Why B2B Marketers Need to Care About "Opportunistic Learning"

One of the most profound developments in B2B marketing of the past two decades has been the emergence of empowered and independent buyers. When I launched this blog in 2010, my second post was about "The Age of the Self-Directed Buyer."

The explosive proliferation of readily available information has been the driving force behind this development. Because of easy access to a wealth of information about almost every conceivable topic, business decision-makers now believe they can find whatever information they want or need, whenever they want or need it, on their terms.

Information abundance has altered many aspects of how B2B buying decisions are made, and B2B marketers have done a reasonably good job of adapting to most of those changes. There is, however, one impact of information abundance that has been (and still is) underappreciated.

The Rise of Opportunistic Learning  

Most models of the B2B buying process assume the process begins when a company's leaders or managers recognize a need or a problem and decide to address the issue in some way.

These "buyers" then gather information about the need or problem and possible solutions, evaluate the available options, and may or may not decide to purchase a product or service to address the situation.

So, the conventional view of B2B buying behavior is that most information gathering occurs after an intentional buying process has started. While this view may still be accurate in a strictly quantitative sense, it misses an important aspect of B2B buying.

Information is now so abundant and readily available that business people are routinely consuming information about business issues long before they have formed anything close to "buying intent," and long before they have started an intentional buying process.

I call this type of information-gathering opportunistic learning, and it occurs because humans are naturally programmed to seek rewards. We all have a mental radar system that constantly scans our environment to identify reward opportunities.

In a business setting, our radar system is always scanning our environment to identify information that may help us improve our company's performance and/or advance our professional careers.

The growth of opportunistic learning has important implications for B2B marketing, but some marketers haven't fully appreciated its significance.

Most B2B marketing tactics and programs are designed to identify and reach people who are ready to begin a buying process or to encourage those already involved in a buying process to move toward a buying decision. At any time, however, most of the people affiliated with potential customers are more likely to be opportunistic learners than true buyers.

Engaging with opportunistic learners is important because the impressions they form during opportunistic learning remain influential when they become involved in a buying process. Therefore, if marketers can create and sustain positive relationships with opportunistic learners, their company will have a competitive advantage when those opportunistic learners turn into buyers.

How to Successfully Engage with Opportunistic Learners

Antonia Wade, the Global Chief Marketing Officer of PwC, has offered a compelling perspective on how B2B marketers can successfully engage with opportunistic learners.

In her recent book, Transforming the B2B Buyer Journey (Kogan Page Limited, 2023), Ms. Wade proposes a new B2B buyer journey "framework" that contains five phases - Horizon Scanner, Explorer, Hunter, Active Buyer, and Client. Her names for these phases symbolize the buyer's needs and thought processes that are important during each journey phase.

Ms. Wade's Horizon Scanner phase is similar in several ways to what I have called opportunistic learning. In her book, she writes that Horizon Scanners are people in strategic roles who are always assessing how big market trends and innovation will impact their business. Horizon Scanners, Wade writes, ". . . aren't looking for answers and they're certainly not looking for a sales message; they're looking for ideas."

Ms. Wade makes two major points about successfully engaging Horizon Scanners. First, she argues that high-quality thought leadership content is critically important. Wade contends that compelling thought leadership is what earns your company a seat at the table in the later stages of the buying process.

Second, and equally important, Ms. Wade argues that most Horizon Scanners tend to seek information from respected and trusted sources. Therefore, she contends, your thought leadership content needs to be available in channels you don't own, such as third-party publications or events. This also means, she argues, that public relations plays an important role in reaching Horizon Scanners.

The Takeaway

Whether you call these individuals "Horizon Scanners" or "opportunistic learners," it's vital to remember they are not yet "buyers," and they shouldn't be treated like decision-makers who are engaged in an intentional buying process. Your goal with these individuals is to position your company as an expert and a reliable authority, while also making your company memorable.

Illustration courtesy of Naval Surface Warriors via Flickr (CC).

Don't Put All Your Faith in Marketing Best Practices

 

Nearly three decades ago, Michael Porter warned us about the dangers of relying on benchmarking and "best practices" to produce business success. In a landmark Harvard Business Review article, Porter drew a sharp distinction between operational effectiveness - which often involves identifying and implementing best practices - and real business strategy.

Porter argued that competing primarily on the basis of operational effectiveness is usually a recipe for disaster. He wrote:  "The more benchmarking companies do, the more they look alike . . . As rivals imitate one another's improvements in quality, cycle times, or supplier partnerships, strategies converge and competition becomes a series of races down identical paths that no one can win."

Four years after Porter's article, Philipp Nattermann made a similar argument in an article for the McKinsey Quarterly. In his article, Nattermann contended that benchmarking and the use of best practices are important ways to improve operational efficiency, but they are not tools for strategic decision-making. He wrote that business leaders rely too much on benchmarking and best practices because:

". . . they don't understand that benchmarking is simply an operational tool. Instead, they all want to occupy the point on the strategic landscape that their most successful competitor has staked out. Soon other competitors can be seen herding, lemminglike, around that best practice company's product, pricing, and channel strategies. Products and services become increasingly commoditized and margins tumble as more and more incumbents compete for smaller and smaller segments of customers and industry resources."

Despite these warnings, business leaders continue to regard identifying and implementing best practices as one of the most powerful management tools at their disposal. And it's not difficult to understand why. It seems imminently reasonable to identify what high-performing companies are doing and then emulate those practices.

The Allure of Marketing Best Practices

Marketers can become particularly enamored with best practices. After all, marketing success is difficult to achieve and even harder to sustain because the marketing landscape is always changing, and because it's tough to predict what marketing methods, channels, and messages will appeal to potential customers. In these circumstances, it shouldn't be surprising that marketers are attracted to "proven" best practices.

Marketers are also strongly attracted to new marketing channels and methods. They tend to believe that constant innovation is essential for marketing success. As a result, most marketers tend to equate "new" practices with "best" practices, at least when the new practices appear to be performing well at other companies.

Most marketing best practices come with an explicit or implicit claim:  Use this channel or tactic and your marketing performance will improve significantly. However, the reality is rarely that simple.

A marketing best practice typically addresses one aspect of marketing, while marketing success usually results from the combined effect of numerous factors. Therefore, best practices don't provide a formula that will automatically guarantee marketing success. Unfortunately, it's easy for marketers to become enthralled with the promised benefits of best practices and lose sight of their limitations.

Marketers need to be particularly aware of two limiting attributes of marketing best practices.

Best Practices Results Aren't Always Transferable 

As I noted earlier, marketing success is usually due to several factors. Therefore, the results produced by a best practice are highly dependent on the context in which it's used.

Suppose, for example, that you attend a marketing conference, and you hear several speakers rave about the fantastic results they're getting from using a specific marketing tactic, say short-form video. You can't assume that short-form video will automatically produce similar results for your company. Your results will depend on several factors that are unique to your company.

Widespread Use Decreases Effectiveness

One of the most paradoxical characteristics of marketing best practices is that the more widely they are used, the less effective they tend to become. 

Marketing best practices can be effective - at least for a while -  because they are distinctive. When a marketing practice is new, it is used by a relatively small number of companies. Therefore, the practice stands out in the marketplace and captures the attention of potential customers. But as more and more companies implement the practice, it loses some of the distinctiveness that made it effective. Content marketing is a good example of a marketing best practice that has become more challenging because it is so widely used.

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I'm not suggesting that marketing best practices have no value. What I am suggesting is that the implementation of marketing best practices isn't a sure-fire, can't-miss recipe for success.

Image courtesy of Paul Mison via Flickr (CC).

[Research Round-Up] Generative AI Has a Substantial Impact on Creative Jobs

Source:  Shutterstock

(This year, I'm devoting some of my Research Round-Up posts to a discussion of academic research papers relating to the use of artificial intelligence - specifically generative AI applications - in marketing. This post features an unpublished paper that provides an early look at the impact generative AI may have on marketing employment.)

The potential impact of generative artificial intelligence on the number of marketing jobs has been vigorously discussed in marketing circles since the public debut of ChatGPT in November 2022.

Some marketing thought leaders have argued that the capabilities of generative AI applications are advancing so rapidly that it's almost inevitable some marketing jobs will be eliminated.

Other commentators maintain that AI applications cannot possess the emotional intelligence required to create marketing content that will be effective with potential buyers, and therefore human marketers will always be needed.

One of my go-to resources for anything relating to artificial intelligence is Christopher Penn, the co-founder and chief data scientist at Trust Insights. Penn says that some companies will see the improved productivity created by AI as an opportunity to reduce costs, and they will eliminate marketing jobs that become "unnecessary." Other companies will view the increased productivity as an opportunity to expand the capabilities of their marketing function, and they will have their human marketers take on new tasks.

The reality is that it's impossible to know with certainty what impact AI will have on the overall number of marketing jobs. However, a recent paper by three academic researchers provides an early indication of what the impact of AI might look like.

Here are the paper's details:

• Title - "Who Is AI Replacing? The Impact of Generative AI on Online Freelancing Platforms" 

• Authors - Ozge Demirci, Harvard Business School; Jonas Hannane, German Institute for Economic Research (DIW Berlin) and Technische Universitat Berlin; and Xinrong Zhu, Imperial College London Business School

• Date Written - October 15, 2023

Study Objectives and Methods

This paper describes the results of an analysis of job posts on a leading global online freelancing platform. The objective of the analysis was to identify the short-term impact of generative AI applications on the demand for freelance jobs in online labor markets.

The analysis included a total of 1,388,711 job posts that appeared on the freelancing platform from July 2021 to July 2023. So, the analysis period included approximately 17 months before, and about eight months after, the public release of ChatGPT.

The authors used a clustering algorithm to identify clusters of skills that frequently appeared together in job posts. Then they mapped each job post to the cluster with the greatest similarity in skills. This enabled the researchers to place the job posts in a manageable number of groups by type of job.

The authors focused their analysis on eight of the most prevalent types of jobs, which they grouped into three broad categories.

• Manual intensive jobs - those that require a large proportion of manual tasks

• Automation prone jobs - those involving tasks that are susceptible to digitalization or automation

• Image generating jobs - those that primarily involve the creation of visual content and 3D models

The final breakdown of jobs included in the analysis was:

• Manual intensive jobs
• Data and office management
• Video Services
• Audio services

• Automation prone jobs
• Writing
• Software, app, and web development
• Engineering

• Image generating jobs
• Graphic design
• 3D modeling

Writing and graphic design jobs are primarily marketing jobs, and the analysis revealed that generative AI applications had a substantial impact on the demand for those jobs.

The researchers found that the demand for writing jobs decreased by 30.37% more than the demand for manual intensive jobs within eight months after the public release of ChatGPT. The analysis also revealed that the release of AI text-to-image generators (such as Midjourney, Stable Diffusion, and DALL-E) led to an 18.49% decrease in the number of job posts for graphic design services, relative to manual intensive jobs.

Caveat

This paper provides an interesting perspective regarding the potential impact of generative AI applications on marketing employment, but I would be surprised if the findings described in the paper extend much beyond the freelance market.

I tend to agree with Christopher Penn that some companies will take advantage of generative AI efficiencies to cut costs, while others will use generative AI as a lever of growth.

Why You Should Think Beyond Surveys for Original Research

 

In my last post, I described where B2B marketers should look when attempting to find topics for thought leadership content. There's no longer any doubt that high-quality thought leadership content has become a critical component of effective marketing at many B2B companies.

Numerous research studies have identified the characteristics that make thought leadership content persuasive. The terms used in those studies vary, but the research consistently shows that compelling thought leadership content will exhibit three core attributes - it will be relevant, authoritative, and novel.

The need to make thought leadership content both novel and authoritative raises the importance of original research. In reality, the only way to develop novel and authoritative thought leadership content is to base that content on original research.

Original research is required to capture the new information and develop the new insights that make thought leadership content novel, and it provides the evidence that makes the content authoritative.

Original Research Means More Than Surveys

When most marketers think about original research, surveys are usually the first thing that comes to mind. Surveys are popular because they can provide valuable data and because they have become easier and less expensive to use. Several firms now offer free or inexpensive tools for conducting surveys.

It's important to recognize, however, that original research encompasses more than quantitative surveys, and that other types of original research can also be highly effective.

The following diagram shows the major categories of original research and the research methods that fall in each category.

As the diagram shows, there are two major categories of original research - primary research and secondary research. Secondary research involves reviewing and analyzing data or research that has been published by others. This includes data published by governmental entities, and data or research published within academia and by private organizations such as consulting firms and research firms.

Primary research, on the other hand, is research you conduct yourself or hire someone to conduct for you. It involves going directly to a source to gather or compile information. The diagram shows several of the most common methods of primary research, all of which can be effective when used in the right circumstances.

Interviews and Focus Groups                                         Interviews can be used on a stand-alone basis or in conjunction with other primary research methods. The major advantage of interviews is that they enable the use of open-ended questions and therefore can produce more in-depth and nuanced answers.

When used on a stand-alone basis, the interviewees essentially take the place of a survey panel. In my experience, however, one of the best ways to use interviews is as a preliminary step in a research project that will ultimately include a survey. In this case, the interviews are used to identify the topics that may be important to survey participants and to help formulate survey questions.

A focus group is essentially a group interview, and therefore focus groups can be used in most of the same ways as individual interviews.

Analysis of Proprietary Data                                                     This method involves the analysis of data that is proprietary to your company. For example, if your company provides a hosted or SaaS software application, this research method could be used to compile and analyze data regarding how your customers are using the application.

A good example of research featuring this method is the annual state of B2B content consumption and demand study produced by NetLine Corporation.

Experiments or Tests                                                                This research method is widely used in social sciences such as psychology and behavioral economics. When you conduct an experiment, you expose participants to alternative versions of a hypothetical situation, and then ask them questions about their experience or record their behaviors. The objective is usually to measure differences in certain aspects of the alternatives.

A field test is similar to an experiment except that the alternatives are presented in a real-world setting. An "A/B test" is a type of field experiment used frequently in marketing.

Expand Your Research Palette

Don't misunderstand my point here. Surveys will always be an important and valuable method of conducting primary research. However, diversifying the research methods you use can have several benefits. Each research method has strengths and weaknesses, and each excels at eliciting certain kinds of information. By using a variety of research methods, you will be better able to produce thought leadership content that is novel and authoritative. And that will make your marketing more effective.

Top image courtesy of U.S. Army DEVCOM via Flickr (CC).