Marketing In A New Age

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The world is in the midst of a new, technologically disruptive period, altering how we relate to the world and to each other as humans. As a consequence, companies and consumers have a second chance to meet face to face as if for the first time. Technology is once again shaking up markets, fueling competition, and presenting opportunities for companies to seize lasting strategic advantage.
Integrating research from diverse fields, this white paper introduces a new marketing model that addresses issues posed by today’s digital sales cycle. It marries new technology with advanced learning models to drive the creation of meaningful and mutually beneficial dialogues between companies and their customers. While applicable to marketing in general, this model targets marketing of products that require complex consumer decision frameworks.

This white paper flows out of a single, provocative question: what would happen if a human salesperson were as bad at selling as the majority of today’s websites? The answer is simple: they would be fired.
For far too long, marketers have gotten away with being terrible salespeople online because they are insulated by the law of large numbers—if hey churn through enough people, eventually some portion of them, usually a minute portion, will convert to customers. It’s a volume business, but it’s also tremendously expensive, inefficient and ineffective for company and customer alike.
What I and the Tahzoo team believe is that the maturation of both big data and content management technologies have reached such a level of sophistication that a new era of online selling is now entirely within reach.
Why then do so few companies seize the opportunity before them? I believe it’s because they lack the right models for understanding their customers’ learning models—what those customers know, how they learn and how they decide what and when to buy. That vacuum, in turn, produces trepidation and over-cautiousness in the marketers, and likely in the customers as well. In other words, the marketers don’t truly know their customers, so they don’t know how to educate those customers about the salient details of the emotionally and intellectually complex purchase decisions they are about to make. Consequently, the marketers are paralyzed and end up doing very little or nothing at all. Often, so do the customers.
Most purchases these days are wrapped inside a considered sales cycle and marketers must think about how to create conditions for learning and educating their customers in order to help them “decide.”
To that end, Tahzoo relies deeply on the precept that all potential customers adhere to preferred learning models that were first laid out by Robert Gagné in the 1980s.
Gagné set out the educational foundations for how one learns, and outlined the process we all go through as we transition from uninitiated shoppers to paying customers to eventually become long-term advocates (some would say evangelists) for the brands and products that most closely align with our learning models.
On the other side of the equation, we have the content that must educate those consumers. We have mapped the various learning models to a series of data-driven content archetypes that not only help us as marketers to speak the language of our audiences, but also to speak to them through preferred channels. That is, some people prefer textual information, others prefer video, yet others favor information graphics, and so forth.
When combined, learning models and content archetypes inform powerful and successful content strategies that are more effective at educating customers and, therefore, more effective at marketing to them. I believe that the sequencing of content in a variety of formats, through multiple digital channels, in order to ensure prospects are ready at a moment’s notice to convert from prospects to customers is the corporate challenge of our time. And Tahzoo is out to solve it.
The problem has existed since the 1970’s. Companies spend increasing sums on traditional marketing initiatives, only to experience diminishing returns
on investment. Campaigns struggle to connect with consumers, and, when they succeed, very little real information is communicated. Though the least- informed customer can pinpoint the problem, the self- appointed experts cannot articulate a cause.
Traditional frequency and reach models measure the success of marketing campaigns by how many and how often people experience an advertisement. These models reflect an era where the majority of people had fewer than ten channels on their televisions, and a
handful a brands from which to choose. Firms focused on brand marketing simply because channels and technology did not provide bandwidth for anything else.
Technology has rung the death knell on that era and marketers and marketing firms need to acknowledge they are no longer the sole gatekeepers of purchase- critical information. We must aspire to more than just brand-building.
To effectively communicate—not merely to present— relevant and personalized content to drive consumer decision-making means that the floodgate to personalized content must be opened, but firms must invite consumer to explore all their options and mere presentation must progress to a real and lasting conversation.
When this happens—when learning models and content archetypes are truly aligned—then and only then will customers be both engaged an educated. And that’s when great things can happen.
At the core of Tahzoo’s approach is the exchange of information between company and consumer. That is to say: how companies educate their customers. Increasingly, customer experience technology is tasked with managing and delivering deep consumer insights by applying robust psychological models of learning to drive the sale cycles to facilitate customer decision making.
By empowering customers to make decisions through better and deeper knowledge of the products they are buying, such a model approaches marketing from a instructional, rather than a sales perspective. A client is asked, in essence: “What do you need to know in order to be able to purchase this product?”
For a car, that knowledge might be an understanding safety standards, or the indirect relationship between fuel efficiency and horsepower. For a mutual fund, on the other hand, it might be a simple breakdown that allows a client to more easily digest quarterly reports.
Marketing success, therefore, is determined not by the persuasive skill of a sales person, but rather by the quality of customer engagement in learning about the products they are buying. Thus, in understanding customer needs, their experiences can be better tailored to each customer touch-point.
Today’s content management platforms leverage a massive increase in computational power to deliver differentiated experiences at scale using sophisticated audience analysis algorithms. A differentiated experience—i.e., personalization—is crucial to digital customer experience management, because no company has one single “type” of customer, but rather several, usually very different types of buyers.
Recall that mutual fund company mentioned earlier. It must juggle customers as varied as the neophyte investor just starting his first 401k to the near-retiree hoping to nurture her nest egg far into retirement.
These audiences are so different in their needs and in their knowledge and in the their learning styles as to be considered polar opposites—an attempt to create a single digital experience that addresses both will certainly fail both. Each customer has unique needs and expectations as to how they wish to be engaged, where they like to be engaged, the knowledge to be imparted and, especially, in the language used to engage them.
Combining prominent learning archetypes allows us to develop a specialized consumer experience.
Our approach is comprised of two aspects: Developing Our Model and Delivering the Experience. Developing the Model involves understanding the target customers and the creation of a personal learning sequence that describes, in step-by-step fashion, how any one particular customer type progresses through their learning journey.
Delivering the Experience involves arranging content in such a way that it is relevant to individual preferences and perspectives. For the consumer, this interactive design and personalized approach has great appeal: they gain the sense of achievement that comes with making an informed purchasing decision, and they gain the value of an excellent product.
We refer to this as the “considered sales cycle.” And, in a world where the considered sales cycle dominates, educating consumers becomes a prerequisite to any purchasing decision, even taking precedence over branding. We must educate to sell.
Since the mid-2000s, several companies have amassed huge databases of textual information—social media, news, blogs, websites, and other digital behavior. These databases contain upwards of 75 billion data sets, which can be refined into valuable customer insights.
These data sets are, in essence, first-hand conversations that we can listen in on without infringing on anyone’s personal privacy. (i.e., The
data is anonymized.) They are, consequently, devoid of the typical biases contaminating traditional “inquisitorial” marketing research methods—e.g., customers who say one thing, but do another; or the inherent influence of the researcher on the respondent shaping how they answer questions. Better yet, we can do it all this in real time and we can evolve our methods continually as trends evolve in order to make better, more-informed projections of customer behavior through time.
The components of Tahzoo’s model stem from the work of psychologist Robert Gagné, a psychologist who was a pioneer in the field of instructional design in the 1980s. Gagné’s model of instruction focuses on the transmission of information to uniform subjects who nonetheless exhibit personalized needs and styles. His Taxonomy of Learning Objectives states any possible learning task includes five components:

  • Verbal Information
    Specific facts and raw data
  • Intellectual Skills
    The ability to perform certain mental tasks
  • Cognitive Strategies
    How people think and learn
  • Attitudes
    Acquired emotional states which effect decision making
  • Motor Skills
    The coordinated use of muscles to achieve a given outcome

We have adapted these components to explain purchasing behavior. Since purchasing decisions do not require motor skills, we have narrowed our list to just four learning objectives and adapted and refined them into a market-oriented context. Learning objectives outline key information and attitudes any customer must possess in order to make a purchasing decision.
Collecting customer insights from the mass of available data, in essence, allows marketers to understand the customers’ Learning Objectives and, therefore, to fill the gaps in each consumer’s product education to ease the sales cycle. Better-informed purchase decisions ultimately align business and consumer intents to form stronger and more valuable relationships between customer and company.
Once identified, a purchasing decision is separated into four components—a Taxonomy of Needs—that must be satisfied before the customer can make an informed decision.

  • Verbal Information
    Relating information back to a person’s preexisting mind states is key to creating better content. Selling often involves conveying new information, but tethering new concepts to old ideas makes the new one easy to remember.
  • Intellectual Skills
    People often struggle to apply what they have learned to situations outside of the direct context in which it was taught. For intellectual skills to take root, they must be applicable across many situations.
  • Cognitive Strategies
    How people think and learn varies widely. We can use personal Learning Objectives to create content that can be varied by learning styles to appeal to each customer segment.
  • Attitudes
    As with learning styles, attitudes can vary wildly among individual customers. Shaping an attitude requires consistent delivery of an experience that reinforces concepts that produce an attitude. Tapping into established attitudes is always going to be easier than constructing new ones.
  • Motor Skills
    With an understanding of what goals content needs to accomplish, we can sequence that content to address specific learning models.

With an understanding of what goals content needs to accomplish, we can sequence that content to address specific learning models.
Again, we can return to Robert Gagné, who laid out the Nine Steps of Instruction of any effective lesson. While each of these nine can be considered as separate processes, they are inherently integrated and should be developed concurrently to create a unified and overarching customer experience to achieve Learning Objectives.

  • Gain Attention
    Creative and relevant content is crucial to capturing customer attention. After all, what good is a sailboat advertisement to someone living in Oklahoma? A consistent lack of consideration by companies of the context of online advertising goes a long way to explaining chronically low response rates that advertising often generates.
  • State a Purpose
    To win a customer’s attention is a feat in-and-of itself—to keep it is another challenge altogether. A customer is inclined to stay involved in an advertisement if they are interested in that product and they comprehend what you are asking of them (e.g., to purchase a product).
  • Stimulate Recall
    People are more likely to listen to an advertisement, and to remember it, if it connects with something they already know. The brain is nothing more that a web of connected neurons and we can easily recall information linked to other information. The old saying goes, “Neurons that fire together, wire together.” That is to say, when our brains lay down an electrical pathway through the brain in the form of memory, those pathways endure and future memories that approximate them are more easily recalled because of it.
  • Deliver Information
    Learning Objectives are used to design an experience that combines useful content and relevant channels. Both are then empowered by data-driven contextual information to communicate more effectively through specific content archetypes.
  • Elicit Performance
    The steps to a purchasing decision—not merely the purchase itself—are meaningful. Measuring how an entire experience is stored and recalled allows us to anticipate future consumer behavior and to reinforce the favorable pathways to purchasing.
  • Assess Performance
    In our efforts to elicit a desirable behavior, we must immediately provide feedback on their decision. Feedback should always be positive.
  • Enhancing Retention and Transfer
    Never miss an opportunity to reinforce the customer’s wise decision and to move the customer toward deepening the relationship with the company through positive perceptions and future purchase opportunities.

Consumer decisions are a finite resource and there are always impediments to the decision-making process. Tahzoo presumes that all prospects, before they become customers, have a pre-existing preference toward indecision, concepts known in psychology as choice deferral and omission bias. In essence, it is easier and less risky not to purchase than to purchase.
This is understandable. Consumers are bombarded with product choices. Our job as marketers is educate and persuade in order to overcome these biases. Learning Models can help us do that more effectively.
None other than Aristotle laid down the principles of education as persuasion—a discipline known as rhetoric—over two thousand years ago. His three modes of rhetoric have never been better articulated, and they provide a powerful guide to content creation to this day. Those modes are:
Ethos (Credibility)
Language and ideas convey credibility, creating a trusting connection between company and customer. In this regard, integrity is among the most valuable assets a company can have. Firms should do everything in their power to establish credibility and, once won, they should guard credibility like a prized gem. Eventually, they can rely on their established credibility to enhance future relationships with consumers.
Pathos (Emotion)
A direct appeal to a customer’s emotions. If ethos establishes credibility, pathos makes a lasting bond. Both unite to reinforce trust and loyalty. With regard to content, when firms put forth engaging content, they connect with consumers on a deep and personal level. Because of ethos the company reputation is established, while pathos serves as a shortcut through the customer’s critical thinking and research phases.
Logos (Logic)
Appealing to reason. Reason, however, is not necessarily rational, but rather it relies upon a logical chain of thought through a traditional proand-
con argument within the consumer’s mind.
From design elements like color and imagery, to the nuances of messaging, effective content relies upon all three Aristotelian modes of rhetoric. To craft and design highly effective content, however, we must apply insight. Like all other aspects of customer experience, content must be driven by data. Insight solidifies our knowledge of existing and potential customers and helps us construct the learning models and content archetypes that speak to them directly.
Insight is the outcome of superior customer research and involves a hierarchy of understanding:
Developing a model for creating personalized and informative content is half the battle; the second have is delivering it. Over multiple interactions and across multiple channels, consumers acquire the information they need to make a purchasing decision.
To effectively deliver information is to understand how people process it. The basic framework for the absorption of information revolves around the concept of schemas first presented by Swiss developmental psychologist Jean Piaget in 1928.
A schema is the basic building block of perspective: an “archetype.” To comprehend the schema, simply picture any given subject—a bicycle, for instance. Quickly, the mind forms a representation of the subject that serves as the schema—a metal object with two circular wheels.
The sub-schemas include various mental and emotional associations: a red object that is used for childhood
activity with friends.
Schemas can be modified over time through assimilation and accommodation. A child seeing a zebra for the first time might say it was a horse and assimilates (or combines) that information into her horse schema, calling it a horse with stripes. Accommodation happens when she considers the properties of a zebra as compared to a horse and she learns the name zebra.
There are many challenges to delivering personalized content in a planned sequence. The process begins by accurately segmenting and identifying customers. It continues with the careful selection of content for each customer, and the consistent delivery of that content at scale.
The Anonymous User Problem
Most of the time, individuals visit websites anonymously. Without cookies tracking them, the information that can be gathered from an individual is limited to: IP address location, device details, and referring source or search engine. Extrapolating from this limited data is a common stumbling block in customer experience management, which explains why many online retailers push people to authenticate by signing in our signing up.
Tahzoo’s Learning Models approach does not ask customers to sign in or sign up. Instead, it employs a unique machine-learning algorithm that performs a Bayesian probabilistic analysis on each customer. It processes this information into a component-based content management system and chooses the correct template to apply content based on this knowledge of the customer. While not exactly a silver bullet in the delivery of exact-match content, increasingly we can get very close indeed.
Using Existing Data
Though the data is limited, our approach capitalizes on what is available. An IP address provides a reasonably accurate geographic location. Cluster-marketing databases like Nielsen’s PRIZM or Experian’s MOSAIC allow us to produce highly accurate demographic guesses about who lives where. Other variables such as time of day, season of the year and even weather can help us refine predictions and to target content to the customer.
Learning Behavior
Over time, as the consumer develops an identity, we can track behavior and form increasingly accurate and powerful inferences about their searching history and content preferences. Here, the approach shifts from relying on relatively uninformative location data to much more instructive observed behavior. The system operates based on carefully drawn probabilities, therefore confidence as to consumer attributes is critical to a highly specialized and highly accurate customer experience.
Component-Based Web Design & The Third-Page Problem
Owing to the degree of personalization required, the component-based Content Management System (CMS) is highly complex and the permutations quickly begin boggle the mind.
Take for instance the personalization of a homepage for five customer segments. It follows that there would be five variations of the homepage, one for each customer. If the site then has eight sub-pages, personalization quickly grows and additional 40 pages. Go another level deeper and imagine each of those eight pages itself has a perfectly reasonable number of three sub-pages. That would require an additional 120 pages. What began as a simple, three-level website with 33 pages has ballooned to a site with over 165 variations.
We refer to this as the “third-page problem,” the point at which many personalized sites give up as the management headaches become too time consuming and resource intensive to justify.
What if, instead of creating 165 different pages, you could simply create 165 variations of a single page? This is what component-based CMS’s allow. We can store elements of content separate from the underlying page structure—also known as the template—and serve up only the relevant pieces of content based on what we know about the customer viewing the page.
As we have learned from our friends in education, psychology and philosophy, insightful marketing is able to align the goals of companies and their customers. For the customer, a more relevant and personal web improves the purchasing experience. Conversely, the time, effort, and research required to purchase a product are reduced considerably. All the while, confidence is enhanced. At each touch-point along the way, companies who strive to communicate personally to customers, are making the purchase decision seamless and, perhaps surprisingly, even pleasurable.
This benefits the company through the fluidity of its sales funnel. When an advertisement is underperforming, a PR storm brewing on Twitter or a modal window is showing slowly decreasing conversions and the company has the power and the technology to optimize those poor performers in real time, the limiting factor to more effective—and more personalized—communications becomes simply a matter of how long it takes the company to reach a decision to change the messaging and produce the necessary content to make it so. This is the real power of the personalized customer experience.
Looking ahead, the trend towards refined models for delivering relevant and personalized experiences will be gradually and more widely adopted, enhancing the marketing strategies of all companies with the foresight to accept these strategies.
Those who profit most, however, will be the first-mover companies who adopt the model. Early adopters can deliver a customer experience light-years away from their competitors. Early adopters will earn a competitive advantage over those who stick with expensive and poor performing traditional advertising, while they also learn that customers are often willing to pay a premium for better customer experiences. In an age where a marketing campaign can easily cost upward of a $15 million, most of the initiatives discussed here can be had for a third of that or less.
We live in the time of the ever-connected consumer and of rapidly evolving technology. Accordingly, companies have limited control of their markets. In failing to adapt their marketing strategies to this shifting environment, they have watched their impact plummet.
For those wise enough to see the writing on the wall, however, such threats are no threat at all, but rather advantages. Digital transformation based on learning models and content archetypes is vital to the delivery of highly relevant and personalized experiences across channels and devices, and to the future success of virtually every company on the web today.
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