is gold. If you’re investing in LinkedIn’s InMail via Navigator or a Premium product this will also be of benefit to you. Especially if you’re not getting the response you’d like.

“Going direct” (to the corporate inbox) is often a better way to start.

Remember, you should be exceptional at provoking response from prospects before investing in InMail. If you’re not it risks becoming turned-off to prospecting in general.

Experiment with standard email until you develop expertise in provoking response at least 40 percent of the time. Then bring that successful approach to the realm of InMail.

2 Email Guesser Tools (That Actually Work)
“I tested Email Hunter on two companies I know. It guessed at around 12-15 emails addresses for each, every single one was wrong,” says digital sales prospecting exert Bruce Johnston, who uses the approach I’m demonstrating today.
There are a few online email guesser and validation services that will tell you if your guess is an actual, working email address. These include MailTester, and bunches of others.

But this is not the best starting point for you. For two reasons:

  • There’s a faster way … and
  • a valid email does not mean it’s an email your prospect is tending to. It could be an old, abandoned email.

I’ve found using Rapportive or Full Contact (both free) to be much faster. If one of these tools fails, I move on to the other email validation services or buy the complete contact data from a provider like

Now I’ll show you how to do it …

Converting Your Social Media Triple-Fs: Friends, Followers and Fans

I’ve heard many gurus, marketers and publishers brag about their social media followers. They’ll say things like, “Isn’t it great … I’ve got 10,000 fans on Facebook” or “I have more than 15,000 followers on Twitter.” Then I’ll ask them how many free e-newsletter subscribers they have. And they’ll reply, “I haven’t had time to build a list yet. I don’t have an e-newsletter.”

I’ve heard many gurus, marketers and publishers brag about their social media followers. They’ll say things like, “Isn’t it great … I’ve got 10,000 fans on Facebook” or “I have more than 15,000 followers on Twitter.” Then I’ll ask them how many free e-newsletter subscribers they have. And they’ll reply, “I haven’t had time to build a list yet. I don’t have an e-newsletter.”

Well, in my opinion, they’ve won only half the battle …

It’s fantastic that they have a following on social media—people who seem to be interested in their messages (posts) and their overall philosophy. They can certainly cultivate these relationships to assist in their marketing efforts. However, I remind these gurus that the “fans” are following them. It’s a passive relationship. And there’s an awful lot of background noise in a news feed that can distract their fans.

If you don’t have fans’ email addresses, then you cannot have one-on-one communications with them. Building and cultivating a list is a fundamental business strategy for sales growth.

In the publishing world, a list (email addresses of free or paid subscribers) is sacred. It’s one of the most valuable things you own. You protect it and treat it with care, because your list is your financial bread and butter. It’s made up of people—customers and subscribers—who can make or break your business through their purchasing power or lack thereof.

Your list is also your leverage—what you use when reaching out to other synergistic publishers and friendly competitors to do reciprocal JV (joint venture) swaps and revenue share deals.

So, if you’re an online publisher, guru or business owner who has social media followers but no list, you’re at a disadvantage. Initiate a plan to capture your fans’ email addresses immediately and get permission to open up the personal lines of communication.

I recommend that you make a special conversion effort to encourage social media followers to give you their email addresses, or, as we say, “opt in” to receive your marketing messages.

This typically involves creating strong promotional copy and a lead-generation landing page (also know as squeeze page), where the goal is to capture the email address of the friend, follower or fan.

The offer should be something that will resonate with your fan, such as a useful and relevant free bonus. Some popular examples are a whitepaper, e-newsletter or e-alert subscription, audio download, bonus video, webinar or teleseminar..

Some marketers also offer coupon codes or gift certificates in exchange for an email address or the option to be in a “VIP club,” where you’re the first to hear about special offers.

Freebies will vary based on what you have to offer in exchange. Ideally, this is something that has a perceived value and is immediate and relevant. You run the campaign for a two-week period at a time, mixing your conversion messages with your regular, organic daily posts. It’s ideal to drive traffic to specially coded pages so you can track traffic and conversions. You can also make sure your sign up box on your website’s home page is up and ready for stray organic traffic. Then you monitor email sign-ups and website traffic (via Google Analytics), to ensure list growth and traffic source referrals.

Aside from captivating copy, many variables come into play to make sure the effort is successful. These include making sure email collection fields are at the top, middle and bottom of the lead-generation landing page being used, as well as in a static (fixed) location on your website. There should also be links to your privacy policy and an assurance statement alleviating any concern about email addresses being rented or sold to third parties.

It’s also critical to clearly disclose before users submit their email addresses that opting in to receive your freebie also gives them a complimentary subscription to your e-newsletter (if applicable), along with special offers from time to time.

Finally, you should follow up with a series of autoresponder (targeted messages) emails welcoming your new subscribers, reminding them how they signed up, offering strong editorial content and special new subscriber offers.

These emails facilitate bonding; validate that the correct email was sent; ensures that the user is aware of the sign up; helps reduce false “do not mail” reports, email bounces and general attrition; and most importantly, improved life time value.

So before you get enamored with your Facebook following, realize that to monetize these names takes a conversion strategy. Once you start building your list, you’ll add a whole new value to your businesses valuation.

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 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.

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 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),, (formerly, and 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.

It’s All About Ranking

The decision-making process is really all about ranking. As a marketer, to whom should you be talking first? What product should you offer through what channel? As a businessperson, whom should you hire among all the candidates? As an investor, what stocks or bonds should you purchase? As a vacationer, where should you visit first?

The decision-making process is really all about ranking. As a marketer, to whom should you be talking first? What product should you offer through what channel? As a businessperson, whom should you hire among all the candidates? As an investor, what stocks or bonds should you purchase? As a vacationer, where should you visit first?

Yes, “choice” is the keyword in all of these questions. And if you picked Paris over other places as an answer to the last question, you just made a choice based on some ranking order in your mind. The world is big, and there could have been many factors that contributed to that decision, such as culture, art, cuisine, attractions, weather, hotels, airlines, prices, deals, distance, convenience, language, etc., and I am pretty sure that not all factors carried the same weight for you. For example, if you put more weight on “cuisine,” I can see why London would lose a few points to Paris in that ranking order.

As a citizen, for whom should I vote? That’s the choice based on your ranking among candidates, too. Call me overly analytical (and I am), but I see the difference in political stances as differences in “weights” for many political (and sometimes not-so-political) factors, such as economy, foreign policy, defense, education, tax policy, entitlement programs, environmental issues, social issues, religious views, local policies, etc. Every voter puts different weights on these factors, and the sum of them becomes the score for each candidate in their minds. No one thinks that education is not important, but among all these factors, how much weight should it receive? Well, that is different for everybody; hence, the political differences.

I didn’t bring this up to start a political debate, but rather to point out that the decision-making process is based on ranking, and the ranking scores are made of many factors with different weights. And that is how the statistical models are designed in a nutshell (so, that means the models are “nuts”?). Analysts call those factors “independent variables,” which describe the target.

In my past columns, I talked about the importance of statistical models in the age of Big Data (refer to “Why Model?”), and why marketing databases must be “model-ready” (refer to “Chicken or the Egg? Data or Analytics?”). Now let’s dig a little deeper into the design of the “model-ready” marketing databases. And surprise! That is also all about “ranking.”

Let’s step back into the marketing world, where folks are not easily offended by the subject matter. If I give a spreadsheet that contains thousands of leads for your business, you wouldn’t be able to tell easily which ones are the “Glengarry Glen Ross” leads that came from Downtown, along with those infamous steak knives. What choice would you have then? Call everyone on the list? I guess you can start picking names out of a hat. If you think a little more about it, you may filter the list by the first name, as they may reflect the decade in which they were born. Or start calling folks who live in towns that sound affluent. Heck, you can start calling them in alphabetical order, but the point is that you would “sort” the list somehow.

Now, if the list came with some other valuable information, such as income, age, gender, education level, socio-economic status, housing type, number of children, etc., you may be able to pick and choose by which variables you would use to sort the list. You may start calling the high income folks first. Not all product sales are positively related to income, but it is an easy way to start the process. Then, you would throw in other variables to break the ties in rich areas. I don’t know what you’re selling, but maybe, you would want folks who live in a single-family house with kids. And sometimes, your “gut” feeling may lead you to the right place. But only sometimes. And only when the size of the list is not in millions.

If the list was not for prospecting calls, but for a CRM application where you also need to analyze past transaction and interaction history, the list of the factors (or variables) that you need to consider would be literally nauseating. Imagine the list contains all kinds of dollars, dates, products, channels and other related numbers and figures in a seemingly endless series of columns. You’d have to scroll to the right for quite some time just to see what’s included in the chart.

In situations like that, how nice would it be if some analyst threw in just two model scores for responsiveness to your product and the potential value of each customer, for example? The analysts may have considered hundreds (or thousands) of variables to derive such scores for you, and all you need to know is that the higher the score, the more likely the lead will be responsive or have higher potential values. For your convenience, the analyst may have converted all those numbers with many decimal places into easy to understand 1-10 or 1-20 scales. That would be nice, wouldn’t it be? Now you can just start calling the folks in the model group No. 1.

But let me throw in a curveball here. Let’s go back to the list with all those transaction data attached, but without the model scores. You may say, “Hey, that’s OK, because I’ve been doing alright without any help from a statistician so far, and I’ll just use the past dollar amount as their primary value and sort the list by it.” And that is a fine plan, in many cases. Then, when you look deeper into the list, you find out there are multiple entries for the same name all over the place. How can you sort the list of leads if the list is not even on an individual level? Welcome to the world of relational databases, where every transaction deserves an entry in a table.

Relational databases are optimized to store every transaction and retrieve them efficiently. In a relational database, tables are connected by match keys, and many times, tables are connected in what we call “1-to-many” relationships. Imagine a shopping basket. There is a buyer, and we need to record the buyer’s ID number, name, address, account number, status, etc. Each buyer may have multiple transactions, and for each transaction, we now have to record the date, dollar amount, payment method, etc. Further, if the buyer put multiple items in a shopping basket, that transaction, in turn, is in yet another 1-to-many relationship to the item table. You see, in order to record everything that just happened, this relational structure is very useful. If you are the person who has to create the shipping package, yes, you need to know all the item details, transaction value and the buyer’s information, including the shipping and billing address. Database designers love this completeness so much, they even call this structure the “normal” state.

But the trouble with the relational structure is that each line is describing transactions or items, not the buyers. Sure, one can “filter” people out by interrogating every line in the transaction table, say “Select buyers who had any transaction over $100 in past 12 months.” That is what I call rudimentary filtering, but once we start asking complex questions such as, “What is the buyer’s average transaction amount for past 12 months in the outdoor sports category, and what is the overall future value of the customers through online channels?” then you will need what we call “Buyer-centric” portraits, not transaction or item-centric records. Better yet, if I ask you to rank every customer in the order of such future value, well, good luck doing that when all the tables are describing transactions, not people. That would be exactly like the case where you have multiple lines for one individual when you need to sort the leads from high value to low.

So, how do we remedy this? We need to summarize the database on an individual level, if you would like to sort the leads on an individual level. If the goal is to rank households, email addresses, companies, business sites or products, then the summarization should be done on those levels, too. Now, database designers call it the “de-normalization” process, and the tables tend to get “wide” along that process, but that is the necessary step in order to rank the entities properly.

Now, the starting point in all the summarizations is proper identification numbers for those levels. It won’t be possible to summarize any table on a household level without a reliable household ID. One may think that such things are given, but I would have to disagree. I’ve seen so many so-called “state of the art” (another cliché that makes me nauseous) databases that do not have consistent IDs of any kind. If your database managers say they are using “plain name” or “email address” fields for matching or summarization, be afraid. Be very afraid. As a starter, you know how many email addresses one person may have. To add to that, consider how many people move around each year.

Things get worse in regard to ranking by model scores when it comes to “unstructured” databases. We see more and more of those, as the data sources are getting into uncharted territories, and the size of the databases is growing exponentially. There, all these bits and pieces of data are sitting on mysterious “clouds” as entries on their own. Here again, it is one thing to select or filter based on collected data, but ranking based on some statistical modeling is simply not possible in such a structure (or lack thereof). Just ask the database managers how many 24-month active customers they really have, considering a great many people move in that time period and change their addresses, creating multiple entries. If you get an answer like “2 million-ish,” well, that’s another scary moment. (Refer to “Cheat Sheet: Is Your Database Marketing Ready?”)

In order to develop models using variables that are descriptors of customers, not transactions, we must convert those relational or unstructured data into the structure that match the level by which you would like to rank the records. Even temporarily. As the size of databases are getting bigger and bigger and the storage is getting cheaper and cheaper, I’d say that the temporary time period could be, well, indefinite. And because the word “data-mart” is overused and confusing to many, let me just call that place the “Analytical Sandbox.” Sandboxes are fun, and yes, all kinds of fun stuff for marketers and analysts happen there.

The Analytical Sandbox is where samples are created for model development, actual models are built, models are scored for every record—no matter how many there are—without hiccups; targets are easily sorted and selected by model scores; reports are created in meaningful and consistent ways (consistency is even more important than sheer accuracy in what we do), and analytical language such as SAS, SPSS or R are spoken without being frowned up by other computing folks. Here, analysts will spend their time pondering upon target definitions and methodologies, not about database structures and incomplete data fields. Have you heard about a fancy term called “in-database scoring”? This is where that happens, too.

And what comes out of the Analytical Sandbox and back into the world of relational database or unstructured databases—IT folks often ask this question—is going to be very simple. Instead of having to move mountains of data back and forth, all the variables will be in forms of model scores, providing answers to marketing questions, without any missing values (by definition, every record can be scored by models). While the scores are packing tons of information in them, the sizes could be as small as a couple bytes or even less. Even if you carry over a few hundred affinity scores for 100 million people (or any other types of entities), I wouldn’t call the resultant file large, as it would be as small as a few video files, really.

In my future columns, I will explain how to create model-ready (and human-ready) variables using all kinds of numeric, character or free-form data. In Exhibit A, you will see what we call traditional analytical activities colored in dark blue on the right-hand side. In order to make those processes really hum, we must follow all the steps that are on the left-hand side of that big cylinder in the middle. Preventing garbage-in-garbage-out situations from happening, this is where all the data get collected in uniform fashion, properly converted, edited and standardized by uniform rules, categorized based on preset meta-tables, consolidated with consistent IDs, summarized to desired levels, and meaningful variables are created for more advanced analytics.

Even more than statistical methodologies, consistent and creative variables in form of “descriptors” of the target audience make or break the marketing plan. Many people think that purchasing expensive analytical software will provide all the answers. But lest we forget, fancy software only answers the right-hand side of Exhibit A, not all of it. Creating a consistent template for all useful information in a uniform fashion is the key to maximizing the power of analytics. If you look into any modeling bakeoff in the industry, you will see that the differences in methodologies are measured in fractions. Conversely, inconsistent and incomplete data create disasters in real world. And in many cases, companies can’t even attempt advanced analytics while sitting on mountains of data, due to structural inadequacies.

I firmly believe the Big Data movement should be about

  1. getting rid of the noise, and
  2. providing simple answers to decision-makers.

Bragging about the size and the speed element alone will not bring us to the next level, which is to “humanize” the data. At the end of the day (another cliché that I hate), it is all about supporting the decision-making processes, and the decision-making process is all about ranking different options. So, in the interest of keeping it simple, let’s start by creating an analytical haven where all those rankings become easy, in case you think that the sandbox is too juvenile.

Email Marketing: To Open or Not To Open …

For many of us, choosing the from name is a simple task. We send it from the person to whom we want the recipient to respond or connect, but hold on … did you test that?

For many of us, choosing the from name is a simple task. We send it from the person to whom we want the recipient to respond or connect, but hold on … did you test that?

One of our clients sends more than a million emails daily to their subscribers. They have built their list using a variety of resources, one of which was to purchase three million self-identified target recipients, but they also used co-registration with a daily newsletter offer to acquire another million names over a span of a few months. The co-registration names were a double-opt in so ideally should have produced stellar results and highly qualified names, but that didn’t actually turn out to be the case.

After sending to the purchased list, we tossed it completely due to the very high number of spam traps we managed to trigger in our first two sends. With those names eliminated, we focused on the co-registration list, which we segmented into large groups to receive the daily message they had been offered. This was done through more than a dozen different ESPs.

As we saw it, job one was to validate the email addresses were deliverable, not spam traps, and were—at best—being opened. As we suspected, a number of them were spam traps, so we dialed it back and a great deal of time to a deep-cleanse effort of sending in very small batches (about 200 per day per ESP) in order to more easily stop the cycle if we irritated more spam sensors. (It takes a long, damn time to send to millions of recipients at the rate of 200 per day.)

Using this process, once we reached 250,000 verified emails, we sent to those in larger groups through our three best-performing ESPs—those with whom we historically saw the best deliverability rates. We continued these two steps with the balance of the names and applied the deep-cleanse process for new names still coming in through the co-registration sites (about 500 names per day).

The combination of the deep cleanse and slow send improved our results drastically. All emails were deliverable, unsubscribes were low, but open rates were still lagging. Since this was a daily message to which the users had specifically subscribed, we were pretty sure there was room for improvement even though the list was growing faster than the combined attrition rate (unsubscribes + undeliverable + spam complaints), and traffic to this site was flourishing.

While our client does not sell anything on their site, they do sell ad space in the daily email, monthly newsletter and on their website. The number of views for these ads is critical to our client’s revenue. Emails going unopened, being marked as spam, or gaining an unsubscribe are not generating revenue in a click or impressions ad placement.

Regardless of which email application the subscriber uses, there are two things they see: from and subject line. Some email applications will also show the preheader text, a preview, or other snippets to give the recipient more clues about the content. We chose to tackle first the sender information, and then work on the subject line. After all, there’s only so many ways we could say, “Here’s the daily email to which you have subscribed.”

The target audience for this daily email is largely male—not all male, mind you, but nearing the 85 percent mark. I suspected males would rather receive emails from women, so we started there. We also used tried other sender names and email addresses:

  • Company name
  • Site owner’s name (she has some visibility in this space, so we tried to parlay that recognition into opens)
  • General email address
  • Mature-sounding woman’s name
  • Young-sounding, woman’s name
  • Sexy woman’s name
  • Mature-sounding male name (in line with the target audience age group)
  • Young-sounding male name

We didn’t just change the from name, we created a matching from address for continuity and credibility (rather than use a system address such as For instance, if Brittni Jones was the from name, the address was

What we found, and what I’m sure you already know, is sender matters—in a big, important way; at least for this client.

I was right on one front: This primarily male constituency did open far more emails from Brittni than Edith, but they also liked getting emails from Trevor, a very close second. They didn’t read nearly as many emails from Bob, though Bob was more popular than using the company name. The actual statistics for this campaign are not important; your company would experience completely different results. The takeaway here is about testing and being relevant—even at the sender name and address level.

If your opens are suffering, think first about whether or not John Smith is convincing enough to get me to open, then remember: test, track, tweak. Repeat.