Sunday, March 24, 2019

The Benefits and Limitations of Look-Alike Modeling


Demand Gen Report recently published a white paper describing the benefits of using look-alike modeling powered by artificial intelligence (AI) to improve lead generation performance. The white paper argues that B2B marketers can use "AI-fueled" look-alike modeling to get more qualified leads that convert at higher rates.

The principles underlying look-alike modeling aren't new. For years, astute B2B marketers have been identifying important attributes of their best existing customers and using those attributes to create a profile of their "ideal prospect." Then, they would use this ideal prospect profile to identify target audiences for outbound lead generation programs and otherwise guide lead generation efforts.

The current incarnation of look-alike modeling does essentially the same thing, but in a more sophisticated way using AI-powered data analytics.

Several technology providers now offer solutions that include or support look-alike modeling, and most of these solutions take similar approaches to the look-alike modeling process.

  • They extract data regarding a company's existing customers from the company's internal technology systems including, but not necessarily limited to, the CRM and marketing automation solutions.
  • Most solution providers have developed or obtained access to extensive databases regarding business organizations. The modeling solution will combine the company's internal customer data with any additional data regarding these customers in the provider's database. This enables the solution to create a more detailed picture of the attributes of the company's existing customers.
  • The modeling solution then uses an algorithm to analyze the combination of internal and external customer data to identify the attributes that the company's existing customers have in common. The result of this analysis is usually called a customer data model.
  • The solution then runs the company's customer data model against the provider's database of businesses to identify companies that resemble the model.
The major advantage of AI-powered look-alike modeling is that it incorporates far more data points than humans can realistically use when the process is done manually. Therefore, AI-powered modeling enables marketers to build a richer and deeper customer data model, and it does a better job of identifying companies that are likely to be good prospects.
Look-alike modeling can be an effective tool for improving B2B demand generation performance, but like any business tool or methodology, it has some limitations.
First, for look-alike modeling to be effective, a company needs to have enough existing customers to build a customer data model that's reliably predictive. One provider of look-alike modeling has indicated that a company needs at least 500 existing customers to build a reliable model. While 500 may not the the absolute minimum, effective look-alike modeling does require a company to have a substantial number of existing customers, and a start-up or young business may not be able to meet this requirement.
Second, look-alike modeling can be less effective when a company is marketing new products or services. If a new product or service appeals to a different type of customer than the company's other products or services, a customer data model based on the company's existing customers may not identify the right prospects for the new product or service.
The important point here is that look-alike modeling is a powerful tool for improving demand generation performance, particularly when it's enhanced with artificial intelligence. But B2B marketers should also remember that like any business methodology, look-alike modeling has a few important limitations.
Image Source:  Flickr.com

Sunday, March 17, 2019

B2B Highlights From the Latest CMO Survey


The findings of the latest CMO Survey by Duke University's Fuqua School of Business, the American Marketing Association, and Deloitte were published a few days ago. The latest results are based on responses from 323 marketing leaders at U.S. B2B and B2C companies. Sixty-eight percent of the respondents were affiliated with B2B companies, and 97% were at VP-level or above.

The CMO Survey is conducted semi-annually, and it's a valuable resource for capturing the views of U.S. marketing leaders regarding the overall economic and competitive environment, and major trends in marketing. In addition to overall results, survey findings are reported by four economic sectors - B2B product companies, B2B services companies, B2C product companies, and B2C services companies.

In this post, I'll discuss some of the major findings in the February 2019 edition of survey. Unless otherwise indicated, the results discussed in this post are based exclusively on the responses of B2B marketers.

Driving Growth is the #1 Challenge

Driving business growth has become the top challenge for marketing leaders in all types of businesses. The CMO Survey asked participants to rank their three biggest challenges in order of importance. The following table shows the top four challenges identified by the entire survey panel and by B2B respondents. The table shows the percentage of respondents who ranked each challenge first in importance.











Measuring Marketing Impact Remains Challenging

Demonstrating the financial impact of marketing activities remains a significant challenge for many marketers. As the above table shows, surveyed marketing leaders identified proving ROI of marketing activities as their fourth highest rated challenge.

The CMO Survey also asked marketing leaders how they demonstrate the long-term impact of marketing spending, and the following table shows how B2B marketers responded.










As this table shows, only 35.4% of respondents from B2B services companies, and 24.0% of respondents from B2B product companies say they can prove the long-term impact of marketing quantitatively.

Given these findings, it shouldn't be surprising that B2B marketers ranked marketing impact as their top C-suite communication challenge. Seventy-three percent of respondents from B2B services companies, and 67.3% of respondents from B2B product companies said demonstrating the impact of marketing actions on financial outcomes is challenging when they are communicating with other C-level executives.

Mixed Signals on Marketing Analytics and AI

Analytics, artificial intelligence, and machine learning have been hot topics in B2B marketing circles for the past few years. The findings of The CMO Survey provide important insights about several aspects of these topics.

B2B marketers expect to increase their spending on marketing analytics over the next few years. Respondents from B2B product companies said they are currently spending 6.6% of their marketing budget on analytics, and they expect the percentage to increase to 11.6% over the next three years. Respondents from B2B services companies currently devote 7.3% of their budget to analytics, and they expect the percentage to grow to 13.3% by 2022.

The CMO Survey findings also show that despite their commitment to analytics, B2B marketers don't believe that analytics currently have a big impact on company performance. On a 7-point scale (where 1 = no impact, and 7 = a high impact), respondents from B2B product companies gave analytics a rating of 3.7, and respondents from B2B services companies rated the impact of analytics at 3.8.

The survey also found that the use of artificial intelligence in B2B companies is still relatively limited. The survey asked B2B marketers how they are using AI in their marketing activities. The following table shows the top six activities identified by B2B survey respondents.















As the table shows, a majority of B2B marketers report using artificial intelligence for content personalization, and about half say they are using AI to gain customer insights. Less than 40% of marketers are using AI for most of the remaining activities.

Top image source:  The CMO Survey (www.cmosurvey.org).

Sunday, March 10, 2019

What's Required for Effective Demand Generation


CSO Insights (a division of Miller Heiman Group) recently published its 2018-2019 Sales Performance Report. This report describes the findings of the 2018-2019 sales performance survey, which generated responses from nearly 900 global sales leaders.

Sixty-one percent of the respondents were either executive managers or senior sales managers, and respondents represented 23 industries. Half of the respondents (50.8%) were located in North America, and the balance were based in EMEA, APAC, and Latin America.

The CSO Insights study focused specifically on the performance of the sales function, but the survey findings provide valuable insights for everyone involved with B2B demand generation. That's because many of the factors that characterize successful sales performance also apply to the other business functions that play important roles in demand generation.

The Defining Attributes of High Performance

CSO Insights identified three defining attributes of high-performing sales organizations. The study found that respondents from top-performing organizations were more likely than other respondents:

  • To say their company has a customer-centric culture
  • To report they have a high level of alignment between their sales process and customers' decision-making journey
  • To say they are confident in the ability of their sales reps to provide valuable insights and perspectives to potential buyers
These characteristics can be extended and applied to the other business functions involved in demand generation. For example, a marketing organization that excels at demand generation is more likely to:
  • Be part of a company with a customer-centric culture
  • Align its programs and messaging with the customer buying journey
  • Create and use content that provides valuable insights to potential buyers
The authors of the survey report acknowledge this point when they write:  "Looking at all three of these characteristics together shows that . . . [high-performing] organizations are embracing 'customer experience' as a broad concept, of which sales process and salespeople are just one piece."

Lead Generation Needs Significant Improvement
The CSO Insights research highlights several areas where better cross-functional collaboration is needed to improve demand generation performance. One of those areas is lead generation. Survey respondents identified improving lead generation as one of their four primary objectives for the coming 12 months, and they also identified the inability to generate enough qualified leads as the second most significant barrier to achieving demand generation success.
Unfortunately, the CSO Insights report reveals a distressing lack of alignment between sales and marketing when it comes to lead generation. For example, only 29.5% of the survey respondents said their sales and marketing teams have an agreed upon, formal definition of who is a legitimate sales lead. And the level of lead definition alignment between sales and marketing has actually gotten worse since 2014, as the following chart shows.














The low level of sales-marketing alignment also shows up in lead nurturing. Only 33.9% of the survey respondents said their sales and marketing teams have an agreed upon, formal process for nurturing leads. Another 30.8% said they have an informal process - whatever that means.
The CSO Insights research provides more compelling evidence that effective B2B demand generation requires a coordinated effort by both sales and marketing, and that sales-marketing alignment is still very much a work-in-progress.

Top Image Source:  CSO Insights (a Division of Miller Heiman Group).

Sunday, March 3, 2019

Where Customer Experience Stands in 2019


Two recently-published reports paint a decidedly mixed picture of the current state of customer experience (CX) management. Most business leaders now recognize that providing great customer experiences is a critical source of competitive advantage and a primary driver of business performance. So these two reports provide an important snapshot of how far companies have come in their efforts to improve customer experiences.

Forrester's Predictions 2019

In its Predictions 2019 report, Forrester observed that CX performance has been flat for three consecutive years. The report stated that in Forrester's Customer Experience Index research, ". . . few businesses made real gains, most continue to plateau, and some fell back."

Forrester also noted that 89% of surveyed CX professionals do not believe that the ROI of customer experience is well established in their companies. As a result, Forrester predicts that 20% of companies will abandon strategic CX initiatives in 2019 and turn to price reductions to secure short-term gains.

Forrester's report describes the outlook for customer experience management in 2019 in somewhat pessimistic terms:  "There is a strategic and structural mismatch between what CX needs to do and what CX is allowed to do or is capable of doing. 2019 will see that mismatch continue to play out."

The 2019 Global Customer Experience Benchmarking Report

The 2019 Global Customer Experience Benchmarking Report by Dimension Data provides detailed insights about the state of CX around the world. This report was based on a global survey of customer experience professionals that produced 1,114 responses. Respondents were located in 59 countries across the Americas, Asia Pacific, Europe, Australia and New Zealand, and the Middle East and Africa.

I found the overall tone of this report to be fairly pessimistic, but when I reviewed the specific survey findings, I thought they painted a somewhat more optimistic - or at least a more balanced - picture.

For example, there is a broad consensus about the importance of customer experience. Almost nine out of ten of the survey respondents (88.3%) said their organization views customer experience as a competitive differentiator.

The research also found that most companies have a defined customer experience strategy, although only a small minority of companies are measuring the ROI of their CX efforts.

  • 36.3% of the respondents said they have a "high level" CX strategy that is aligned to brand positioning
  • 30.9% said a CX strategy exists and is recognized as crucial to organizational strategy
  • 13.3% said a clear CX strategy exists and its ROI/value is defined and measured
  • Only 19.5% of the respondents said they have no formal CX strategy
More than three out of four of the survey respondents (76.7%) indicated they were fairly or very satisfied with their current customer experience capabilities, although only 10.3% said they were very satisfied. Perhaps more important, more than three-fourths of the respondents (77.1%) said their customers would rate their company's CX capabilities as 6 or higher on a 10-point scale (where 0 = poor, and 10 = excellent).
The Dimension Data research also revealed some additional areas of concern. For example, 29.5% of respondents said customer experience is seen as relevant in some business functions only, and that there is no organization-wide ownership of CX. Another 23.9% said CX is owned by individual business functions that are supported by a central CX team.
As I noted earlier, most respondents to this survey said they have some form of a company-wide CX strategy. So it appears that many companies are still leaving the execution of that strategy to individual business functions. This approach can easily produce CX efforts that are not tightly coordinated, and it can also result in customer experiences that are not completely consistent.
Overall, the Dimension Data research indicates that many companies have made substantial progress on CX, but it also shows that more work is needed to deliver consistently great customer experiences.

Image courtesy of frontriver via Flickr CC.

Sunday, February 24, 2019

Don't Rely Too Much on Marketing Best Practices


More than two decades ago, Michael Porter warned about the dangers of relying on benchmarking and "best practices" to produce business success. In a landmark article in the Harvard Business Review, 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 this 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 they 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 the risks associated with best practices, business leaders continue to regard the identification and implementation of best practices as one of the most powerful management tools at their disposal. And it's not difficult to understand why the use of best practices remains so popular. It seems immanently reasonable to identify the practices of successful, high-performing companies 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 incredibly hard to predict what marketing methods, channels, and message formats will appeal to potential customers. In these circumstances, it shouldn't be surprising that marketers are attracted to "proven" best practices.

Marketing best practices are often portrayed as effective and reliable tools for achieving marketing success, but the reality is more nuanced. Marketing best practices can be helpful when they are understood correctly and used appropriately, but it's easy for marketers to become enthralled with the promised benefits of best practices, and forget their limitations.

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. A marketing best practice can derive its effectiveness from several sources. It can be effective because it's based on sound business principles, or because it resonates with how potential customers make decisions, or because it effectively leverages the capabilities of a particular medium of communication.

But marketing best practices are also highly effective - at least for a while -  because they are distinctive. When a best practice is new, it tends to be 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 highly effective. Content marketing is a good example of a marketing best practice that is now more challenging because it is so widely used.

The bottom line is, identifying and implementing marketing best practices may lead to a temporary improvement in marketing results, but it won't deliver superior marketing performance over the long term. Superior long-term marketing performance requires an effective marketing strategy and the use of marketing methods and tactics that will make your company distinctive in the marketplace.

Image courtesy of Paul Mison via Flickr CC.

Sunday, February 17, 2019

ABM Supports (But Doesn't Create) Better Sales-Marketing Alignment


Some pundits contend that account-based marketing will create better alignment between marketing and sales. In reality, ABM can be a catalyst for improving sales-marketing alignment, but it won't cause such improved alignment to magically materialize. The adoption of ABM will quickly uncover weaknesses in the relationship between your marketing and sales teams, and that's a good thing. Here's why.

One of the key requirements for successful account-based marketing is coordinated efforts by business functions that have historically operated more or less independently. The need for teamwork routinely involves marketing, business development, and sales, and when ABM is used to expand relationships with existing customers, it will also extend to the customer success/customer service functions.

To reap the maximum benefits from ABM, marketing, business development, and sales must jointly develop an engagement plan for each target account. This account plan will usually span several weeks to several months, and will likely include activities by all three functions that must be closely coordinated. In addition, these business functions must be ready to make on-the-fly adjustments to the account plan based on actual buyer responses and changing business conditions at each account.

Therefore, successful ABM requires multiple business functions to work collaboratively on an ongoing basis. This level of coordination is challenging for many companies because it represents a major change in how they have traditionally engaged and managed sales leads.

In many B2B companies, the demand generation process involves a series of "hand-offs" from one business function to another. In essence, the process assumes that marketing, business development, and sales will engage potential buyers sequentially. The metaphor often used is a relay race in which each member of the relay team runs for a specified distance, and then passes the baton to the next runner.

The relay race approach has never been the best way to manage demand generation, and it is particularly problematic when used with ABM. The adoption of ABM has an effect that is similar to reducing the work-in-process inventories in a manufacturing process.

ABM "Lowers the Water Level"

In the discipline of lean manufacturing, inventory is one of the seven primary sources of waste, and most lean practitioners are always looking for ways to reduce inventory levels. To explain one role that inventories play, lean experts use a "rocks in the river" analogy.

In this analogy, inventory is like the water level in a river. As long as the water level is high enough, boats on the river will easily float over any rocks in the stream bed. The high water level makes the rocks invisible and also eliminates the danger they would otherwise pose for boats navigating the river. But if the water level is lowered, the rocks become visible, and the danger they pose becomes clear.

Lean experts say that inventory in a manufacturing system often conceals problems in the manufacturing process. High inventory levels also alleviate the immediate pain caused by the problems, but at a high cost. When inventory levels are lowered, the real problems become visible, and the ramifications of those problems become apparent. So in lean manufacturing, reducing inventories ("lowering the water level") not only eliminates waste, it also points company managers to the real problems that need to be solved.

The adoption of account-based marketing works in a similar way. Because successful ABM demands an unprecedented level of collaboration and coordination across multiple business functions, any lack of collaboration or coordination will quickly become visible. And this will enable company leaders to address the specific problems that are holding back the success of their ABM program.

The bottom line is, ABM can be a catalyst for improving the relationship between marketing, sales, and other business functions because it will make weaknesses in those relationships visible and addressable.

Image courtesy of monikomad via Flickr CC.

Sunday, February 10, 2019

Marketers Are Embracing Advanced Marketing Measurement


Demand Gen Report's 2018 Marketing Measurement & Attribution Benchmark Survey makes one point abundantly clear:  Measuring marketing performance is both a top priority and a major challenge for most B2B marketers.

Eighty-seven percent of the survey respondents said that measuring marketing performance is a growing priority for their company, but more than half (54%) also said their ability to measure and analyze marketing performance needs improvement or is poor/inadequate.

The widespread interest in measuring marketing performance indicates that the demand for performance measurement software is poised to grow substantially. In a September 2018 report, Forrester Research said that marketers spent about $1.09 billion on marketing measurement solutions in 2017, and the firm estimates that spending on such solutions will reach $2.1 billion by 2023.

The Demand Gen research also revealed what is motivating marketers to improve their measurement capabilities. When survey participants were asked what is increasing their need for deeper metrics, the top two drivers identified were:

  • The desire to show marketing's impact on pipeline and revenue (70% of respondents)
  • The push to show ROI from all marketing investments (60%)
As these results show, the key motivations for improving marketing measurement capabilities are to demonstrate the economic value that marketing creates for the business and to optimize the mix of marketing programs based on economic performance.
Both of these objectives require the use of financial metrics, and this makes marketing measurement more challenging. The heart of the challenge is attribution, which is the process of assigning revenue and costs to marketing programs. 
There are three robust methods for attributing revenue to, and measuring the financial impact of, advertising and marketing programs. Two of these methods - marketing mix modeling (MMM) and multi-touch attribution (MTA) - have been in use for several years. The newest and most sophisticated method is unified marketing measurement (UMM).
Marketing Mix Modeling
Marketing mix modeling involves the use of advanced statistical techniques to estimate the impact of advertising and marketing activities on incremental sales and/or other desired outcomes. Marketing mix models are usually based on many months of historical information about sales and marketing/advertising spending across both digital and offline channels. MMM also incorporates factors such as weather, competitive activity, seasonality, and overall economic conditions.
MMM is a top-down approach that estimates the impact of distinct marketing programs and channels on incremental revenue. These models do not evaluate the actions of individual prospects or customers. Because MMM is backward-looking and doesn't consider the actions and responses of individual people, it doesn't provide the timeliness or level of detailed information that are required to support tactical marketing decisions.
Multi-Touch Attribution
Unlike MMM, multi-touch attribution is a bottom-up approach that analyzes information about the actions and behaviors of individual prospects and customers. Ideally, this data will include every exposure that an individual has had to a marketer's messages and his or her responses (or lack thereof) to those messages.
Most MTA solutions focus exclusively or primarily on estimating the financial impact of digital marketing activities, and their ability to capture the impact of offline marketing activities is limited. Therefore, MTA solutions can overstate the amount of revenue attributable to digital marketing programs. MTA solutions can also be inaccurate because they don't usually account for a baseline of revenue that would exist without any marketing efforts.
Most robust MTA solutions use advanced statistical techniques and computer algorithms to assign revenue to marketing activities, rather than relying on simplistic pre-set "rules" (such as first-touch, last-touch, etc.) that often produce wildly inaccurate results.
Unified Marketing Measurement
Given the inherent limitations of MMM and MTA, a growing number of companies have begun using a method known as unified marketing measurement that leverages the strengths and eliminates the weaknesses of MMM and MTA. UMM solutions are capable of measuring the impact of both digital and offline marketing activities, and they combine a top-down and bottom-up approach. In its report, Forrester estimated that UMM solutions now account for 28% of the measurement solution market. 
What About Cost?
These advanced marketing measurement solutions aren't exactly cheap. In a report published last year, Gartner estimated that companies pay from $100,000 to $250,000 on average for a one year MMM or MTA solution. And the cost can be much higher. 
Notwithstanding the cost, advanced marketing measurement solutions can be a smart investment for many companies. In its report, Forrester noted that these solutions often enable a 15% improvement in marketing ROI, and that overall spending on marketing measurement represents only 0.2% of total marketing spending.

Illustration courtesy of Kari Bluff via Flickr CC.