Sunday, February 25, 2024

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).

Sunday, February 18, 2024

[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."
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.

Sunday, February 11, 2024

[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." 

Sunday, February 4, 2024

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.