The Role of Brand Communicators in an Outbreak

A lot of the work we do in healthcare marketing and communications is predictable. Brand-building, patient acquisition, and organizational support. But when a new health threat emerges, brand communicators have to respond quickly to help people minimize their risk of infection and to keep fear from spreading.

A lot of the work we do in healthcare marketing and communications is predictable. Brand-building, patient acquisition, and organizational support are long-haul types of activities that you sustain throughout the year. But when a new health threat emerges, brand communicators have to respond quickly to help people minimize their risk of infection and to keep fear from spreading unnecessarily.

That continues to be the case with the Novel Coronavirus (COVID-19), which emerged from the city of Wuhan and Hubei province in China. Authorities suppressed news of the initial cases, so when it finally hit the news cycle, it seemed to appear menacingly overnight. From that point on, the media coverage was almost breathless in its reporting on the quarantine of millions and disturbing visuals of jammed hospitals turning people away. Some of the images circulated online were haunting.

Fear Spreads Faster Than Facts

Even though the Centers for Disease Control and Prevention (CDC) worked quickly to understand how COVID-19 spreads and its mortality rate, people thousands of miles away from the epicenter began to fear for their safety.

At times like these, brand communicators must find facts from trusted sources, like the CDC, and disseminate it across multiple touchpoints. The information has to be pushed out assertively, because fear raises cognitive barriers that make it even harder to absorb information and assess risk within an appropriate context. For example, at the same time that COVID-19 was making headlines, millions in the U.S. had the flu, more than 100,000 hospitalizations would occur, and more than 12,000 would die from its complications. Yet we are so accustomed to the flu that we perceive its risk as less than the risk of something new.

Spread Facts

If you work in healthcare, you are part of a crisis response team with a responsibility to share evidence-based facts to combat fear and misinformation. The outbreak continues and our thoughts are with those who are impacted.

But with an ongoing dose of information, we can help reduce the spread of unnecessary fear and the spread of the virus. Learn more about COVID-19 from the CDC.

7 Event Planning Tips and Tricks From the Pros

Event planning is an eloquent art that can leave a lasting impression on attendees. Strategic event planning can be used to create new relationships, promote a product and increase employee participation. When done right, an event will leave a positive lasting impression long after it has passed. Follow this easy to use, step-by-step guide to plan an event like the pros.

Event planning is an eloquent art that can leave a lasting impression on attendees. Strategic event planning can be used to create new relationships, promote a product and increase employee participation. When done right, an event will leave a positive lasting impression long after it has passed.

Follow this easy to use, step-by-step guide to plan an event like the pros.

1. Event Planning with a Purpose

The beginning stages of event planning can never start too early. The first thing you should focus on is the purpose of your event. Are you fundraising, holding an informational workshop or corporate event? Or maybe your event is a celebration like a birthday party, wedding or anniversary. Whatever the occasion, once you clearly define your purpose, other things will fall into place, including who will be attending, the décor and how the occasion will be organized.

2. Gather Volunteers

Event planning is hard work and it can be difficult to go it alone. If you know people who are willing to volunteer, you can start delegating specific tasks to them. Sending invites, welcoming guests and cleaning are things you should think about when considering who is going to do what. If you are unable to find people who can help you for free, consider hiring a crew.

3. Create an Event Budget

If you don’t create a budget, you run the risk of spending way more than you had anticipated. Think about the cost of location, staff, food and whatever other expenses will be incurred. Try to save money wherever possible.  This can be done by finding inexpensive venues and using volunteers rather than a hired staff.

4. Decide on the Event Time and Place

Before deciding on a date, think about what else might be happening around that time. If there are other events that are similar to yours happening on the same date, it may hurt your attendance. Also, consider working around holidays and school or work schedules.

When thinking about location, find something that will be easily accessible for your guests. Also, note that your venue should be booked in advance, so you can be sure it will be available on the date you are requesting. If you are planning an event in Detroit, Brooklyn Outdoor can provide an industrial chic loft with panoramic views of the city. Use of this space includes an attentive staff that can see to every last detail.

6. Other Logistics

Other logistics to be considered include parking, what items and equipment you will need, whether you want to provide giveaways for your guests to take home and whether you want to have a photographer present to document the event.

7. The Countdown

As the event gets closer, you will realize there is a lot of be done to make everything run smoothly. When you are about two weeks out from the event, you will want to think about meeting with your team, visiting the venue and confirming your guest list to make sure everyone is on the same page.

During this time, it is easy to become stressed out so do your best to keep calm. Careful planning in the early stages can help to eliminate some of the stress. Planning an event is a lot of work, but if you are well organized, it can go relatively smoothly.

Use My Personal Data, But Don’t Offend Me

I’m fine with companies collecting my data; however, how about providing me something in return?

I’m fine with companies collecting my data; however, how about providing me something in return?

I’m a huge college football fan and watched most of the 41 bowl games that just wrapped up with Alabama beating Georgia in the second-best bowl game of the year, next to the Rose Bowl.

Nissan is a significant sponsor of college football. It runs commercials throughout the games and has spent a lot of money producing the humorous Heisman House series that appears before the kickoff of major games.

I noticed the addition of a five-second tag at the end of a few Nissan commercials, saying it was the official vehicle of “Duke Blue Devil” fans. I live in Raleigh, N.C. There are a lot more University of North Carolina (UNC), N.C. State University (NCSU), and East Carolina (ECU) alumni in Raleigh than Duke alumni.

I can only assume I was targeted to receive this tag with programmatic advertising because I have two degrees from Duke. You can pick this up from Facebook, LinkedIn or Twitter. However, if you look deeper at my profiles and posts, you’ll learn pretty quickly that I’m not a Duke fan, I’m a UNC fan because of Dean Smith — the person and the coach.

Instead of making me feel an affinity to Nissan, it alienated me. Over the past 15 years, I’ve owned three Nissans, but just replaced my last one with a Hyundai. When it’s time to replace the current Hyundai, if we’re still owning cars, I will remember Nissan’s mistake. Is it significant enough for me to not consider a Nissan? We’ll see.

The amount of data companies have access to in order to identify the needs, wants, likes and dislikes of consumers is huge. Granted, we’re in the infancy of using this data to improve marketing; however, companies must be smarter about how they are going to use this data.

How about this? Focus on providing information of value to make customers’ and prospects’ lives simpler and easier instead of trying to make an emotional connection which, in fact, offends. It’s much less risky to tell your story than it is to attempt to make an emotional connection based on big data, which is inherently impersonal.

Watch the Attitude, Data Geeks

One-dimensional techies will be replaced by machines in the near future. So what if they’re the smartest ones in the room? If decision-makers can’t use data, does the information really exist?

Data Geeks
Data geeks may be the smartest people in the room, but maybe not if decision-makers don’t know what to do with their information.

Data do not exist just for data geeks and nerds. All of these data activities are inevitably funded by people who want to harness business value out of data. Whether it is about increasing revenue or reducing cost, in the end, the data game is about creating tangible value in forms of dollars, pounds, Euros or Yuans.

It really has nothing to do with the coolness of the toolsets or latest technologies, but it is all about the business — plain and simple. In other words, the data and analytics field is not some playground reserved for math or technology geeks, who sometimes think that belonging to exclusive clubs with secret codes and languages is the goal in itself. At the risk of sounding like an unapologetic capitalist, data don’t flow if money stops flowing. If you doubt me, watch where the budgets get cut first when going gets rough.

Data and analytics folks may feel secure, as they may know something in which non-technical people may not be well-versed in the age of Big Data. Maybe their bosses leave techies alone in a corner, as technical details and math jargon give them headaches. Their jobs may indeed be secure, for as long as the financial value coming out of the unit is net positive. Others may tolerate some techie talk, condescending attitudes, or mathematical dramas, for as long as data and analytics help them monetarily. Otherwise? Buh-bye geeks!

I am writing this piece to provide a serious attitude adjustment to some data players. If data and analytics are not for geeks, but for the good of businesses (and all of the decision-makers who may not be technical), what does useful information look like?

Allow me to share some ideas for all the beneficiaries of data, not a selected few who speak the machine language.

  • Data Must Be in Forms That Are Easy to Understand without mathematical or technical expertise. It should be as simple and easy to understand as a weather report. That means all of the data and statistical modeling to fill in the gaps must be done before the information reaches the users.
  • Data Must Be Small, not mounds of unfiltered and unstructured information. Useful data must look like answers to questions, not something that comes with a 500-page data dictionary. Data players should never brag about the size of the data or speed of processing, as users really don’t care about such details.
  • Data Must Be Accurate. Inaccurate information is worse than not having any at all. Users also must remember that not everything that comes out of computers is automatically accurate. Conversely, data players must be responsible to fix all of the previous mistakes that were made to datasets before they even reached them. Not fair, but that’s the job.
  • Data Must Be Consistent. It can be argued that consistency is even more important than sheer accuracy. Often, being consistently off may be more desirable than having large fluctuations, as even a dead clock is completely accurate twice a day. This is especially true for information that is inferred via statistical work.
  • Data Must Be Applicable Most of the Time, not just for limited cases. Too many data are locked in silos serving myopic purposes. Data become more powerful when they are consolidated properly, reaching broader audiences.
  • Data Must Be Accessible to users through devices of their choices. Even good information that fits the above criteria becomes useless if it does not reach decision-makers when needed. Data players’ jobs are not done until data are delivered to the right people in the right format and a timely manner.

Who are these data players who should be responsible for all of this, and where do they belong? They may have titles such as Chief Data Officer (who would be in charge of data governance); Data Strategist or Analytics Strategist: Data Scientist; Statistical Analyst or Program Developer. They may belong to IT, marketing, or a separate data or analytics department. No matter. They must be translators of information for the benefit of users, speaking languages of both business and technology fluently. They should never be just guard dogs of information. Ultimately, they should represent the interests of business first, not waving some fictitious IT or data rules.

So-called specialists, who habitually spit out reasons why certain information must be locked away somewhere and why they should not be available to users in a more user-friendly form, must snap out of their technical, analytical or mathematical comfort zone, pronto.

Techies who are that one-dimensional will be replaced by a machine in the near future.

The future belongs to people who can connect dots among different worlds and paradigms, not to some geeks with limited imaginations and skill sets that could become obsolete soon.

So, if self-preservation is an instinct that techies possess, they should figure out who is paying the bills, including their salaries and benefits, and make it absolutely easy for these end-users in all ways listed here. If not for altruistic reasons, for their own benefit in this results-oriented business world.

If information is not used by decision-makers, does the information really exist?

Best Practices Exist for a Reason, Part 2: Landing Pages

In my last post, I gave some specific and proven best practices for the creation of successful emails. In this post, I’ll talk about Landing Pages—because now that you’ve been able to lure your target into opening your email and clicking on the embedded link(s), you want to continue to drive that prospect to your desired outcome.

In my last post, I gave some specific and proven best practices for the creation of successful emails. In this post, I’ll talk about Landing Pages—because now that you’ve been able to lure your target into opening your email and clicking on the embedded link(s), you want to continue to drive that prospect to your desired outcome.

Whether your email offer is more information, a video, an e-book, a survey or a whitepaper, don’t send your prospect down a black hole by linking them to your website. Instead, create a specific digital destination (a landing page) for your campaign so you can not only quantify site visitors and their actions on the site, but it also reassures prospects that they’ve arrived at the right destination.

Based on lots of testing with our own clients and best practices from sites like Marketing Experiments, Marketing Sherpa, KISSmetrics, HubSpot and more, here’s what I’ve learned:

  • Your LP Headline Should Match Your Email Headline: While this may not seem like rocket science, prospects can get easily confused. You have less than a second to help them take the next step, so why create confusion with a brand new headline that is seemingly unrelated to the email they opened, read and clicked?
  • Place the CTA ABOVE the Fold: Especially now that we’ve entered the world of responsive design, it’s critical that your call-to-action is near the top of your page so that those viewing on even the smallest screens can clearly take the next step. And, make sure it’s the most obvious thing on the page because—after all—it’s the action you want them to take!
  • Make Buttons Highly Obvious and Actionable: Whether it’s using a color that contrasts to the rest of your page, uses language that makes it clear what you want/what they’ll get when they click, or are sized big enough to be obvious and legible, don’t hide your action buttons where they might get missed. Instead of buttons that say “Click here” try “Get me my..”
  • Have a Single Purpose With a Single-Focused Message: Think about why the prospect clicked on the email, and what their expectations are for when they arrive on your page. Don’t clutter it up with extraneous copy points or additional “stuff.” In fact, remove other types of navigation from the page as it can unnecessarily distract the visitor from taking the desired next step.
  • Be Authentic and Transparent With Real Testimonials: While you can—and should—edit quotes, make sure they’re attributable to someone even if it’s “Carolyn G., Business owner” or “C. Goodman, California.” Make sure they’re pithy and don’t ramble. These days, “social proof” (using quotes from Facebook posts or Tweets), adds social credibility. Plus people are influenced based on reviews by others.
  • Use Bullet Points for Copy: People skim, and won’t spend any time reading long paragraphs of text. Make sure your copy is crisp—short, sharp and to the point.
  • Include a Phone Number: This helps overcome buyer insecurity that they may be dealing with a company based overseas. Plus, they may have questions before completing an order, so it’s best to provide an easy-to-find phone number to help.
  • Keep Your Forms Simple: If you don’t need to collect certain data, then don’t ask/collect it. As a rule-of-thumb, shorter forms tend to work better. Personally, I’m always annoyed that certain forms ask me for personal information that is seemingly irrelevant to my purchase. As a result, I’m often untruthful in the information I provide in that field because I consider it none of their business.
  • Radio Buttons or Drop Down Menus? The right answer is to test it yourself because different tests for different customers yield different results. Marketing Experiments provides some great case studies on this topic. In one experiment, radio buttons generated a 15% lift over a drop down menu.

In summary, if all of these marketers have already done all the testing for you, why wouldn’t you at least consider these insights and apply them to your own landing page efforts? Tell me. I’m all ears.

Direct Mail: Data Makes All the Difference

The draw of the latest marketing trends pulls at us all. Many companies have integrated their direct mail with technologies like QR Codes, NFC and augmented reality, but many are missing the point with direct mail. The power of direct mail is the ability to reach the right person with the right offer to drive their response. Yes, technology can make the responses quicker and easier, but if you are not taking into consideration the person you are sending too, you may be throwing money away.

The draw of the latest marketing trends pulls at us all. Many companies have integrated their direct mail with technologies like QR Codes, NFC and augmented reality, but many are missing the point with direct mail. The power of direct mail is the ability to reach the right person with the right offer to drive their response. Yes, technology can make the responses quicker and easier, but if you are not taking into consideration the person you are sending too, you may be throwing money away.

The most powerful tool you have today is your data. You need to be able to harness this power to create great direct mail campaigns. Here are some things to consider:

  1. Create a data plan. What are your goals? What data have you already captured? What data do you want to capture? Now that you know what you want, how are you going to get it?
  2. Outline how you are going to use that data. Just having the data is not enough. You need to plan out ways to capitalize on it. Being able to group like people together for messaging will help you have less complicated campaigns. Make sure to not sacrifice your ROI by trying to make the campaign too simple. Some complexity is a good thing.
  3. The most common form of information that is extremely helpful in direct mail is purchase history. When you know what someone has already purchased you are able to tempt them with other items that they may be interested in, such as accessories or upgrades. This can also work in the nonprofit sector by tracking donation amounts. You can entice donors to donate more, by providing stepped donation amounts based on the last donation made.
  4. When you don’t have a lot of data already compiled there are many resources that can help you to enhance your data. There are geo, psycho, and demographics to name a few. Using this information can help you to build personas for better message targeting. Augmenting your data can provide powerful insights such as financial, shopping, technology and so much more. A couple of examples are Nielson with the Prizm tool and Accudata with the SnapShot tool. Working with a data company can help you expand your customer and prospect knowledge which can equate to better targeted marketing.
  5. Keeping old data is the biggest mistake. Outdated data is a real problem. These days the key to good data is not only capturing as much information about each person as you can, but also double checking it. Keep your data clean with all available tools. Some of these tools include NCOA (checking for new addresses when people move), deceased file processing (removing people when they die), surveys (keep your info current by asking them directly) and so on. You should look at your data as a constant work in progress and be cleaning and adding to it all the time.
  6. Do not forget about security. It is extremely important to secure your data. Too many times we hear reports of data breaches. Work with your IT department to make sure you can count on your data security. Many companies have not spent enough time on data security and have had to pay a very high price. Your customers trust you. Make sure you are trustworthy now before it is too late.
  7. If your data is small, don’t worry about it. Plan ways to grow your data base and continue to improve it. The more you are able to capture with each campaign the better your direct mail is going to get. Everyone started off small at one point. Just remember the tools you have available to help you and keep your data up to date. Old data will cost you money.

Direct mail can be an excellent driver for your marketing, not just for purchases, but for online engagement as well. When you focus on your data and really target your audience the impact of direct mail can be enormous. Tracking your campaigns is extremely important so that you know what is making you the most money and what needs to be worked on. Your direct mail should be constantly changing and updated based on your responses and data files. Have fun creating direct mail campaigns and learning more about your customers and prospects.

Marketing and IT; Cats and Dogs

Cats and dogs do not get along unless they grew up together since birth. That is because cats and dogs have rather fundamental communication problems with each other. A dog would wag his tail in an upward position when he wants to play. To a cat though, upward-tail is a sure sign of hostility, as in “What’s up, dawg?!” In fact, if you observe an angry or nervous cat, you will see that everything is up; tail, hair, toes, even her spine. So imagine the dog’s confusion in this situation, where he just sent a friendly signal that he wants to play with the cat, and what he gets back are loud hisses and scary evil eyes—but along with an upward tail that “looks” like a peace sign to him. Yeah, I admit that I am a bona-fide dog person, so I looked at this from his perspective, first. But I sympathize with the cat, too. As from her point of view, the dog started to mess with her, disrupting an afternoon slumber in her favorite sunny spot by wagging his stupid tail. Encounters like this cannot end well. Thank goodness that us Homo sapiens lost our tails during our evolutionary journey, as that would have been one more thing that clueless guys would have to decode regarding the mood of our female companions. Imagine a conversation like “How could you not see that I didn’t mean it? My tail was pointing the ground when I said that!” Then a guy would say, “Oh jeez, because I was looking at your lips moving up and down when you were saying something?”


Cats and dogs do not get along unless they grew up together since birth. That is because cats and dogs have rather fundamental communication problems with each other. A dog would wag his tail in an upward position when he wants to play. To a cat though, upward-tail is a sure sign of hostility, as in “What’s up, dawg?!” In fact, if you observe an angry or nervous cat, you will see that everything is up; tail, hair, toes, even her spine. So imagine the dog’s confusion in this situation, where he just sent a friendly signal that he wants to play with the cat, and what he gets back are loud hisses and scary evil eyes—but along with an upward tail that “looks” like a peace sign to him. Yeah, I admit that I am a bona-fide dog person, so I looked at this from his perspective first. But I sympathize with the cat, too. As from her point of view, the dog started to mess with her, disrupting an afternoon slumber in her favorite sunny spot by wagging his stupid tail. Encounters like this cannot end well. Thank goodness that us Homo sapiens lost our tails during our evolutionary journey, as that would have been one more thing that clueless guys would have to decode regarding the mood of our female companions. Imagine a conversation like “How could you not see that I didn’t mean it? My tail was pointing the ground when I said that!” Then a guy would say, “Oh jeez, because I was looking at your lips moving up and down when you were saying something?”

Of course I am generalizing for a comedic effect here, but I see communication breakdowns like this all the time in business environments, especially between the marketing and IT teams. You think men are from Mars and women are from Venus? I think IT folks are from Vulcan and marketing people are from Betazed (if you didn’t get this, find a Trekkie around you and ask).

Now that we are living in the age of Big Data where marketing messages must be custom-tailored based on data, we really need to find a way to narrow the gap between the marketing and the IT world. I wouldn’t dare to say which side is more like a dog or a cat, as I will surely offend someone. But I think even non-Trekkies would agree that it could be terribly frustrating to talk to a Vulcan who thinks that every sentence must be logically impeccable, or a Betazed who thinks that someone’s emotional state is the way it is just because she read it that way. How do they meet in the middle? They need a translator—generally a “human” captain of a starship—between the two worlds, and that translator had better speak both languages fluently and understand both cultures without any preconceived notions.

Similarly, we need translators between the IT world and the marketing world, too. Call such translators “data scientists” if you want (refer to “How to Be a Good Data Scientist”). Or, at times a data strategist or a consultant like myself plays that role. Call us “bats” caught in between the beasts and the birds in an Aesop’s tale, as we need to be marginal people who don’t really belong to one specific world 100 percent. At times, it is a lonely place as we are understood by none, and often we are blamed for representing “the other side.” It is hard enough to be an expert in data and analytics, and we now have to master the artistry of diplomacy. But that is the reality, and I have seen plenty of evidence as to why people whose main job it is to harness meanings out of data must act as translators, as well.

IT is a very special function in modern organizations, regardless of their business models. Systems must run smoothly without errors, and all employees and outside collaborators must constantly be in connection through all imaginable devices and operating systems. Data must be securely stored and backed up regularly, and permissions to access them must be granted based on complex rules, based on job levels and functions. Then there are constant requests to install and maintain new and strange software and technologies, which should be patched and updated diligently. And God forbid if anything fails to work even for a few seconds on a weekend, all hell will break lose. Simply, the end-users—many of them in positions of dealing with customers and clients directly—do not care about IT when things run smoothly, as they take them all for granted. But when they don’t, you know the consequences. Thankless job? You bet. It is like a utility company never getting praises when the lights are up, but everyone yelling and screaming if the service is disrupted, even for a natural cause.

On the other side of the world, there are marketers, salespeople and account executives who deal with customers, clients and their bosses, who would treat IT like their servants, not partners, when things do not “seem” to work properly or when “their” sales projections are not met. The craziest part is that most customers, clients and bosses state their goals and complaints in the most ambiguous terms, as in “This ad doesn’t look slick enough,” “This copy doesn’t talk to me,” “This app doesn’t stick” or “We need to find the right audience.” What the IT folks often do not grasp is that (1) it really stinks when you get yelled at by customers and clients for any reason, and (2) not all business goals are easily translatable to logical statements. And this is when all data elements and systems are functioning within normal parameters.

Without a proper translator, marketers often self-prescribe solutions that call for data work and analytics. Often, they think that all the problems will go away if they have unlimited access to every piece of data ever collected. So they ask for exactly that. IT will respond that such request will put a terrible burden on the system, which has to support not just marketing but also other operations. Eventually they may meet in the middle and the marketer will have access to more data than ever possible in the past. Then the marketers realize that their business issues do not go away just because they have more data in their hands. In fact, their job seems to have gotten even more complicated. They think that it is because data elements are too difficult to understand and they start blaming the data dictionary or lack thereof. They start using words like Data Governance and Quality Control, which may sound almost offensive to diligent IT personnel. IT will respond that they showed every useful bit of data they are allowed to share without breaking the security protocol, and the data dictionaries are all up to date. Marketers say the data dictionaries are hard to understand, and they are filled with too many similar variables and seemingly conflicting information. IT now says they need yet another tool set to properly implement data governance protocols and deploy them. Heck, I have seen cases where some heads of IT went for complete re-platforming of their system, as if that would answer all the marketing questions. Now, does this sound familiar so far? Does it sound like your own experience, like when you are reading “Dilbert” comic strips? It is because you are not alone in all this.

Allow me to be a little more specific with an example. Marketers often talk about “High-Value Customers.” To people who deal with 1s and 0s, that means less than nothing. What does that even mean? Because “high-value customers” could be:

  • High-dollar spenders—But what if they do not purchase often?
  • Frequent shoppers—But what if they don’t spend much at all?
  • Recent customers—Oh, those coveted “hotline” names … but will they stay that way, even for another few months?
  • Tenured customers—But are they loyal to your business, now?
  • Customers with high loyalty points—Or are they just racking up points and they would do anything to accumulate points?
  • High activity—Such as point redemptions and other non-monetary activities, but what if all those activities do not generate profit?
  • Profitable customers—The nice ones who don’t need much hand-holding. And where do we get the “cost” side of the equation on a personal level?
  • Customers who purchases extra items—Such as cruisers who drink a lot on board or diners who order many special items, as suggested.
  • Etc., etc …

Now it gets more complex, as these definitions must be represented in numbers and figures, and depending on the industry, whether be they for retailers, airlines, hotels, cruise ships, credit cards, investments, utilities, non-profit or business services, variables that would be employed to define seemingly straightforward “high-value customers” would be vastly different. But let’s say that we pick an airline as an example. Let me ask you this; how frequent is frequent enough for anyone to be called a frequent flyer?

Let’s just assume that we are going through an exercise of defining a frequent flyer for an airline company, not for any other travel-related businesses or even travel agencies (that would deal with lots of non-flyers). Granted that we have access to all necessary data, we may consider using:

1. Number of Miles—But for how many years? If we go back too far, shouldn’t we have to examine further if the customer is still active with the airline in question? And what does “active” mean to you?

2. Dollars Spent—Again for how long? In what currency? Converted into U.S. dollars at what point in time?

3. Number of Full-Price Ticket Purchases—OK, do we get to see all the ticket codes that define full price? What about customers who purchased tickets through partners and agencies vs. direct buyers through the airline’s website? Do they share a common coding system?

4. Days Between Travel—What date shall we use? Booking date, payment date or travel date? What time zones should we use for consistency? If UTC/GMT is to be used, how will we know who is booking trips during business hours vs. evening hours in their own time zone?

After a considerable hours of debate, let’s say that we reached the conclusion that all involved parties could live with. Then we find out that the databases from the IT department are all on “event” levels (such as clicks, views, bookings, payments, boarding, redemption, etc.), and we would have to realign and summarize the data—in terms of miles, dollars and trips—on an individual customer level to create a definition of “frequent flyers.”

In other words, we would need to see the data from the customer-centric point of view, just to begin the discussion about frequent flyers, not to mention how to communicate with each customer in the future. Now, it that a job for IT or marketing? Who will put the bell on the cat’s neck? (Hint: Not the dog.) Well, it depends. But this definitely is not a traditional IT function, nor is it a standalone analytical project. It is something in between, requiring a translator.

Customer-Centric Database, Revisited
I have been emphasizing the importance of a customer-centric view throughout this series, and I also shared some details regarding databases designed for marketing functions (refer to: “Cheat Sheet: Is Your Database Marketing Ready?”). But allow me to reiterate this point.

In the age of abundant and ubiquitous data, omnichannel marketing communication—optimized based on customers’ past transaction history, product preferences, and demographic and behavioral personas—should be an effortless routine. The reality is far from it for many organizations, as it is very common that much of the vital information is locked in silos without being properly consolidated or governed by a standard set of business rules. It is not that creating such a marketing-oriented database (or data-mart) is solely the IT department’s responsibility, but having a dedicated information source for efficient personalization should be an organizational priority in modern days.

Most databases nowadays are optimized for data collection, storage and rapid retrieval, and such design in general does not provide a customer-centric view—which is essential for any type of personalized communication via all conceivable channels and devices of the present and future. Using brand-, division-, product-, channel- or device-centric datasets is often the biggest obstacle in the journey to an optimal customer experience, as those describe events and transactions, not individuals. Further, bits and pieces of information must be transformed into answers to questions through advanced analytics, including statistical models.

In short, all analytical efforts must be geared toward meeting business objectives, and databases must be optimized for analytics (refer to “Chicken or the Egg? Data or Analytics?”). Unfortunately, the situation is completely reversed in many organizations, where analytical maneuvering is limited due to inadequate source data, and decision-making processes are dictated by limitations of available analytics. Visible symptoms of such cases are, to list a few, elongated project cycle time, decreasing response rates, ineffective customer communication, saturation of data sources due to overexposure, and—as I was emphasizing in this article—communication breakdown among divisions and team members. I can even go as far as to say that the lack of a properly designed analytical environment is the No. 1 cause of miscommunications between IT and marketing.

Without a doubt, key pieces of data must reside in the centralized data depository—generally governed by IT—for effective marketing. But that is only the beginning and still is just a part of the data collection process. Collected data must be consolidated around the solid definition of a “customer,” and all product-, transaction-, event- and channel-level information should be transformed into descriptors of customers, via data standardization, categorization, transformation and summarization. Then the data may be further enhanced via third-party data acquisition and statistical modeling, using all available data. In other words, raw data must be refined through these steps to be useful in marketing and other customer interactions, online or offline (refer to “‘Big Data’ Is Like Mining Gold for a Watch—Gold Can’t Tell Time“). It does not matter how well the original transaction- or event-level data are stored in the main database without visible errors, or what kind of state-of-the-art communication tool sets a company is equipped with. Trying to use raw data for a near real-time personalization engine is like putting unrefined oil into a high-performance sports car.

This whole data refinement process may sound like a daunting task, but it is not nearly as painful as analytical efforts to derive meanings out of unstructured, unconsolidated and uncategorized data that are scattered all over the organization. A customer-centric marketing database (call it a data-mart if “database” sounds too much like it should solely belong to IT) created with standard business rules and uniform variables sets would, in turn, provide an “analytics-ready” environment, where statistical modeling and other advanced analytics efforts would gain tremendous momentum. In the end, the decision-making process would become much more efficient as analytics would provide answers to questions, not just bits and pieces of fragmented data, to the ultimate beneficiaries of data. And answers to questions do not require an enormous data dictionary, either; fast-acting marketing machines do not have time to look up dictionaries, anyway.

Data Roadmap—Phased Approach
For the effort to build a consolidated marketing data platform that is analytics-ready (hence, marketing-ready), I always recommend a phased approach, as (1) inevitable complexity of a data consolidation project will be contained and managed more efficiently in carefully defined phases, and (2) each phase will require different types of expertise, tool sets and technologies. Nevertheless, the overall project must be managed by an internal champion, along with a group of experts who possess long-term vision and tactical knowledge in both database and analytics technologies. That means this effort must reside above IT and marketing, and it should be seen as a strategic effort for an entire organization. If the company already hired a Chief Data Officer, I would say that this should be one of the top priorities for that position. If not, outsourcing would be a good option, as an impartial decision-maker, who would play a role of a referee, may have to come from the outside.

The following are the major steps:

  1. Formulate Questions: “All of the above” is not a good way to start a complex project. In order to come up with the most effective way to build a centralized data depository, we first need to understand what questions must be answered by it. Too many database projects call for cars that must fly, as well.
  2. Data Inventory: Every organization has more data than it expected, and not all goldmines are in plain sight. All the gatekeepers of existing databases should be interviewed, and any data that could be valuable for customer descriptions or behavioral predictions should be considered, starting with product, transaction, promotion and response data, stemming from all divisions and marketing channels.
  3. Data Hygiene and Standardization: All available data fields should be examined and cleaned up, where some data may be discarded or modified. Free form fields would deserve special attention, as categorization and tagging are one of the key steps to opening up new intelligence.
  4. Customer Definition: Any existing Customer ID systems (such as loyalty program ID, account number, etc.) will be examined. It may be further enhanced with available PII (personally identifiable information), as there could be inconsistencies among different systems, and customers often move their residency or use multiple email addresses, creating duplicate identities. A consistent and reliable Customer ID system becomes the backbone of a customer-centric database.
  5. Data Consolidation: Data from different silos and divisions will be merged together based on the master Customer ID. A customer-centric database begins to take shape here. The database update process should be thoroughly tested, as “incremental” updates are often found to be more difficult than the initial build. The job is simply not done until after a few successful iterations of updates.
  6. Data Transformation: Once a solid Customer ID system is in place, all transaction- and event-level data will be transformed to “descriptors” of individual customers, via summarization by categories and creation of analytical variables. For example, all product information will be aligned for each customer, and transaction data will be converted into personal-level monetary summaries and activities, in both static and time-series formats. Promotion and response history data will go through similar processes, yielding individual-level ROI metrics by channel and time period. This is the single-most critical step in all of this, requiring deep knowledge in business, data and analytics, as the stage is being set for all future analytics and reporting efforts. Due to variety and uniqueness of business goals in different industries, a one-size-fits-all approach will not work, either.
  7. Analytical Projects: Test projects will be selected and the entire process will be done on the new platform. Ad-hoc reporting and complex modeling projects will be conducted, and the results will be graded on timing, accuracy, consistency and user-friendliness. An iterative approach is required, as it is impossible to foresee all possible user requests and related complexities upfront. A database should be treated as a living, breathing organism, not something rigid and inflexible. Marketers will “break-in” the database as they use it more routinely.
  8. Applying the Knowledge: The outcomes of analytical projects will be applied to the entire customer base, and live campaigns will be run based on them. Often, major breakdowns happen at the large-scale deployment stages; especially when dealing with millions of customers and complex mathematical formulae at the same time. A model-ready database will definitely minimize the risk (hence, the term “in-database scoring”), but the process will still require some fine-tuning. To proliferate gained knowledge throughout the organization, some model scores—which pack deep intelligence in small sizes—may be transferred back to the main databases managed by IT. Imagine model scores driving operational decisions—live, on the ground.
  9. Result Analysis: Good marketing intelligence engines must be equipped with feedback mechanisms, effectively closing the “loop” where each iteration of marketing efforts improves its effectiveness with accumulated knowledge on a customer level. It is very unfortunate that many marketers just move through the tracks set up by their predecessors, mainly because existing database environments are not even equipped to link necessary data elements on a customer level. Too many back-end analyses are just event-, offer- or channel-driven, not customer-centric. Can you easily tell which customer is over-, under- or adequately promoted, based on a personal-level promotion-and-response ratio? With a customer-centric view established, you can.

These are just high-level summaries of key steps, and each step should be managed as independent projects within a large-scale initiative with common goals. Some steps may run concurrently to reduce the overall timeline, and tactical knowledge in all required technologies and tool sets is the key for the successful implementation of centralized marketing intelligence.

Who Will Do the Work?
Then, who will be in charge of all this and who will actually do the work? As I mentioned earlier, a job of this magnitude requires a champion, and a CDO may be a good fit. But each of these steps will require different skill sets, so some outsourcing may be inevitable (more on how to pick an outsourcing partner in future articles).

But the case that should not be is the IT team or the analytics team solely dictating the whole process. Creating a central depository of marketing intelligence is something that sits between IT and marketing, and the decisions must be made with business goals in mind, not just limitations and challenges that IT faces. If the CDO or the champion of this type of initiative starts representing IT issues before overall business goals, then the project is doomed from the beginning. Again, it is not about touching the core database of the company, but realigning existing data assets to create new intelligence. Raw data (no matter how clean they are at the collection stage) are like unrefined raw materials to the users. What the decision-makers need are simple answers to their questions, not hundreds of data pieces.

From the user’s point of view, data should be:

  • Easy to understand and use (intuitive to non-mathematicians)
  • Bite-size (i.e., small answers, not mounds of raw data)
  • Useful and effective (consistently accurate)
  • Broad (answers should be available most of time, not just “sometimes”)
  • Readily available (data should be easily accessible via users’ favorite devices/channels)

And getting to this point is the job of a translator who sits in between marketing and IT. Call them data scientists or data strategists, if you like. But they do not belong to just marketing or IT, even though they have to understand both sides really well. Do not be rigid, insisting that all pilots must belong to the Air Force; some pilots do belong to the Navy.

Lastly, let me add this at the risk of sounding like I am siding with technologists. Marketers, please don’t be bad patients. Don’t be that bad patient who shows up at a doctor’s office with a specific prescription, as in “Don’t ask me why, but just give me these pills, now.” I’ve even met an executive who wanted a neural-net model for his business without telling me why. I just said to myself, “Hmm, he must have been to one of those analytics conferences recently.” Then after listening to his “business” issues, I prescribed an entirely different solution package.

So, instead of blurting out requests for pieces of data variables or queries using cool-sounding, semi-technical terms, state the business issues and challenges that you are facing as clearly as possible. IT and analytics specialists will prescribe the right solution for you if they understand the ultimate goals better. Too often, requesters determine the solutions they want without any understanding of underlying technical issues. Don’t forget that the end-users of any technology are only exposed to symptoms, not the causes.

And if Mr. Spock doesn’t seem to understand your issues and keeps saying that your statements are illogical, then call in a translator, even if you have to hire him for just one day. I know this all too well, because after all, this one phrase summarizes my entire career: “A bridge person between the marketing world and the IT world.” Although it ain’t easy to live a life as a marginal person.

Top 10 Local SEO Best Practices for Small Businesses

Have you ever wondered how you could get your business to show up on the first page of Google, along with a map showing your prospective customers exactly where your business is located? The answer is to use local search engine optimization (SEO).

Have you ever wondered how you could get your business to show up on the first page of Google, along with a map showing your prospective customers exactly where your business is located? The answer is to use local search engine optimization (SEO).

With local SEO, you can get your business in front of prospects at the precise moment when they are literally searching for you. It doesn’t get much better than this. However, due to all the Google algorithm updates, local SEO is not quite as easy as it used to be. Whether you’re an SEO veteran or you’re just getting started, use the top 10 best practices in this article to give your business the best shot at ranking on the first page of Google’s local results.

  1. Claim and Complete a Google+ Local Page
    Next time you search in Google to find a business, pay close attention to the big map in the upper right corner of the results page. An entire section of the results list is devoted to the businesses that appear on that map. But here’s the catch: Google doesn’t pull the business information from websites. They are pulled from Google+ Local business pages!

    Setting up your Google+ Local page is easy and free, but you need to pay attention to what you are doing. The number one rule is to create only a single page per location. Creating duplicate Local pages is forbidden by Google’s Terms of Service, and can hurt your rankings.

    In addition, your page must use relevant categories. Think of categories like sections of the Yellow Pages, so the more categories you choose the better—as long as you don’t choose irrelevant categories, which is also against Google’s Terms of Service. Choosing categories can be difficult, so use this list for help.

  2. Add Your Service and Geographic Keywords to Page Titles
    This is especially critical for your homepage, but is a Best Practice for all your web pages. Title tags are like chapter names in a book—they tell Google what the page is all about. Your homepage title tag is like the book’s cover. It needs to be enticing but accurate, and explain to Google what the website holds. For local SEO, adding both the service and geographic keywords to your title tags lets Google know that your site is relevant to people searching for your particular service in your local area.
  3. Make Your NAP Consistent—and Omnipresent
    NAP is an acronym for the most important information when it comes to optimizing for local SEO. NAP stands for Name, Address, and Phone number.

    Google strives to provide the most accurate, credible information to its users. Therefore, before displaying your information, the algorithm cross-checks your NAP across not only your Google+ local page, but the entire Internet! To ensure your NAP is consistent, I recommend searching for your business name in the Moz Local search tool.

  4. Add Pages for Different Services and Locations
    If you provide multiple services, and/or practice in different locations, make sure you create a separate web page for each. Although it may seem redundant, this step is crucial to local SEO. You simply cannot optimize the same page for Houston, Texas, and Deer Park, Texas, and expect it to perform well for either location. Likewise, a page with keywords for both oil changes and collision repair is not truly optimized for either. Make sure that each page is entirely unique, and target each to a core keyword phrase.
  5. Install Schema
    Schema markup is a type of HTML code that tells Google more about your website. When a human reads a particular page, he or she innately understands certain things about that page, such as exactly what is being discussed. Search engines, however, have a much more limited understanding. Schema bridges that gap by adding machine-understandable explanations. Many webmasters are not yet using this valuable tool, so this is a great opportunity to get a jump on your competition.
  6. Get Customer Reviews on Google+ Local
    Unfortunately, getting customer reviews is one of the most challenging tasks that small business owners face, and there is no magical shortcut. The two keys to success are first to ask, and second to make it as easy as possible for your customers leave an online review. Even when you make things easy for your customers, this will be a slow process, but over time, it will improve your local rankings and create a big barrier for your competitors.
  7. Create a Mobile-Optimized Website
    Increasingly, consumers are turning to their phones and other mobile devices when searching for products and services. This is even more true for those who are looking for local companies, which means you absolutely must have a mobile-friendly website to compete in the local search results.

    If you’re like most businesses, then you have been dragging your feet and putting off investing in a mobile website. Well, the time has finally come because on April 21, 2015 Google will launch an algorithm update that will drastically change the mobile search results. In short, if your site is not mobile-optimized at that time, your rankings will suffer dramatically in any Google search launched on a mobile device-which is approximately 50% of all searches today!

  8. Provide High-Quality Website Content
    The importance of high quality content is nothing new for SEO. However, until recently this wasn’t a big factor in the local search rankings. Now, failing to create well-written, unique, informative web pages with at least 500 words of content each could mean your business will not show up when prospective customers are searching for you.
  9. Build High-Quality Links to Your Website
    Again, this is nothing new for SEO, but it’s a fairly new factor for local SEO. Your domain authority, or online reputation, is now a critical factor in your local Google rankings. One of the biggest factors in your domain authority is the quantity and quality of relevant links from other websites.

    As you gain more and more high-quality links, then your domain authority will increase, and in turn, your local rankings will also improve.

  10. Be Active on Social Media
    Exactly how much of an impact social media presence has on local SEO is currently the subject of hot debate. What is not open for debate, however, is the fact that social media is a great way to generate buzz and get exposure for your business. This exposure can lead to more referral traffic, more high-quality links, more reviews, and more online comments about your business, which are all signals that will improve your local Google rankings.

Want more Local SEO Tips? Click here to get my Ultimate Local SEO Checklist

Don’t Do It Just Because You Can

Don’t do it just because you can. No kidding. … Any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

Don’t do it just because you can. No kidding. By the way, I could have gone with Ben Parker’s “With great power comes great responsibility” line, but I didn’t, as it has become an over-quoted cliché. Plus, I’m not much of a fan of “Spiderman.” Actually, I’m kidding this time. (Not the “Spiderman” part, as I’m more of a fan of “Thor.”) But the real reason is any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

All jokes aside, I received a call from my mother a few years ago asking me if this “urgent” letter that says her car warranty will expire if she does not act “right now” (along with a few exclamation marks) is something to which she must respond immediately. Many of us by now are impervious to such fake urgencies or outrageous claims (like “You’ve just won $10,000,000!!!”). But I then realized that there still are plenty of folks who would spend their hard-earned dollars based on such misleading messages. What really made me mad, other than the fact that my own mother was involved in that case, was that someone must have actually targeted her based on her age, ethnicity, housing value and, of course, the make and model of her automobile. I’ve been doing this job for too long to be unaware of potential data variables and techniques that must have played a part so that my mother to receive a series of such letters. Basically, some jerk must have created a segment that could be named as “old and gullible.” Without a doubt, this is a classic example of what should not be done just because one can.

One might dismiss it as an isolated case of a questionable practice done by questionable individuals with questionable moral integrity, but can we honestly say that? I, who knows the ins and outs of direct marketing practices quite well, fell into traps more than a few times, where supposedly a one-time order mysteriously turns into a continuity program without my consent, followed by an extremely cumbersome canceling process. Further, when I receive calls or emails from shady merchants with dubious offers, I can very well assume my information changed hands in very suspicious ways, if not through outright illegal routes.

Even without the criminal elements, as data become more ubiquitous and targeting techniques become more precise, an accumulation of seemingly inoffensive actions by innocuous data geeks can cause a big ripple in the offline (i.e., “real”) world. I am sure many of my fellow marketers remember the news about this reputable retail chain a few years ago; that they accurately predicted pregnancy in households based on their product purchase patterns and sent customized marketing messages featuring pregnancy-related products accordingly. Subsequently it became a big controversy, as such a targeted message was the way one particular head of household found out his teenage daughter was indeed pregnant. An unintended consequence? You bet.

I actually saw the presentation of the instigating statisticians in a predictive analytics conference before the whole incident hit the wire. At the time, the presenters were unaware of the consequences of their actions, so they proudly shared employed methodologies with the audience. But when I heard about what they were actually trying to predict, I immediately turned my head to look at the lead statistician in my then-analytical team sitting next to me, and saw that she had a concerned look that I must have had on my face, as well. And our concern was definitely not about the techniques, as we knew how to do the same when provided with similar sets of data. It was about the human consequences that such a prediction could bring, not just to the eventual targets, but also to the predictors and their fellow analysts in the industry who would all be lumped together as evil scientists by the outsiders. In predictive analytics, there is a price for being wrong; and at times, there is a price to pay for being right, too. Like I said, we shouldn’t do things just because we can.

Analysts do not have superpowers individually, but when technology and ample amounts of data are conjoined, the results can be quite influential and powerful, much like the way bombs can be built with common materials available at any hardware store. Ironically, I have been evangelizing that the data and technology should be wielded together to make big and dumb data smaller and smarter all this time. But providing answers to decision-makers in ready-to-be used formats, hence “humanizing” the data, may have its downside, too. Simply, “easy to use” can easily be “easy to abuse.” After all, humans are fallible creatures with ample amounts of greed and ambition. Even without any obvious bad intentions, it is sometimes very difficult to contemplate all angles, especially about those sensitive and squeamish humans.

I talked about the social consequences of the data business last month (refer to “How to Be a Good Data Scientist“), and that is why I emphasized that anyone who is about to get into this data field must possess deep understandings of both technology and human nature. That little sensor in your stomach that tells you “Oh, I have a bad feeling about this” may not come to everyone naturally, but we all need to be equipped with those safeguards like angels on our shoulders.

Hindsight is always 20/20, but apparently, those smart analysts who did that pregnancy prediction only thought about the techniques and the bottom line, but did not consider all the human factors. And they should have. Or, if not them, their manager should have. Or their partners in the marketing department should have. Or their public relations people should have. Heck, “someone” in their organization should have, alright? Just like we do not casually approach a woman on the street who “seems” pregnant and say “You must be pregnant.” Only socially inept people would do that.

People consider certain matters extremely private, in case some data geeks didn’t realize that. If I might add, the same goes for ailments such as erectile dysfunction or constipation, or any other personal business related to body parts that are considered private. Unless you are a doctor in an examining room, don’t say things like “You look old, so you must have hard time having sex, right?” It is already bad enough that we can’t even watch golf tournaments on TV without those commercials that assume that golf fans need help in that department. (By the way, having “two” bathtubs “outside” the house at dusk don’t make any sense either, when the effect of the drug can last for hours for heaven’s sake. Maybe the man lost interest because the tubs were too damn heavy?)

While it may vary from culture to culture, we all have some understanding of social boundaries in casual settings. When you are talking to a complete stranger on a plane ride, for example, you know exactly how much information that you would feel comfortable sharing with that person. And when someone crosses the line, we call that person inappropriate, or “creepy.” Unfortunately, that creepy line is set differently for each person who we encounter (I am sure people like George Clooney or Scarlett Johansson have a really high threshold for what might be considered creepy), but I think we can all agree that such a shady area can be loosely defined at the least. Therefore, when we deal with large amounts of data affecting a great many people, imagine a rather large common area of such creepiness/shadiness, and do not ever cross it. In other words, when in doubt, don’t go for it.

Now, as a lifelong database marketer, I am not advocating some over-the-top privacy zealots either, as most of them do not understand the nature of data work and can’t tell the difference between informed (and mutually beneficial) messages and Big Brother-like nosiness. This targeting business is never about looking up an individual’s record one at a time, but more about finding correlations between users and products and doing some good match-making in mass numbers. In other words, we don’t care what questionable sites anyone visits, and honest data players would not steal or abuse information with bad intent. I heard about waiters who steal credit card numbers from their customers with some swiping devices, but would you condemn the entire restaurant industry for that? Yes, there are thieves in any part of the society, but not all data players are hackers, just like not all waiters are thieves. Statistically speaking, much like flying being the safest from of travel, I can even argue that handing over your physical credit card to a stranger is even more dangerous than entering the credit card number on a website. It looks much worse when things go wrong, as incidents like that affect a great many all at once, just like when a plane crashes.

Years back, I used to frequent a Japanese Restaurant near my office. The owner, who doubled as the head sushi chef, was not a nosy type. So he waited for more than a year to ask me what I did for living. He had never heard anything about database marketing, direct marketing or CRM (no “Big Data” on the horizon at that time). So I had to find a simple way to explain what I do. As a sushi chef with some local reputation, I presumed that he would know personal preferences of many frequently visiting customers (or “high-value customers,” as marketers call them). He may know exactly who likes what kind of fish and types of cuts, who doesn’t like raw shellfish, who is allergic to what, who has less of a tolerance for wasabi or who would indulge in exotic fish roes. When I asked this question, his answer was a simple “yes.” Any diligent sushi chef would care for his or her customers that much. And I said, “Now imagine that you can provide such customized services to millions of people, with the help of computers and collected data.” He immediately understood the benefits of using data and analytics, and murmured “Ah so …”

Now let’s turn the table for a second here. From the customer’s point of view, yes, it is very convenient for me that my favorite sushi chef knows exactly how I like my sushi. Same goes for the local coffee barista who knows how you take your coffee every morning. Such knowledge is clearly mutually beneficial. But what if those business owners or service providers start asking about my personal finances or about my grown daughter in a “creepy” way? I wouldn’t care if they carried the best yellowtail in town or served the best cup of coffee in the world. I would cease all my interaction with them immediately. Sorry, they’ve just crossed that creepy line.

Years ago, I had more than a few chances to sit closely with Lester Wunderman, widely known as “The Father of Direct Marketing,” as the venture called I-Behavior in which I participated as one of the founders actually originated from an idea on a napkin from Lester and his friends. Having previously worked in an agency that still bears his name, and having only seen him behind a podium until I was introduced to him on one cool autumn afternoon in 1999, meeting him at a small round table and exchanging ideas with the master was like an unknown guitar enthusiast having a jam session with Eric Clapton. What was most amazing was that, at the beginning of the boom, he was completely unfazed about all those new ideas that were flying around at that time, and he was precisely pointing out why most of them would not succeed at all. I do not need to quote the early 21st century history to point out that his prediction was indeed accurate. When everyone was chasing the latest bit of technology for quick bucks, he was at least a decade ahead of all of those young bucks, already thinking about the human side of the equation. Now, I would not reveal his age out of respect, but let’s just say that almost all of the people in his age group would describe occupations of their offspring as “Oh, she just works on a computer all the time …” I can only wish that I will remain that sharp when I am his age.

One day, Wunderman very casually shared a draft of the “Consumer Bill of Rights for Online Engagement” with a small group of people who happened to be in his office. I was one of the lucky souls who heard about his idea firsthand, and I remember feeling that he was spot-on with every point, as usual. I read it again recently just as this Big Data hype is reaching its peak, just like the boom was moving with a force that could change the world back then. In many ways, such tidal waves do end up changing the world. But lest we forget, such shifts inevitably affect living, breathing human beings along the way. And for any movement guided by technology to sustain its velocity, people who are at the helm of the enabling technology must stay sensitive toward the needs of the rest of the human collective. In short, there is not much to gain by annoying and frustrating the masses.

Allow me to share Lester Wunderman’s “Consumer Bill of Rights for Online Engagement” verbatim, as it appeared in the second edition of his book “Being Direct”:

  1. Tell me clearly who you are and why you are contacting me.
  2. Tell me clearly what you are—or are not—going to do with the information I give.
  3. Don’t pretend that you know me personally. You don’t know me; you know some things about me.
  4. Don’t assume that we have a relationship.
  5. Don’t assume that I want to have a relationship with you.
  6. Make it easy for me to say “yes” and “no.”
  7. When I say “no,” accept that I mean not this, not now.
  8. Help me budget not only my money, but also my TIME.
  9. My time is valuable, don’t waste it.
  10. Make my shopping experience easier.
  11. Don’t communicate with me just because you can.
  12. If you do all of that, maybe we will then have the basis for a relationship!

So, after more than 15 years of the so-called digital revolution, how many of these are we violating almost routinely? Based on the look of my inboxes and sites that I visit, quite a lot and all the time. As I mentioned in my earlier article “The Future of Online is Offline,” I really get offended when even seasoned marketers use terms like “online person.” I do not become an online person simply because I happen to stumble onto some stupid website and forget to uncheck some pre-checked boxes. I am not some casual object at which some email division of a company can shoot to meet their top-down sales projections.

Oh, and good luck with that kind of mindless mass emailing; your base will soon be saturated and you will learn that irrelevant messages are bad for the senders, too. Proof? How is it that the conversion rate of a typical campaign did not increase dramatically during the past 40 years or so? Forget about open or click-through rate, but pay attention to the good-old conversion rate. You know, the one that measures actual sales. Don’t we have superior databases and technologies now? Why is anyone still bragging about mailing “more” in this century? Have you heard about “targeted” or “personalized” messages? Aren’t there lots and lots of toolsets for that?

As the technology advances, it becomes that much easier and faster to offend people. If the majority of data handlers continue to abuse their power, stemming from the data in their custody, the communication channels will soon run dry. Or worse, if abusive practices continue, the whole channel could be shut down by some legislation, as we have witnessed in the downfall of the outbound telemarketing channel. Unfortunately, a few bad apples will make things a lot worse a lot faster, but I see that even reputable companies do things just because they can. All the time, repeatedly.

Furthermore, in this day and age of abundant data, not offending someone or not violating rules aren’t good enough. In fact, to paraphrase comedian Chris Rock, only losers brag about doing things that they are supposed to do in the first place. The direct marketing industry has long been bragging about the self-governing nature of its tightly knit (and often incestuous) network, but as tools get cheaper and sharper by the day, we all need to be even more careful wielding this data weaponry. Because someday soon, we as consumers will be seeing messages everywhere around us, maybe through our retina directly, not just in our inboxes. Personal touch? Yes, in the creepiest way, if done wrong.

Visionaries like Lester Wunderman were concerned about the abusive nature of online communication from the very beginning. We should all read his words again, and think twice about social and human consequences of our actions. Google from its inception encapsulated a similar idea by simply stating its organizational objective as “Don’t be evil.” That does not mean that it will stop pursuing profit or cease to collect data. I think it means that Google will always try to be mindful about the influences of its actions on real people, who may not be in positions to control the data, but instead are on the side of being the subject of data collection.

I am not saying all of this out of some romantic altruism; rather, I am emphasizing the human side of the data business to preserve the forward-momentum of the Big Data movement, while I do not even care for its name. Because I still believe, even from a consumer’s point of view, that a great amount of efficiency could be achieved by using data and technology properly. No one can deny that modern life in general is much more convenient thanks to them. We do not get lost on streets often, we can translate foreign languages on the fly, we can talk to people on the other side of the globe while looking at their faces. We are much better informed about products and services that we care about, we can look up and order anything we want while walking on the street. And heck, we get suggestions before we even think about what we need.

But we can think of many negative effects of data, as well. It goes without saying that the data handlers must protect the data from falling into the wrong hands, which may have criminal intentions. Absolutely. That is like banks having to protect their vaults. Going a few steps further, if marketers want to retain the privilege of having ample amounts of consumer information and use such knowledge for their benefit, do not ever cross that creepy line. If the Consumer’s Bill of Rights is too much for you to retain, just remember this one line: “Don’t be creepy.”

The 1 Simple Way to Sell via Your Webinar

Want to sell with your webinar? Actually go for the close at the end or generate an appointment for your reps to follow-up immediately? Stop wasting the audience’s time with blather about your speaker.

Want to sell with your webinar? Actually go for the close at the end or generate an appointment for your reps to follow-up immediately? Stop wasting the audience’s time with blather about your speaker.

Ok, it will take more I admit. The rest can be done by getting to the point fast and helping your buyer become attracted to the idea of talking more about the itch your speaker just scratched. Here’s a three-step process to getting that done.

You Have the Email but not a Lead
The word webinar itself has a negative connotation. At best it is something your prospects attend while they check email and put out any number of fires. You might argue, “Sure, Molander, but I have the prospects’ email.”

True. But you don’t have them on the way to becoming a lead. You blew it. How? By wasting every single moment from “go.”

It’s time for tough love about your Webinar and the lousy leads it’s sending to sales. Of course, I’ll also offer three simple steps to help produce Webinars that spark customers’ curiosity in what your solution can do for them.

No. 1: Avoid all Introductions Like the Plague
“I find the need to hear the presenters personal story for 10-20 minutes a huge turn off,” says sales coach, Iain Swanson of UK-based Kolzers. “In most cases I have literally switched off and missed the content of the call.”

Enough said. And let’s face it. You’ve probably done the same. Or perhaps you make it habit to join the webinar late in an effort to avoid the irrelevant blather.

This time-wasting tradition needs to stop. Right now. How? NO introductions.

Your potential buyer isn’t attending the webinar to hear about the backgrounds or experiences of the presenter. Nor what the sponsor does, for whom or how well.

They’re there for one reason: To take from you. They want as much as they can get, for free, as possible. Why? They’re human.

Let them take. Let them gorge.

Just structure the way you release the information. Copywrite it. Yes, copywrite it. Scripted? Yes but only for the pros. If you come off as canned you can kiss the leads goodbye.

Start by canning your introduction. Shock your audience by immediately getting to the point. They’ve already qualified the speaker. They’re there, after all.

Brighten their day. Surprise them. Make them think, “WOW, he/she just skipped the boring introduction stuff!”

This is how to sell using Webinars. Trust me, it works.

No. 2: Promise Viewers Something They Don’t Already Know—Then Deliver It Fast, Clearly
Start your webinar by telling prospects, “You’re about to hear information that you probably don’t already know.” Then, follow the Golden Rule of communication. What if prospects already know most of what you’re about to tell them?

You’ve designed the webinar to fail. Just like a whitepaper that looks sharp but is worthless, your Webinar must contain useful information and new know-how, tips or knowledge. If it does not contain enough new information you will not hold the audience.

Build in useful, actionable and fresh information and present it according to the Golden Rule:

  • Tell them what you’re about to tell them (the main insight, short-cut, better way or remedy)
  • Tell them the “better way” (at a high level, yet specific)
  • Tell them what you just told them (come back and remind of the main point)

This approach serves the most essential goal: Getting customers clear on your message. Without clarity your webinar will fail.

Remember the last time you were clear—really clear—on something? Remember how you felt?

Remember the sense of confidence that came with your “ah-ha moment?” You might also recall a feeling of wanting to know more—wanting to have more clarity, more confidence. That’s what we’re after.

That’s your webinar’s job: get buyers crystal clear, confident in themselves and trusting you.

No. 3: Help Them to Want to Know More
When is the last time you attended a Webinar and learned something new? Think about a time when the presenter gave you everything they promised they would at the beginning of the presentation—and more. Did you want more from them? Were you ready to act on that impulse?

Give your best insights, tips or warnings away. Give away all of your best knowledge. All of it.

“But, Jeff, giving prospects my best advice for FREE will help them to do it without me!”

Doubtful. Be careful to not confuse customers qualifying you with what you perceive as their purchase intent.

The act of looking for answers does not always translate to customers’ wanting to do what you charge money for themselves. Even when it does “signal” a customer’s desire to do it themselves, what customers want can change.

You want to be there when it changes.

Most importantly you need to create a craving, deep inside your prospects. A desire to know more details about your big claim, better way, short-cut or system.

The only way to get prospects hungry for more of you is to attract them to the idea of talking to you. Attraction takes a reliable, effective system.

The idea is to structure (copywrite) the content you release in a way that makes asking more questions irresistible to your attendees. Yes, questions can be answered in Q&A. That’s fine. This builds trust and creates more intense curiosity in you—a hunger for more of what you can offer.

But only if you are careful about how you answer those questions.

To get started, present the answers or solutions clearly but in ways that provokes prospects’ curiosity. Answer questions always creates more questions about the details (relating to what you sell).

To create this hunger:

  • Make your words specific, filled with integrity, true and useful
  • Be action-oriented (make your answer clear and easily acted on)
  • But be incomplete (make a credible answer yet leave out most of the details)

Tee-Up Your Call to Action
The idea is to create hunger for a short-cut at the end of your webinar. In other words, the goal of this three-step process is to get prospects hungry for a faster, easier way to get all the details you just spent 40 minutes talking about.

This faster, easier way can be:

  • a lead generation offer
  • your product/service.

The idea is to present content that helps customers begin to desire your lead generation offer. Or at least be primed for the idea of taking action on it.

Making the pitch for viewers to buy at the end of your webinar? Help viewers see buying your product/service as a logical next step in the journey you just started with them.

Using this three-step process transforms what you sell from “something I need to think about buying some day” into “the obvious next step I should take right now.”

Your fee or price tag becomes a logical investment that “feels right, right now.”

Good luck!