The Right Customer Promises Drive Better Marketing Results

One of the more infamous quotes in marketing is usually attributed to John Wanamaker, who reportedly said, " Half the money I spend on advertising is wasted. The trouble is, I don't know which half."

Cracking the code on what drives marketing effectiveness can be incredibly difficult. One TV ad, webinar, or ebook may be hugely successful, while another - based on the same theme and having similar creative elements and comparable distribution - fails to move the needle. In many cases like this, there's no readily apparent way to explain the difference in performance.

An article appearing in the current issue of the Harvard Business Review offers a potential solution for this conundrum, at least when it comes to brand advertising. "The Right Way to Build Your Brand" was written by Roger L. Martin, Jann Schwarz, and Mimi Turner.

Martin is the former dean of the Rotman School of Management and the author of several books on business strategy and management. Schwarz and Turner are both executives at The B2B Institute, a B2B marketing think tank funded by LinkedIn.  

The authors clearly state their central message early in the article:  " . . . the key to successful brand building is a clear and specific promise to the customer that can be demonstrably fulfilled. Advertising that makes such a promise almost always results in better performance than advertising that does not - even if the latter creates greater name awareness."

This conclusion was based on an analysis of a large database of advertising case studies maintained by the World Advertising Research Centre (WARC). The WARC database includes over 24,000 case studies drawn from global ad competitions. These competitions typically require their entrants to provide information about how well their ads worked.

Specifically, the authors analyzed data relating to more than 2,000 ad campaigns entered in competitions from 2018 to 2022. The first step of the analysis was to classify the campaigns based on whether they had made "an explicit and verifiable promise to customers." Forty percent of these campaigns (the "CP campaigns") included such a promise, while 60% (the "non-CP campaigns") did not.

Advertising that Included Customer Promises Performed Better

The authors then compared the performance of the CP campaigns with the non-CP campaigns on a variety of metrics and found that the CP campaigns outperformed the non-CP campaigns across most of the metrics. For example, the analysis revealed that:

• 56% of the CP campaigns (vs. 38% of the non-CP campaigns) produced improvement in brand perception, brand preference, and purchase intent.

• 45% of the CP campaigns (vs. 38% of the non-CP campaigns) resulted in increased market penetration.

• 27% of the CP campaigns (vs. 17% of the non-CP campaigns) resulted in market share growth.

The article also compared the performance of the CP campaigns vs. the non-CP campaigns based on the rating system used by WARC to rank campaign performance. The following table shows the results of that comparison.

As this table shows, the CP campaigns did better than the non-CP campaigns on all but the lowest level of performance.

Martin, Schwarz, and Turner also looked at what made the promises in the CP campaigns attractive to customers. They found that the most effective promises shared three important attributes. They were memorable, valuable, and deliverable.

Why Customer Promises Work

The authors have built a compelling case for including customer promises in brand advertisements. But what makes such promises effective? Martin, Schwarz, and Turner gave this answer:

"When one person makes a promise to another, it creates a relationship between the two. If the pledge is fulfilled, it builds trust, resulting in a valuable connection."

I don't disagree with this rationale, but established decision science principles provide an even more compelling explanation for why the right kinds of customer promises will deliver better business outcomes. This explanation is based on the interplay of rewards, goals, and motivation.

I wrote about this topic earlier this month, but here's an abbreviated recap of the relevant decision science principles.

• Motivation is a willingness to exert mental or physical effort in pursuit of a goal, and motivation is the primary driver of all human behavior.

• As humans, we pursue a goal because we expect to receive a reward if the goal is achieved. Neuroscience research has shown that our brain has a "reward system" that's activated when it processes information that signals a reward we value.

• When our brain's reward system is activated, we become motivated to pursue the goal that will enable us to reap the expected reward.

So, a customer promise in a marketing message will be effective when it signals a reward the recipient values. Martin, Schwarz, and Turner allude to this when they write, "Customers must want what the promise offers."

"The Right Way to Build Your Brand" is an important article for marketers. It's well worth the few minutes you will spend reading it.

Top image courtesy of Kevin Simmons (Mayberry Health and Home) via Flickr (CC).

[Research Round-Up] What CEOs Think of Marketing/CMOs and How Much Tech Buyers Trust Marketing

(This month's Research Round-Up features a study by Boathouse that reveals what CEOs actually think about marketing and CMOs, and a survey by Informa Tech that addresses how much trust B2B technology buyers actually place in marketing.)

The Third Annual CEO Study on Marketing and the CMO by Boathouse 

Source:  Boathouse

• Based on a survey of 150 CEOs at U.S. companies; 55% were with public companies, and 45% were with private companies
• Survey respondents were with companies having $250 million to more than $1 billion in annual revenue
• Survey respondents represented 17 industry sectors
• The survey was in the field September 9, 2023 - October 4, 2023

This survey explored the perspectives of U.S. CEOs regarding the performance of their marketing function and their CMO. It also addressed how CEOs view their job and the major issues they are facing.

Overall, this survey contains good news for CMOs and marketers. On most points, the survey found that CEOs have a more favorable opinion of their marketing team and CMO than they did when earlier versions of the survey were conducted in 2022 and 2021.

To set the stage, the survey asked participants about the problems they want marketing to help them solve. The top five problems selected by respondents (from a list of 15) were:

1. "Create new customers, retain existing customers, and drive revenue growth" (52% of respondents)
2. "Drive sales and grow market share" (45%)
3. "Stay ahead, differentiate, grow faster than our competition" (44%)
4. "Improve our brand/reputation" (41%)
5. "Transform the company's narrative in the marketplace" (40%)

Nearly half (49%) of the surveyed CEOs rated the performance of their marketing function as Best in Class. That was up from 24% in the 2022 edition of the survey.

The latest survey also found that CEOs view their CMO more favorably. In the 2023 survey, 26% of the respondents gave their CMO a grade of "A" for the overall performance of their role. That was up from 16% in the 2022 survey.

Concerning artificial intelligence, over half (57%) of the surveyed CEOs in the 2023 survey gave their CMO a grade of "A" or "B" on their ability to integrate AI/machine learning into their marketing efforts.

Despite the high grades for overall performance, the latest Boathouse survey identified areas where CEOs aren't as pleased with CMO performance. For example, only 23% of the surveyed CEOs gave their CMO a grade of "A" on strategy, and the lowest number of "A" grades given to CMOs was on their "ability to drive company growth."

2023 Trust in Marketing Index:  How B2B marketers can fill the trust gap by Informa Tech

Source:  Informa Tech

• Based on a survey of 150 B2B technology buying decision-makers
• 68 of the respondents were at the C-level or executive level of seniority; 82 were at the director level
• Respondents were located in the United States and the United Kingdom
• The survey was conducted in the summer of 2023

The purpose of this research was to assess the level of trust that B2B technology buyers have in marketing and identify factors that will increase or reduce that level of trust. To quantify the level of trust, Informa Tech created a "Trust in Marketing Index."

The survey used to develop the index included five index questions with numerical values assigned to each potential answer. The researchers calculated the average score for each index question and then added the average scores together to create the overall index score.

The resulting index showed that B2B technology buyers' level of trust in marketing is at 61 on a scale of 1 to 100. So, while the level of trust isn't horrible, there is significant room for improvement.

Here are the five index questions and the key survey finding for each.

• "In general, how much do you trust the information marketers provide in B2B content?" - 62% of the survey respondents said they trust all or a majority of the content B2B marketers provide.

• "How often are you disappointed with the value of B2B gated content?" - 71% of the respondents said often or sometimes.

• "How much do you trust personalized content . . . from B2B marketers you've already shared your data with?" - 59% of the respondents said they trust all or a majority of such personalized content.

• "How good of a job are all B2B brands doing in general when targeting you with content and offers?" - 62% of the respondents said good or outstanding.

• "How good of a job are all B2B brands in general doing when it comes to sending content and offers at the right time?" - 64% of the respondents said good or outstanding.

The survey also identified several factors that increase or reduce buyer trust in marketing. For example, 85% of the respondents said high-quality B2B thought leadership content improves the perception of a brand. In contrast, 42% of the respondents said content that is too general reduces trust.

[Book Review] "Escape from Model Land" by Erica Thompson

Source:  Basic Books

Predictive mathematical models touch our lives virtually every day. Every weather forecast we watch, hear, or read is formulated based on multiple atmospheric models. And that's just one example.

Predictive models have also become an integral part of modern marketing. For example, marketers use mathematical models to determine the optimal mix of marketing programs (marketing mix models), identify the attributes of their best prospects, and personalize marketing communications and other forms of marketing content.

The primary function of most mathematical models in marketing is to identify patterns in existing data and then apply those patterns to predict the likely future outcomes or results of marketing decisions or programs.

The use of predictive models in marketing is poised to increase significantly because of continuing advances in artificial intelligence. If you need proof of this growth, just look at the explosion of generative AI applications since the public release of OpenAI's ChatGPT in November 2022.

All this makes it vital that marketers have a basic understanding of how mathematical models are constructed, how they work, and why they don't always produce accurate forecasts. This makes Escape from Model Land:  How Mathematical Models Can Lead Us Astray and What We Can Do About It (Basic Books, 2022) a book all marketers should read.

Escape from Model Land was written by Erica Thompson, an associate professor at University College London (UCL) and a Fellow at the London Mathematical Laboratory. Previously, she was a senior policy fellow at the Data Science Institute at The London School of Economics and Political Science. Thompson holds a PhD in physics from Imperial College.

What's In the Book

Escape from Model Land contains ten chapters. In the first six chapters, Thompson focuses on the attributes and limitations of mathematical models. She observes that people who design and build models work in a wonderful place she dubs "Model Land." In Model Land, she writes, all the assumptions that underlie a model are "literally true," and all the uncertainties are quantifiable.

The problem is that these conditions don't exist in the real world. Thompson writes, "Deep or radical uncertainty enters the scene in the form of unquantifiable unknowns:  things we left out of the calculation that we simply could not have anticipated . . . In that case, your carefully defined statistical range of projected outcomes would turn out to be completely inadequate."

Escape from Model Land discusses several other limitations of models. For example, Thompson observes that all models are oversimplifications of the real world, which means they provide an incomplete picture of reality. She writes, " We might think of models as being caricatures . . . Inevitably, they emphasize the importance of certain kinds of features . . . and ignore others completely."

Thompson also points out that a model builder makes numerous choices when developing a model - what to put in, what to leave out, what scientific and mathematical approach to take, etc. Therefore, a model will reflect the values, education, and culture of the model builder, which means that it only presents one perspective of a given situation when, in fact, several perspectives are possible.

Throughout the book, Thompson exposes the limitations and "blind spots" of predictive models, but she does not argue they should be relegated to the junk pile. Near the end of Chapter 1, Thompson includes a passage that describes the challenge she hopes the book addresses. She writes:

"I have tried to find a balanced way to proceed in between what I think are two unacceptable alternatives. Taking models literally and failing to account for the gap between Model Land and the real world is a recipe for underestimating risk and suffering the consequences of hubris. Yet throwing models away completely would lose us a lot of clearly valuable information."

Thompson uses the final chapter of Escape from Model Land to offer five suggestions for addressing this challenge.

• Define the Purpose - "As a starting point for creating models, we need to decide what purpose(s) they are supposed to be put . . . Most models are not adequate for the purpose of making any decision, although they may be adequate for the purpose of informing the decision-maker about some parts of the decision."

• Don't Say "I Don't Know" - "If we can give up on the prospect of perfect knowledge and let go of the hope of probabilistic predictions . . . there are alternative narratives in each model which in themselves contain useful insights . . . We know nothing for certain, but we do not know nothing."

• Make Value Judgements - "All models require value judgements . . . When you understand the value judgements you have made, write them down . . . Allow for representations of alternative judgements without demonising those that are different from your own."

• Write About the Real World - "When you're explaining your results to somebody else, get out of Model Land and own the results . . . in what ways is this model inadequate or misinformative? What important processes does it fail to capture?"

• Use Many Models - ". . . gathering insights from as diverse a range of perspectives as possible will help us to be maximally informed about the prospects and possibilities of the future."

My Take

Escape from Model Land is well-written, accessible, and engaging. Erica Thompson does an excellent job of making the complex, technical aspects of mathematical models easy for those of us who aren't trained data scientists to understand.

This book is not specifically about marketing, but it contains a message that is important and timely for marketers. Over the past several years, marketers have increasingly relied on data to inform their decisions, and recent advances in artificial intelligence will likely increase this reliance.

There's no doubt that data analytics and AI can help marketers make more evidence-based decisions, but these tools also have limitations that often go unrecognized - or at least underappreciated.

The apparent precision of numbers and the halo of scientific validity surrounding AI can easily create an illusion of certainty that gives us a false sense of confidence in the outputs these tools produce.

Escape from Model Land reminds us that marketing should always be "data-informed," but never totally "data-driven." 

Leverage Buyer Goals to Drive Breakthrough Marketing Results

Source:  Shutterstock

I've always been skeptical of claims that using any one technique or tactic will consistently result in superior marketing performance. Simple, "silver bullet" solutions for big, complex challenges are incredibly rare in the real world.

But, if there is one key to decoding the formula for effective marketing, it is the ability to understand how people make decisions and what drives human behavior.

Understanding what will cause a potential buyer to respond to your marketing messages and ultimately buy your product or service is a prerequisite for developing an effective marketing strategy and creating persuasive marketing messages and content.

When you can't identify the factors that underlie human decision-making and behavior, it's nearly impossible to design marketing programs that are consistently successful. It's like trying to navigate by the stars on a cloudy night. 

The good news is, you can use established principles of decision science to identify and better understand the mechanisms that drive your potential buyers' decision-making and behavior.

The Critical Role of Buyer Goals

Recent advances in decision science have established that motivation is the primary driver behind all human behavior, including buying behavior.

The American Psychological Association defines motivation as, "a person's willingness to exert physical or mental effort in pursuit of a goal or outcome." Put another way, motivation is the willingness to take action to achieve a goal. The goal may be to solve a problem, satisfy a need, or get a particular "job" done.

As humans, we pursue a goal because we expect to receive a reward if the goal is achieved. Neuroscience has shown that the human brain has a "reward system," which is a group of structures and neural pathways that are activated when our brain processes sensory inputs that signal a reward we value.

When our brain's reward system is activated, we are motivated to pursue the goal that will enable us to reap the expected reward. And the more we value the expected reward, the more motivated we become to achieve the goal.

Our goals also largely dictate what we pay attention to. Research has shown that our brain automatically scans our environment for information that aligns with our goals. So, in essence, our brain causes us to pay attention to information that is closely related to our goals.

Lastly, goals can be explicit or implicit. Explicit goals are those we set and pursue at a conscious level. An implicit goal operates primarily at a subconscious level. These goals arise out of basic human physical, psychological, and social needs, things like safety, security, and autonomy. We are motivated to pursue implicit goals even when we aren't consciously thinking about them.

Implications for Marketers

These principles of decision science have major implications for marketers. The most important lesson is that the ability of any marketing message to provoke a response from a potential buyer is determined by how closely the message aligns with the buyer's goals. That degree of "fit" is what makes the message relevant to the buyer and what will prompt him or her to respond.

This means you need to identify what the goals of your potential buyers are and then craft messages that are linked to those goals. Unfortunately, this is easier said than done for two main reasons.

First, buyer goals are highly individualistic. They can differ even among buyers who have similar demographic attributes, work in similar types of businesses, and have similar job titles and functions. Therefore, even well-constructed buyer personas may not reveal what goals are most important for an individual buyer.

Second, the goals of a business buyer can and will change as the opportunities and challenges facing the buyer's organization change. This means that a buyer who doesn't respond to a particular marketing message today might well respond to the same message received a month from now.

The challenges presented by these two factors are always present, but they are more pronounced when you're seeking to acquire new customers.

If you are properly nurturing your relationship with an existing customer, you should be well-positioned to understand what your customer's high-priority opportunities and challenges are at any point in time. And that gives you greater insight into the goals your customer's buyers are likely to have.

When you're seeking to acquire new customers, the most effective strategy is to ensure that your marketing messages feature links to one or more of the implicit goals I discussed earlier. This approach has two main advantages.

First, implicit goals are universal because they arise out of fundamental psychological and social needs that all humans share. And second, implicit goals are durable; they don't change much over time. Therefore, marketing messages linked to these goals will likely resonate with most of your buyers whenever they are used.

The bottom line is:  If you want to achieve consistent marketing success, there's no substitute for understanding your buyer's goals.

Are the 4P's Still Relevant for Today's Marketers?

Source:  Shutterstock

(The concept of the "marketing mix" has been a staple of marketing for over 70 years. It's discussed in virtually all marketing textbooks and taught in virtually all introductory marketing courses. But does the marketing mix idea still have a place in 21st-century marketing? The answer is "yes," and here's why.)

The marketing mix construct has been part of the marketing landscape for more than seven decades. The origin of the concept can be traced to 1948 when James Culliton, a marketing professor at Harvard, wrote an article in which he described the marketing executive as a "mixer of ingredients."

Culliton's article inspired Neil H. Borden, another Harvard marketing professor, who began using the phrase "marketing mix" in his teaching and writing in 1949.

Borden developed a model of the marketing mix that included 12 elements - product planning, pricing, branding, channels of distribution, personal selling, advertising, promotions, packaging, display, servicing, physical handling, and fact-finding and analysis.

In his 1960 marketing textbook, Basic Marketing:  A Managerial Approach, E. Jerome McCarthy introduced a simpler model of the marketing mix that contained only four elements - product, price, place, and promotion. McCarthy's model quickly became popular and has been so widely adopted by academics and practitioners that the "4P's of marketing" have become synonymous with the concept of the marketing mix.

Despite its popularity and longevity, the 4P's model has been criticized for several reasons. Given how much marketing has changed over the past several decades, it's legitimate to ask whether a sixty-year-old marketing mix model is still relevant. My answer to this question is an emphatic "yes," provided you keep a few things in mind. 

The 4P's Include More Than the Terms Suggest

One criticism of the 4P's is that the ingredients used in the model don't adequately capture the complexity of today's marketing environment.

The response to this criticism is that the terms used in the model should be viewed as flexible category labels that can encompass more than the literal or common meanings of the words would suggest. For example:

• Product - The "product" element can be used for both products and services, and for complex "solutions" that consist of multiple products and services. In essence, this element can refer to whatever a company sells.

• Price - This element can encompass any type of price and virtually every aspect of pricing strategy - for example, cost-plus vs. market-based vs. value-based pricing, premium vs. discount pricing, unit pricing, subscription-based pricing, and pay-for-performance pricing.

• Place - "Place" can encompass any method or channel of distribution a company is (or could be) using. Importantly, place can also encompass distribution via the cloud.

• Promotion - This element is intended to encompass all of the ways a company can communicate with its customers and potential buyers. This would include all online and offline "marketing" communication channels and tactics, and personal selling, but it would also encompass communications that are "non-promotional," such as customer service and customer success communications.

The 4P's Describe Factors Marketers Can Manipulate and Control, Not What They Must Achieve

Another criticism of the 4P's model is that it focuses on the decisions and actions of the selling company, but doesn't address what is required to be successful with customers. This criticism is factually accurate, but that doesn't mean the model is flawed. It simply means the model was never designed to prescribe what will be effective with customers.

The 4P's model is like a list of available ingredients a chef can use to prepare a variety of dishes in a variety of ways, but it doesn't provide recipes for specific dishes that diners are guaranteed to like. It's up to marketers to decide what specific ingredients will produce a "meal" that will appeal to their target buyers.

To make these decisions wisely, marketers will need to use other methods and tools to identify the needs and preferences of their potential buyers. It's noteworthy that, in his marketing textbook, E. Jerome McCarthy did not discuss the 4P's model until after he had explained the importance of understanding the needs and attributes of the potential customers in the selling company's target market.

The Marketing Mix Concept Is Still Relevant

Even if you think the 4P's model is outdated, it's important to recognize that the basic idea of marketing leaders as "mixers of ingredients" is even more valid today than it was when it was introduced more than 70 years ago.

Regardless of company size, the resources available for marketing are rarely sufficient to enable marketing leaders to do everything they'd like to do. Deciding how and where to invest finite marketing resources has never been easy, but these decisions have become more complex because today's marketing leaders have more options than ever.

The challenge facing marketing leaders is to use their finite resources to implement the combination of marketing activities and programs that will produce maximum results. Therefore, the task of a marketing leader is similar to that of a professional money manager.

The job of an investment manager is to construct a portfolio of investments that will produce the highest risk-adjusted rate of return. In today's environment, as in the past, a primary job of a marketing leader is to construct a portfolio of marketing activities and programs that will maximize the return on marketing resources.

So, James Culliton's 76-year-old description of marketing executives as "mixers of ingredients" is still accurate.

[Research Round-Up] AI vs. Humans - Round 1

Source:  Shutterstock

(This year, I plan to devote some of my Research Round-Up posts to a discussion of academic research papers about artificial intelligence. Some of these scientific papers will likely focus on comparing the capabilities of AI to those of humans at performing tasks related to marketing. This month's Research Round-Up features an unpublished paper that compares the performance of AI vs. humans at generating ideas for new products.)

"Ideas are Dimes a Dozen:  Large Language Models for Idea Generation in Innovation"

• Authors - Karan Girotra, Cornell Tech and Johnson College of Business, Cornell University; Lennart Meincke, Christian Terwiesch, and Karl T. Ulrich, The Wharton School, University of Pennsylvania

• Date Written - July 10, 2023

This paper describes the results of an experiment designed to compare the performance of generative AI and humans at producing ideas for new consumer products.

The task used in the experiment was to generate ideas for a new product for the college student market that would sell at retail for less than $50. The AI application used in the experiment was OpenAI's ChatGPT-4.

The experiment used three "pools" of new product ideas.

• First pool (200 ideas) - Ideas created without AI assistance by students enrolled in a product design course at an elite university.

• Second pool (100 ideas) - Ideas generated by ChatGPT based on the same "prompt" as that given to the students.

• Third pool (100 ideas) - Ideas generated by ChatGPT based on the same prompt and a sample of highly-rated product ideas. 

All 400 product ideas were evaluated by a panel of college-age individuals in the United States. The quality of the product ideas was based on purchase intent. Panel members expressed their purchase intent by selecting one of five options - definitely would not purchase, probably would not purchase, might or might not purchase, probably would purchase, or definitely would purchase.

The Results

The average quality of the product ideas produced by ChatGPT was higher than the average quality of the human-generated ideas. The average purchase probability of a human-produced idea was 40.4%, while the average for a ChatGPT idea (without examples) was 46.8%, and the average with examples was 49.3%.

Of the 40 highest-rated ideas in the experiment, 35 (87.5%) were ideas produced by ChatGPT.

The researchers also asked members of the evaluating panel to rate the novelty of the new product ideas. In this experiment, the mean novelty value of the human-generated ideas was higher than that of the ideas generated by ChatGPT. However, the researchers noted that novelty did not appear to be significantly correlated with purchase intent.

Implications for Marketers

The Girotra et al. paper has important implications for marketers because it adds to our understanding of the capabilities of AI applications like ChatGPT.

The results of the experiment described in the paper are similar to the findings of other recent research, including an experiment conducted by Boston Consulting Group (GCG) and scholars from four elite universities. I described this study in a post I wrote last fall.

In the BCG study, participants were tasked to generate ideas for a new shoe for an underserved market. They were also required to develop a list of the steps needed to launch the product, create marketing slogans, and write a press release for the product. The researchers found that participants who used an AI tool to complete the tasks outperformed those who didn't by 40%.

The results of these studies suggest that AI tools based on large language models may be better than humans at performing "brainstorming-like" tasks where the objective is to generate a large number of diverse ideas relating to a topic.

This result should not be that surprising. Large language models are trained on a voluminous amount of data from incredibly diverse sources. The ability to generate responses based on such a vast repository of training data enables an AI tool like ChatGPT to excel at brainstorming-like tasks.

For marketers, the findings described in the Girotra et al. paper and similar findings in other studies suggest that AI tools powered by large language models can be particularly well suited to perform content ideation tasks such as generating potential topics for blog posts or producing potential social media posts.

[Book Review] An Authoritative Road Map To High-Impact Content Marketing

Source:  Kogan Page

Last November, I published a review of Robert Rose's new book, Content Marketing Strategy. Rose's book is one of the best I've recently read, and it's an important addition to our library of content marketing literature. If you haven't read Content Marketing Strategy, I recommend that you add it to your reading list for 2024.

Shortly after I finished Rose's book, I discovered and read Purna Virji's new book, High-Impact Content Marketing:  Strategies to Make Your Content Intentional, Engaging and Effective (Kogan Page, 2023). This is also an excellent book, and I enthusiastically recommend it.

Purna Virji is a globally recognized content strategist and marketer whose work has been featured in The Drum, Marketing Land, Adweek, and other publications. She is currently Principal Consultant, Content Solutions at LinkedIn, and before joining LinkedIn, she was Senior Manager of Global Engagement at Microsoft.

What's In the Book

High-Impact Content Marketing contains 12 chapters that are packed with strategies, insights, and frameworks designed to enable marketers to conceive and produce intentional, engaging, and effective content.

Purna Virji uses the first two chapters of the book to explain why many content marketing efforts produce underwhelming results and to describe the essential building blocks of long-term content marketing success. These two chapters are particularly important because they reveal the perspective that Virji brings to the material in the balance of the book.

In Chapter 01, she argues that marketers struggle to achieve success with content marketing because they often get five basic choices wrong.

1. Focusing on outputs vs. outcomes (a/k/a content quantity vs. business results)
2. Chasing trends vs. being grounded in strategy
3. Prioritizing short-term vs. longer-term
4. Creating for machines vs. humans
5. Not balancing creation vs. distribution

Virji uses Chapter 02 to discuss what she calls the "four essential element pairs" of long-term content marketing success.

1. Behavioral science and learning design
2. Empathy and inclusion
3. Copywriting and selling skills
4. Strategy and measurement

The balance of High-Impact Content Marketing covers several topics that Virji argues are critical for the development of a high-impact content marketing program. These include:

• Needs analysis (internal and customer) - Chapters 03-05
• Competitor content audit - Chapter 06
• Content marketing strategy and measurement - Chapter 07
• Copywriting strategy - Chapter 11
• Content distribution techniques - Chapter 12

Virji also includes two chapters that explain how to use brainstorming to come up with high-impact content ideas.

My Take

High-Impact Content Marketing is an excellent book that should be considered required reading for anyone involved in content marketing. The book is well organized and well written, and Virji includes numerous real-world examples, which make the book more engaging and relatable.

She also provides several practical tips and frameworks in the book, which will enable readers to more easily apply the principles and techniques she discusses.

One particularly valuable aspect of the book is that Virji includes a discussion of "instructional design" principles and explains how content marketers can leverage those principles to create more effective content.

At the beginning of this review, I mentioned Robert Rose's new book, Content Marketing Strategy, and I noted that it is one of the best content marketing books that I've recently read. Rose's book and High-Impact Content Marketing address different aspects of content marketing, but these books are highly complementary.

Purna Virji's book provides a road map for creating effective content, while the primary focus of Rose's book is the organizational structures and processes that are needed to effectively manage a content marketing function. By applying the principles described in both books, marketers will greatly increase their odds of achieving content marketing success.

So, the bottom line is:  If you're involved in content marketing - and especially if you're responsible for leading your company's content marketing efforts - you need to read both of these valuable books.