Don’t Let Old Habits Dictate Your Marketing Thoughts

When marketers play with data, we often get confined within the limitations of the datasets that are available to us, or worse, tool sets through which we get to access data. Some bad habits live through an organization for multiple generations, as we all get trained in marketing thoughts, in the beginning of our careers, by others who have been doing similar jobs.

marketing thoughts
Credit: Pixabay by Mohamed Hassan

When marketers play with data, we often get confined within the limitations of the datasets that are available to us, or worse, tool sets through which we get to access data. Some bad habits live through an organization for multiple generations, as we all get trained in marketing thoughts, in the beginning of our careers, by others who have been doing similar jobs.

When a few iterations of such training go on through a series of onboarding processes, the original intents of data, reporting and analytics get diluted. And the organization ends up just using those marketing thoughts to go through motions of producing lots of reports that no one cares about or benefits from. I’ve heard some radical claims that the majority of decision-makers today won’t miss over half of automatically generated reports.

We shouldn’t really look at a single report or initiate data-related projects without setting a clear goal first. Often, the most important role of a consultant is to remind clients “why” they should do anything in the first place.

For example, why should we all watch clickthrough rates every day, often locked in a set frame of time parameters? As in, compared to the same time last year, the clickthrough rate went down by 0.8%! The horror! Why do marketers make a big fuss about it, when the clickthrough rate is just one of many indicators, not even the most effective one at that, of actual purchases? Because someone in the past set the KPI reports up that way?

In other words, sometimes marketers and analysts who help them needed to be reminded that the goal is to sell more things and retain customers, not live and die with open and clickthrough rates. I am not flatly dismissing those important metrics at all; I’m just pointing out that we need to have a goal-oriented mindset when dealing with data and analytics. Otherwise, we end up in a maze of metrics and activities that do not really help us achieve organizational goals.

What are those ultimate goals? Not that I want to be a smart ass who would say “From Earth” to an innocuous question “Where are you from?”, but let’s really go to that high level for a moment; we play with data (1) to increase the revenue, or (2) to decrease the cost. Since Profit=Revenue-Cost, well, we can even reduce this whole thing to just one goal: Increase the Profit.

Why am I pointing out the obvious? Because I’ve seen too many data players who just go through motions without questioning the original intent of the activity or key metrics, and blindly believe that all that hard work will somehow lead to success. Unfortunately, that is far from the truth.

If you run on an airplane midflight, would you get to the destination any sooner? Definitely not. In fact, the captain may even go back to the originating airport to drop such crazy person off, further elongating the length of the journey.

You may think this analogy is silly, but in the world of data and analytics, such detours happen all of the time. All because no one questioned how and why any activity set in motion in the distant past would continue to help achieve long and short-term organizational goals – especially when goals need to be constantly adjusted thanks to ever-changing business environments. Nothing in scientific activities, no marketing thoughts, should be carved in stone.

That is why the first question by a seasoned consultant should be what the organization’s long and short-term goals are. Okay, we can all easily agree that we are all in this data and analytics game to increase profit, but what are the specific goals, and what are the immediate pain points? Of course, like any good doctor, a consultant must remedy immediate pain points first. But what do we call those doctors who make the patient’s condition worse just to relieve immediate pain? We call them quacks.

Bringing back this discussion to the world of marketing, having the clear long and short-term goals for every data and analytical activity is a must. If you do that, you may never need an expensive consultant just to remind you that you are wasting resources digging wrong places. Clear business goals beget proper problem statements (not just list of all symptoms and wish lists), which beget appropriate measurement metrics, which in turn lead us to proper digging points in terms of data and methodology, which would minimize waste of time and energy to achieve predetermined goals. In short, we can avoid lots of mishaps and detours just by remembering the original intents of data and analytics endeavors.

Up Your Price Potential by 8X

It’s easy to assume that B2C is more emotional than B2B — as more consumer goods have hedonistic appeal, while B2B products have utilitarian appeal. But that’s not true.

B2B Influencer Marketing
Credit: Pixabay by Thomas Malyska

It’s easy to assume that B2C is more emotional than B2B — as more consumer goods have hedonistic appeal, while B2B products have utilitarian appeal. But that’s not true.

Research by Google and Motista shows that 10 to 40 percent of B2C customers feel emotionally connected to a brand while 50 percent and higher of B2B purchasers feel emotionally connected to the brands with which they do business. And when you create the right emotional reactions, you can increase your chances of getting a premium price by eight times. Strange, but true.

Think about it. When we buy that $30,000 luxury handbag, we are emotionally connected to how we feel having bought a luxury brand item that few people can afford. We feel superior, awesome and like we’ve arrived at a place in society where others have not. Yet, in time, that wears off, and you replace that “uber awesome” handbag with another one which often puts the first one on the back shelf and the back part of your mind.

Yet when you buy that $30,000 CRM system to automate your email campaigns, analyze customer behavior — and are thus able to sort customers according to propensity to buy sooner than later, and thus get higher response and results and sales on a marketing campaign — that feeling lasts a lot longer. It hits much deeper chords in our emotional vessel — security, actualization, and aspirational fulfillment, and a sense of comfort that we will be able to maintain what we have earned vs. lose what matters most: our ability to survive and provide for our families.

The coolness factor of the handbag doesn’t add to our sense of security or help us achieve higher goals, like a job promotion, praise and recognition that lead to job security, potential end-of-year bonuses and so on. These outcomes from a wise business purchase can help us achieve outcomes that last far longer and have much stronger applications for our long-term wellbeing than a trendy luxury item. When you can strike these emotional chords among B2B purchasers and then deliver customer service and products that fulfill the implied promises, you are far better poised to generate sustainable sales and increase existing customer value.

To achieve success in B2B marketing and up your chances of getting a premium price by eight times, think of daisy chains. Big choices that are associated with big outcomes are often made up of decision daisy chains of which the purchaser is not even aware. Back to purchasers of marketing technology or marketing services, such as consulting or agency work. It is not as simple as buying the coolest brand, trendiest design or the lowest price. The choice is complex and influenced by a chain of “what ifs.”

  • What if I buy something that doesn’t work or takes too long to implement?
  • What if I waste my budget and can’t buy what else I need to perform and reach goals?
  • What if the agency doesn’t deliver new ideas that beat past programs?
  • What if I look bad to my bosses?
  • What if I don’t get recognized for doing a good job?
  • What if I lose my job because I didn’t reach my goals?
  • What then will happen to my job security, income, ability to pay my mortgage, car payment and support my kids’ dreams?
  • … and so on.

While you don’t want to craft messaging that creates the fear of the “what ifs” happening, and position your brand as the fear monger or a manipulator, you do want to subtly project your brand’s ability to dismiss all the unconscious and conscious “what ifs” that come to mind during any B2B purchasing process that has substantial implications and outcomes.

You can do this by tapping into psychological drivers and influencers such as:

  • Authority: Who are the authorities who support and align with your category and/or brand? How can you use their allegiance to attract others? Better yet, who are the authorities within your brand and how can you elevate their voices?
  • Social Proof: Share case studies as part of your “thank you” follow up after a sales call. Showcase brands that reflect your prospects’ brands and show results that you can help new clients achieve, as well.
  • Actualization: Tell a story about how your brand helps clients’ achieve the emotional goals they strive for within their jobs. Whether they are purchasers of marketing technology, IT, educational systems or medical devices, there’s always a deeper purpose or “why” behind what they do. In most cases, it is not about the products they buy for their companies, but their ability to influence positive outcomes for the people they serve, like a better education, smarter way to work, or medical devices that deliver an accurate diagnosis the first time.

When you can do even just the above, you take price out of the equation, and put partnership in the process, which lasts a lot longer than the joy of a quick sale for low price, and much much longer than the joy of having a beaded crocodile handbag that will be forgotten in a few months’ time.

Building an Audience-Focused Content Strategy

Generating content that is relevant to your audience is easy; delivering unique content that actually serves its needs is significantly more difficult. That requires a content strategy.

Generating content that is relevant to your audience is easy; delivering unique content that actually serves its needs is significantly more difficult. That requires a content strategy.

These days, it’s not enough to produce loads of content based on keyword research alone. That might have worked years ago, when Google judged a webpage’s relevance and quality by keyword density. Since then, Google has revamped its algorithm and leaned on artificial intelligence to reward content that’s unique, useful and engaging. Focusing on people’s needs — not just their search queries — is the new goal of content marketing. And yes, there’s a big difference.

Does your content strategy really speak to your audience? And, equally important, does your audience notice? Forging a content strategy that achieves these objectives will likely help all of your marketing efforts. Here, we’ll review the basics for building an audience-focused content strategy.

Step 1: Know Your Audience

To build an audience-focused content strategy, you must first understand your audience. Who are they, and what do they need? What are their hardships? Why might they want your help? In terms of your content, would your audience prefer articles, blog posts, video tutorials, infographics or something else?

Listening is the key to answering these questions. Keyword research — specifically long-tailed keywords in your analytics reports — are one piece of the puzzle. There are better ways to get actual human feedback, though. Check websites such as Yelp and Reddit to see how people talk about merchants and issues in your sphere, or read your own social media comments for more insights on customers’ needs and wants. Brick-and-mortar business owners can ask their employees about what’s on customers’ minds.

Only after you truly know your audience can you move on to the next step.

Step 2: Find Your Content Tilt

At the core of this endeavor is finding your content tilt. Don’t worry if this is the first time you’ve heard this term — you’re not alone. Your content tilt is a form of branding; it’s what ultimately makes your content valuable in a way that’s unique to your business. Finding your content tilt doesn’t just mean pumping out articles that are relevant to your customer’s needs. Rather, it’s about diving deep into the core purpose of your business — thinking carefully about what makes your business remarkable — and then understanding how you’ll help your customers in ways no one else can.

Want an example of a content tilt? Think of how Kelley Blue Book established itself as the go-to resource for people who want to buy or sell used cars, or how Consumer Reports became known as the authority on informative, objective reviews. For another example, go to YouTube and watch different videos of chefs demonstrating their recipes. Then, watch one clip of Nadia G’s “Bitchin Kitchen.” That’s one heck of a content tilt!

Most businesses these days produce plenty of content. They barrage customers with online and print ads, coupons, blog posts, Facebook posts, Twitter posts, Instagram pictures, email blasts and more. And yet, still, people in business are often dissatisfied with their marketing.

That’s because content without a tilt is just noise in the crowd. Find your tilt, and you’ve found your voice. Unlike noise, a voice can send a message.

Step 3: Set Goals

What do you hope to accomplish with your content strategy? Your answer to this question depends largely on your website or the type of business you run.

4 Ways to Make Your Website Work Better

“Make your website work better than what?” you might ask. Better than it has. Better than it will if you decide to make changes or build a new site based on some vague notion that the site isn’t working now.

“Make your website work better than what?” you might ask. Better than it has. Better than it will if you decide to make changes or build a new site based on some vague notion that the site isn’t working now.

1. Define Success

Moving past vague notions means finding out what really is and is not working on your website. Which in turn means defining what the website is supposed to accomplish. Without the end goal in mind, you may as well stick with vague notions, because solid data can only lead the way if you know where you want to go.

2. Dive Into the Data

Once you have defined your goals its time to dive into the data that will provide you the ability to do a real quantitative examination of your site.

For most sites, Google Analytics data is all the data you’ll ever need. I have written elsewhere about the most basic analytics data points to track, so don’t let the overwhelming amount of information stop you in your tracks. (And I’m happy to chat with you if you have questions about diving deeper.)

The data should provide insights into the strengths and weaknesses of your website — what areas to double down on and what you need to shore up.

3. Prospect Perspective

Once you’ve established that quantitative framework you have to decide what to do with the data you’ve found. In other words, the quantitative information leads to some qualitative questions. For example, data on how long a visitor spends on your site and how many pages the average visitor views naturally lead to questions about how to get visitors to stay longer and view more pages.

One of the surest ways to increase engagement is to double- and triple-check that your website is written and presented from a prospect’s perspective. Your firm’s internal org chart or product lines aren’t typically going to matter to a prospect. Instead, arrange the information on your site to answer all of a prospect’s questions in one place.

For example, rather than separating services completely from case studies, the services pages should include sidebar links to the case studies most relevant to that service. The goal is to bring they information to the visitor, not to make them figure out your website’s organizational logic.

Be sure that you’re taking into account not just their interests, but also their timing. You’ll need different types of content for prospects who are just beginning their journey and prospects who are much closer to making a decision.

4. Focus on Benefits and Outcomes

Laundry detergent bottles don’t tout “20% more alcohol ethoxylate!” They tout 20 percent more whitening power. You need to follow the same pattern because no-one really cares about the process; they care about the outcome. Focusing on benefits and outcomes is another part of marketing with the prospect’s perspective in mind.

However, the laundry detergent packaging also offers a cautionary tale: nobody believes “better” anymore. We’re so inundated with advertising claims, that even with “proof” in the form of hard data, we’re dubious of all claims we can’t see with our own eyes.

Focus instead on differentiators and you remove the good/better/best evaluation from the equation. You still have to back up your differentiation claims with evidence in order to best your competitors, but building credibility for that comparison should be easier.

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.

Setting SEO Strategies and Priorities for 2015

As you turn the calendar to 2015, it is time once again to revisit the SEO successes or unmet challenges from the previous year and set priorities for what must get done during this year. Setting priorities for SEO is difficult. SEO is fast-moving, constantly changing and highly tactical marketing. There is always the temptation to chase the changes in search algorithms and ranking factors, for these changes require tactical solutions. It is easy to focus so intently on tactics to meet these immediate changes in the search that the overarching goals can get lost in the details, deep in the weeds. Good tactical execution done without real strategies and clearly set priorities is like driving fast with no directions or destination.

As you turn the calendar to 2015, it is time once again to revisit the SEO successes or unmet challenges from the previous year and set priorities for what must get done during this year. Setting priorities for SEO is difficult. SEO is fast-moving, constantly changing and highly tactical marketing. There is always the temptation to chase the changes in search algorithms and ranking factors, for these changes require tactical solutions. It is easy to focus so intently on tactics to meet these immediate changes in the search that the overarching goals can get lost in the details, deep in the weeds. Good tactical execution done without real strategies and clearly set priorities is like driving fast with no directions or destination.

Here are three things to consider as you go about setting your SEO strategies and priorities for 2015. How have your customers changed in their use of search? What are your business goals for 2015? Are you looking to grow, introduce new products or services, or regain lost business or traction in your industry? Does your site reflect your business? Does it offer anything of value to the customer or is it a static billboard or catalog? How and when will you be changing it? Finally, look at your SEO program and set the goals and priorities.

What About the Consumer?
There is a clear trend toward consumers using mobile devices for their search. Are you ahead or behind your customers? Review your analytics and consider what devices your customers are using. If you have not seen a clear uptake in mobile, don’t simply rationalize that your customers are different and haven’t moved to mobile yet. If your mobile traffic is not growing in relation to other Web devices, you may be losing ground already.

Another clear trend is that consumers are using social media to vet businesses and products. Social media today are clearly interlinked with search results. In setting 2015 priorities, you must look at how consumers are using social media relative to your business. Also, don’t forget to look at which social media sites are their favorites.

Are Your Business Goals Realistic?
If your business is growing, you will need to look at where online growth will come as you move to set your 2015 search directions. Do you expect huge growth from search? If so, you will need to look long and hard at how you will make this happen. Be reasonable in your expectations. In short, curb your optimism. Ground it in real numbers. It is not sensible to expect huge growth from search in a vacuum. Branding is ever more important element in search, so if your brand is weak, so too will be your ability to generate new traffic from search.

If you are introducing new products or adding a new line of business, you will need to make sure that you marketing program supports the product launch in all of the media that search influences. I am constantly surprised at businesses that simply add a page to their existing site and expect traffic. This may have once worked, but it does not work now.

Visit Your Site With Fresh Eyes
Come to your site as if you are a new customer. Do a search for your own products and follow the path. You may be surprised at what you discover. Does your site show up for the keyword searches that best describe your business? Did you turn up an outdated page as the key result of your search? On visiting the site from a search, did you easily find what you wanted? These answers may help set your direction.

Content is key for search success, and customers coming to your site will be looking for content that answers their search quest. Does your content fill the bill? One of my favorite exercises is to pull content from key pages and replace the name with “our company” and replace product and service offerings with “this product/service.” Then look and see if there is anything that can be learned about either the company or the product from the page. This is a quick way to find just how generic your content is. For small businesses, you can frequently trade in a different type of business. For example on the About Us page for an accounting firm swap in veterinarian for accountant and see if the page still makes sense. If it does, the page is virtually worthless for search since it offers nothing of real value.

Based on this high level review, you will be able to set your directions without getting lost in the tactics. You may discover that your first priority is to make the site more mobile friendly. You may also discover that without the addition of more and better content, being mobile friendly is not going to be as important as developing more content, and so it goes. Once the direction is set, you can relatively easily set the priorities and fit together the essential tactics.

Focus Group of One

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

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

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

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

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

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

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

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

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

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

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

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

How Big Should Your Campaign Budget Be?

How do you set a budget for a multi-touch, multi-target B-to-B digital campaign like the one Michelle was describing? The short answer is: Spend as much as delivers your threshold level of ROI. But, in B-to-B, it’s not so simple. Large enterprise sales cycles are long, as much as 18 to 24 months, so sales results won’t be available until long after she needs to make campaign decisions

At the ClickZ Live conference in New York, Michelle Killebrew presented an interesting case study of an IBM campaign called “Rethink Business.” It got me thinking (or, should I say, rethinking?) about campaign budgeting. My question is: How do you set a budget for a multi-touch, multi-target B-to-B digital campaign like the one Michelle was describing? The short answer is: Spend as much as delivers your threshold level of ROI. In other words, if Michelle’s campaign is generating qualified leads that convert to sales at a return that pays for themselves, covers her overhead, plus leaves a profit for IBM, she can keep the campaign running until the cows come home. Or until the campaign fatigues, and dips below the required ROI hurdle rate.

But, in B-to-B, it’s not so simple. Large enterprise sales cycles are long, as much as 18 to 24 months, so Michelle’s sales results won’t be available until long after she needs to make campaign decisions. And some of those results may never be known, since the leads are likely being worked by third party channel partners, who are often reluctant to share sales information.

Plus, Michelle said she had other objectives in mind for this campaign other than leads. She wanted to create digital experiences for prospect engagement, and she wanted to demonstrate the use of IBM’s proprietary marketing tools.

So in B-to-B, budgets are often set at a higher level than campaign ROI. Here are five methods that B-to-B marketers may be using to set marketing budgets.

  1. Percentage of last year’s budget. Take last year’s budget and subjectively add or cut, to arrive at a figure for this year’s budget. Can be applied by periods other than a year, like the quarter. Not based on much logic, but in common practice.
  2. Percentage of sales. Calculate a percentage of expected sales in the coming year; 4 percent is common in B-to-B for large, mature companies. Avoid using last year’s sales volume as the basis for this calculation. If last year was a bad year for your company, you won’t have a large enough B-to-B marketing budget to meet your growth goals in the coming year.
  3. Percentage of selling cost. A variation of No. 2, where the denominator is sales salaries and commissions, instead of revenue. You might see percentage levels like 20 percent to 30 percent with this method. It neatly reflects B-to-B marketing’s role as an efficient driver of sales productivity.
  4. Match your competition. In a high-growth, fiercely competitive stage in the product life-cycle, keeping up with your competitors may make sense. If you can find out what they are spending, which may require some clever intelligence-gathering activity.
  5. Zero-based budgeting. In this method, you determine your specific marketing goals, tied directly to business objectives. Then, you figure out what you need to achieve your marketing goals. For example, say it costs $350 to generate a qualified SMB lead that will convert to sales at 20 percent conversion rate. To bring in 3,000 SMB customers in the year, we need $5.2 million budget ($350/.2*3000). Clear and accountable.

Zero-based budgeting is the best way to go, in my view. You have a firm grasp of the numbers, and you are delivering against business objectives. With this approach, you can take you plans anywhere in the organization, and explain what you’re doing in a way that is meaningful to everyone.

A version of this article appeared in Biznology, the digital marketing blog.

Help! I’m Being Stalked by a Bathtub!

As a marketing agency, we’re always recommending different media channels to our clients depending on the product, the target audience demographics, marketing goals, etc. And, like many of you, I thought online retargeting was a clever way of “helping” to remind browsers that since they had been interested in a product/service at one point, they might still be interested in making a purchase from that site, so a little tap on the shoulder seemed like a clever way to stay top of mind. Until it happened to me.

As a marketing agency, we’re always recommending different media channels to our clients depending on the product, the target audience demographics, marketing goals, etc. And, like many of you, I thought online retargeting was a clever way of “helping” to remind browsers that since they had been interested in a product/service at one point, they might still be interested in making a purchase from that site, so a little tap on the shoulder seemed like a clever way to stay top of mind. Until it happened to me.

Retargeting, for those of you who may not know, involves having an advertiser drop a cookie into the consumer’s browser which enables the advertiser to follow that consumer around and display an ad for the advertiser after they’ve left the original site.

The logic is sound, the process is relatively simple, and it seems to make good marketing sense. Before it happened to me, I equated it to shoe shopping. I visit a store and see a pair of shoes I like. I try them on, but since I haven’t really looked in a lot of other shoe stores yet, I decide to put off the purchase until I’ve looked at all my options. But in the back of my head a little voice keeps whispering, “Those black patent kitten heels were perfect—even if they were $100 more than you wanted to spend.” I may or may not go back to that first store to get them but I do think about those shoes for quite a while—and with my luck, I return to the store only to find they are now sold out in my size.

But if I was shopping online and the shoes I liked were at Retailer A, I’m now seeing ads for those shoes no matter where I cruise on the Internet. Yep. Those black patents are now stalking me. Not whispering, but shouting out to “come back!”

However, I must confess that my recent stalking incident was not about shoes at all, but about bathtubs.

My husband and I are remodeling a bathroom, so I’ve spent quite a bit of time searching for the perfect bathtub online. Yesterday I actually placed an expensive bathtub in my shopping cart and proceeded to check out, but at the 11th hour started thinking that maybe my contractor could purchase the same tub for a better price. So I abandoned my cart. And in the process, it seems, launched obsessive tracking behavior that could only be rivaled by a professional stalker.

No matter what site I visited while researching client-related work, bathtubs kept appearing. Some were in the upper right hand corner of the page, so as I scrolled down the page they would disappear from view. Whew!

Others seemed to travel down the page with me … tumbling tub over tub with prices flashing, offers blazing and the lure of a long, hot soak compelling me to glance … nay linger … on the designer tub dangling within the reach of a mouse click.

But since I had no intention of completing the purchase transaction without the nod from my contractor, the ads seemed to get more annoying than helpful as the day went on. At one point, a colleague was looking over my shoulder while we were reviewing some online research. After looking at the page for about five minutes, she pointed to the tub ad and commented, “That tub reminds me—did you finish remodeling your bathroom yet?”

Intellectually I understand why retargeting is so valuable. Statistics show that 95 percent of users leave a site without making a transaction, and the ones retargeted are 70 percent more likely to complete a purchase, so it makes perfect sense to retarget.

However the default setting for most retargeting platforms is 30-90 days, so if you’re planning to include retargeting in your marketing mix, think carefully about cookie duration and ad fatigue. Because right now, my fatigue is only off-set by the dream of a long, hot soak in my new tub—cookie-free.

How Big Is Your Vision?

Way back in the Internet dark ages of January 1996, Bill Gates wrote about and coined the phrase “Content Is King.” He was talking of course, about Web content and the need for people and organizations hoping to monetize the Internet to consistently produce fresh and relevant topics in order to gain the interest and loyalty of viewers, just as television had been doing, radio before that and print media the longest of all. His assertion that “over time, someone will figure out how to get revenue” from Internet advertising is frighteningly similar to today’s gurus predicting much the same in regard to social media marketing. Just as back then—when companies and marketers struggled with deciding whether a Web presence was needed—today there are still major corporations only testing the social media waters, even if only half-heartedly, to keep pace with competitors.

Way back in the Internet dark ages of January 1996, Bill Gates wrote about and coined the phrase “Content Is King.” He was talking of course, about Web content and the need for people and organizations hoping to monetize the Internet to consistently produce fresh and relevant topics in order to gain the interest and loyalty of viewers, just as television had been doing, radio before that and print media the longest of all. His assertion that “over time, someone will figure out how to get revenue” from Internet advertising is frighteningly similar to today’s gurus predicting much the same in regard to social media marketing. Just as back then—when companies and marketers struggled with deciding whether a Web presence was needed—today there are still major corporations only testing the social media waters, even if only half-heartedly, to keep pace with competitors.

For me, however, two lines in the Gates vision statement take on a slightly different connotation than his thoughts on content: “The definition of ‘content’ becomes very wide” and “Over time, the breadth of information on the Internet will be enormous, which will make it compelling.”

I read those two lines and what immediately strikes me is the overwhelming amount of data being generated during these last 17 years and how it is being captured, nurtured and put to work in areas such as Lead Generation, Brand, Affinity, Cross-Channel and Retention marketing. If at all.

IBM has an infographic regarding the flood of Big Data they use in demonstrating how their Netezza device handles integration for several major marketing organizations. This shows how, with connectivity, speed and bandwidth issues having become nearly eradicated during just the last two to three years, the amount of collectible, actionable data has exploded.

Unfortunately, the amount of irrelevant and useless data being collected is even greater than the actionable data, and being able to simply store that much data, let alone begin to organize and digest it all, is a major concern for most organizations. Before even thinking about the incorporation of Big Data initiatives, there should be an organizational review of quality for the existing information held in the collective datamarts that feed the central repository used for decision-making. Long before Big Data, the issue of Bad Data must be addressed.

Whether you are a B-to-B or B-to-C marketing entity, the creep of inaccurate data is constant across every customer and prospect contact you currently maintain. Experian-QAS has a stark reality “Cost of Bad Data” infographic showing the millions of dollars lost each year as a direct result of inaccurate and incomplete contact information. Complacency and budgetary shortcuts speed the process even more. Whether it is via an in-house effort or using third-party tools and vendors to perform ongoing hygiene, the vitality of your contact strategy is not sustainable without regular maintenance.

Once secure in the clarity and accuracy of your core data, you can move on to the integration plan for all of the additional goodies sprouting up from the Big Data seeds being sewn across every outbound and inbound marketing channel being utilized. But again, more planning and decision-making is critical before just jumping in and trying to grab every nugget. Perhaps the Fortune 50- to 500-level corporations might have the resources to take this on in one massive project, but I doubt that many small, mid or even larger brands can just dump everything into a pot and begin using the information gleaned into a successful series of campaigns. In a SAS/Harvard Business Review whitepaper I read recently; “What Executives Don’t Understand About Big Data,” this quote stood out to me:

“What works best is not a C-suite commitment to ‘bigger data,’ ambitious algorithms or sophisticated analytics. A commitment to a desired business outcome is the critical success factor. The reason my London executives evinced little enthusiasm for 100 times more customer data was that they couldn’t envision or align it with a desirable business outcome. Would offering 1,000 times or 10,000 times more data be more persuasive? Hardly.”

Having the foresight to develop phased approaches for data incorporation based on both short- and long-term ROI is the most realistic approach. Using results from the interim stages provides the ability to thoroughly test and analyze and measure value, keeping the project moving forward steadily while minimizing roadblocks to the longer-term goals.

My initial recommendation for the process would be along the lines of:

  1. C-Suite leadership establish the long-term goals for organizational success and with other Senior Management develop the phases to follow based on data, budget and resource availability to be assigned through each phase.
  2. Set the expectations and build the benefits case of the project across the entire company, communicating these goals in order to coordinate the gathering and availability of resources needed from whatever silo in which they reside.
  3. Design the KPIs that will be required in determining accuracy of marketing integration of the insights being introduced during each phase.
  4. Test and Measure every step of each phase for completeness and success before moving on to the next.
  5. Build simple and multivariate test panels into marketing campaign segmentation to analyze what new data elements truly provide sustainable lift in response.

I would love to hear your thoughts.