AI’s inflection point was OpenAI’s decision to provide free and unfettered access to ChatGPT — the result: 100 million users in less than two months. 

As martech and marketing operations leaders, this open access is both a blessing and a challenge. It dramatically changed our 2023 plans and priorities.

That’s where MarTechBot entered the picture approximately two weeks ago. Thanks to Marc Sirkin and the team at MarTech for allowing me behind the curtain of MarTechBot, providing insider access to how it’s being trained, the underlying tech, and the real-time learnings.

Sirkin and I discussed the implications of the contextual “MMM” prompt that he posted about. That experiment demonstrated that training MarTechBot with this site’s content would result in customized answers for marketers. The result was expected but impressive nevertheless. And led to further reflection. Here are some of the insights I walked away with.

• Start now. Learning how to train an AI bot using a company-specific language model should be at the top of your 2023 to-do list. It may not be released to the public, but the potential benefits demand that we all start taking tangible steps now.
• Echochamber effect. Watching MarTechBot respond within the bubble of marketing and martech was awesome — like a two-week-old baby already knowing how to say “mom” and “dad!” However, the implications are serious. Biases may creep in just as quickly. In the world of marketing tech, would MarTechBot soon conclude that the only solution to each marketing problem is to add a new tool to the stack?
• New marketing ops roles. We discovered that training a bot comes with all sorts of new guardrails. One example is operationalizing GPT token limits. While word counts are a rough metaphor, they are not exact equivalents given the predictive feedback loops that are the foundation of large language models (LLM). Another example would be new content ops roles to edit audio/video text transcriptions. Previously, slight inaccuracies produced by real-time closed captioning would’ve been overlooked. Those inaccuracies are consequential when text is fed into training bot models.
• Pivots. If a bot can be trained so quickly to take on a tone of voice, can it be retrained instantly? What if a brand has trained a bot on messaging and tone that’s now obsolete because of a new product direction or rebranding?

But wait, there’s more! The following are just the tip of the iceberg when it comes to new MarTech and MOps challenges (e.g., unanswered questions!) that MarTechBot prompted.

• New stack without a how-to guide. Those creating generative AI systems admit that they don’t understand exactly why and how they respond the way they do sometimes. How does a marketing ops professional explain that to customers, the executive team, shareholders, etc.? 
• Balancing speed and responsibility. The race to innovate will unearth thorny legal, copyright and ethical issues. Will new content tags such as #train_on_this (or #do_NOT_train_on_this) be honored? 
• The potential rekindling of marketing-IT “infighting.” Over the last 10 years, we have established some norms in the role/responsibility splits between marketing and IT. But AI tools will be used by the entire enterprise. Will marketers need to renew their cross-functional partnership with IT, or risk losing access to important datasets that IT will and should always control for the enterprise?
• Rapid infusion into marketing automation. As I wrote and spoke about in March, these capabilities also drive reinvestment in core CRM and marketing automation platforms as the foundation of the martech stack. I’ll cover the impact on data management in part 2 of the series in June. How much will change again or be introduced between now and then? (I’ve already modified my outline three times!)

In the past, vendors and/or consultants could usually help us identify where something was awry in our stacks. That won’t be the case with the AI bot stack for the next 6-12 months. We have to be the operator behind the curtain. Start today.

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The rapid adoption of generative AI has increased the excitement volume to 11 for martech professionals. AI-enabled enhancements to the core uses of marketing automation platforms — data management, campaign/lead management and workflows/integrations — are being introduced by Salesforce, HubSpot and other market leaders. They will alter the mix of tasks marketers tackle daily and impact planned improvements to customer experiences and satisfaction.

This quote sums up the scale of AI’s impact:  

“Next-gen marketers know that in order to deliver the personalization and experiences modern consumers expect, marketing must become smarter. It must become marketer + machine.”

– Paul Roetzer and Mike Kaput, Marketing Artificial Intelligence

This statement could have applied to the mainstream adoption of marketing automation platforms (MAP) as the original natural language processing for martech. They experienced an inflection point — similar to the one we’re seeing with AI today — of their own 10 years ago. Widespread adoption of marketing automation set the stage for the exponential growth of martech applications, which increased to over 10,000 in 2022 — a 6,000% increase compared to 2011. 

Why it matters. New capabilities will emerge by infusing MAPs with AI, further expanding the influence of the foundation of most organizations’ martech stack: core MAP integrated with CRM. Therefore, martech leaders should invest in discovering use cases that can be modified to incorporate new AI capabilities. AI-powered, tried-and-true best practices will drive value in 2023 and beyond.

Here’s how AI will be applied to the three core marketing automation uses. Each of these three will be the focus of a deeper dive follow-up piece over the coming year. 

Data quality will be even more important when our data are used to train company-specific AI models. 

Underlying data about customers and prospects is table stakes for personalizing marketing. As the amount and variety of data captured increases, it will require re-focused efforts to adjust to more natural language standard values in drop-downs, form fields, etc., to describe customer engagements. AI will enable marketers to understand, process and analyze data more effectively.

Campaigns and lead management. AI will enable new campaign approaches within existing workflows. Generative AI will power these approaches by choosing between content AI integration prompts or asking an AI assistant to help “codify” business processes. 

Workflows and integrations. Previously assumed scope limitations for broader operations and orchestration will be tested. If generative AI can help coders correct code, it’s just a matter of time before it can help extend an open API beyond a native Integration.

Native platform integrations were the original natural language for field mappings and workflows between the CRMs and marketing automation platforms. Instead of asking an IT team to build a custom API, we could use natural language software interfaces to set them up. 

Although the overall AI trends are moving at an unprecedented pace, re-investing in these core MAP processes will prepare your organization to adapt to these new AI-infused capabilities quickly. 

Check back for part two of this series on the AI infusion into data quality.  

Can’t wait for more? Check out my presentation at the MarTech Conference next week, “New School, Old School: Navigating the Current Marketing Automation Landscape.”

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The path to knowledge employs the scientific method. Practitioners first develop a hypothesis, which is an assumption or potential explanation for an observation. They then test the hypothesis by conducting experiments. An idea in marketing is analogous to a hypothesis. The execution — such as a campaign based on the idea — and measurement of results can be compared to an experiment. 

Incorporating a scientific-discovery mindset is integral to the success of marketing teams and professionals. Evaluating and implementing new martech is now a core responsibility of marketing and marketing operations professionals (see part 1). The hypothesis implicit in the adoption is that the new technology will enhance outcomes. Using the marketing software, and measuring the results, is the experiment.  

For example, a cornerstone value proposition of marketing automation platforms is the ability to conduct email marketing at scale. Not only can using the platform determine whether it can achieve that goal, but it’s also possible to conduct experiments within experiments. A/B testing was initially implemented by creating and deploying two separate versions of the email creative to small segments of the database. This is a simple experiment to determine which creative performs better.

Every element of every digital campaign and underlying tactic is an opportunity for an experiment. The results (which performed “better”) are measured from recipient responses. Those responses may include key performance indicators (KPIs) ranging from the foundational — opens, click-throughs, form-completions, conversion rates — to campaign and business outcomes, e.g., leads, opportunities and sales.  

Holistic testing and iterative learning

Many marketers consider A/B testing a starting point. But linking multiple tactics and experiments, and using an iterative approach, can turbocharge our marketing. 

We ”…want to go a little bit further than (A/B testing) and do what I call ‘holistic testing,’ which is very much scientific testing,” Kath Pay, CEO of Holistic Email Marketing, said at a recent MarTech conference.

“Once you get a winning result, and this will be based upon time, as opposed to just the volume of emails (in a single campaign), then you’re going to update the hypothesis and replace the losing stream with a new stream that’s supporting your next hypothesis,” Pay explained.

Learning is an iterative process whether the A/B or holistic approach is employed. Observations yield a hypothesis. A test is conceived and conducted, followed by a review of results and learnings applied to the next iterative learning cycle. 

Evaluate results, beware automation 

Every experiment yields more data to be analyzed. Successful marketers are disciplined to pause and evaluate the outcomes of experiments before moving on to the next.  

Often, the data requires us to revise our hypothesis before coming up with the next experiment. Just because we can automate the next step doesn’t mean we should.

Scientists impact business results

Marketing leaders and marketing operations specialists are often tasked with building the models that report on the outcomes of marketing programs. 

Attribution models have evolved significantly beyond “last touch” conversion measurements for most organizations. Applying scientific rigor to attributions requires testing multiple hypotheses to determine the outcome.

Some experiments fail 

Failure is baked into the scientific method. If every idea is a hypothesis and every campaign an experiment, then it’s inevitable that some hypotheses be disproved. Failed experiments provide direction for the next hypothesis and the next experiment.  

“In the end, the analytics won’t tell you the next big creative idea, it will tell you when the next big creative idea is working,” according to Elea Feit, Assistant Professor, Marketing at Drexel University. 

Conclusion

Harnessing insights from data created by user interactions is the key to improving customer experience and boosting conversions. Adopting a scientific approach — developing and testing hypotheses — is key to improving experiences and outcomes. 

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Exposure to marketing during my early educational journey was limited. With a heavy math/science background, I chose the “easy” path and majored in engineering. I struggled in advanced engineering classes but thrived in electives — communications, business, organizational behavior — which was a sign for my future in marketing.

Because of my engineering background, I was fortunate to get an opportunity to join GE Healthcare through its entry-level leadership development program. There I was exposed to magnetic resonance imaging (MRI). 

MRIs had become go-to diagnostic devices and subsequently were used in neuroscience. I was fascinated by their eventual application in fMRI: Functional MRI. These extensions helped us understand the most consequential medical mystery: how (and why) people do what they do.

fMRI uses the same underlying technology as conventional MRI, but the scanner and a medical contrast agent are used to detect increased blood flow in response to a stimulus in what is commonly referenced as “hot spots.”

fMRI reveals which of the brain’s processes “light up” when a person experiences different sensations, e.g., exposure to different images in common studies. As a result, we now know what parts of the brain are involved in making decisions.

Successful marketing ‘lights up’ customers’ brains

Traditional marketing campaigns and measurement left gaps in understanding how and why people choose to buy. We were dependent on aggregated data. 

With digital channels, we gain first-hand insights into an individual’s response to a stimulus, i.e., content. Here’s where the comparison picks up: 

• We can observe nearly anything and everything that customers or prospects do digitally.
• Most customers know that we can track (almost) everything that they do.
• Because of that knowledge, customers expect contextual, value-based content, forcing marketing to provide more value in exchange for the permission to track.

Our goal as marketers is to make our customers and prospects “light up” with pleasure or satisfaction at each interaction. And, we now have the technology to track it. We are effectively reading minds — just as if it were an fMRI scan.

Here’s an overview of three of the primary psychology “tactics” that every marketer should know: 

• Priming is the attempt to trigger a subconscious reaction to stimuli that influences our conscious decisions. The most common application is in branding and first click-through impressions. If a customer continues their journey, then the use of aspirational product or service images in content are common priming approaches.
• Social proof is perhaps the most common example, given the impact of word-of-mouth influence. It is commonly seen in product reviews and ratings. Content marketing often relies on case studies and customer testimonials to hear from “people like us.”
• Anchoring refers to marketing’s role in pricing and discounting. Most decisions people make are relative to the initial set of information they have received.

MOps leaders manage the mind-reading stack 

MOps leaders are modernizers that now manage the mind-reading martech stack. We then lead the orchestration efforts to analyze the response (the “scan” data) and “prescribe” the next steps of the campaign.

Two catalysts spawned the emergence for martech applications:

• New channels that delivered stimulus (content) and collected responses: search, social media, retail commerce channels, etc.
• Tools that organize and manage all of that response data, from foundational CRM platforms to marketing analytics and data enrichment.

These developments led to the new psychological skills that have become essential to the role of MOps leaders. 

Processing and interpreting intent data is an example. ZoomInfo illustrates how B2B marketers are accessing this capability. The company now provides buying signals to marketers based on their customers’ behaviors, in addition to the basic contact information that was the origin of its business. 

Intent data is already in widespread use. Six in 10 companies responding to a recent survey said they had or planned in the next year to implement intent measurement data solutions. 

The top challenges for effective intent data utilization fit squarely in the role/responsibilities of MOps leaders include:

• Integration.
• Platform selection.
• Data management/analytics.

These trends support the conclusion of the first three parts of this series — that MOps leaders should aspire to be: 

• Psychologists who elicit responses (i.e., “light up” the brains) of customers and prospects and interpret those signals for the business. 
• Modernizers who adopt the technology that enables the activation of those signals.
• Orchestrators who are cross-functional project managers and business partners with IT, legal and compliance.

Next time, I’ll complete the framework with a discussion of how the role of MOps leaders includes being a scientist, constantly testing and evaluating marketing efforts with teams of analytics specialists and data scientists. 

Editor’s note: This is the 3rd in a 4-part series. In case you missed them, part 1 (modernizers) is here, part 2 (orchestrators) is here, and part 4 (scientists) is here.

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In case you missed it, part 1 is here. And if you want to skip ahead, here are part three (psychologists), and part four (scientists).

Inspiration for this framework

Two years ago, marketing technology pioneer and chiefmartec.com editor Scott Brinker outlined the four key responsibilities of marketing technologists, summarized here.  

That work espoused the view that you could be both a marketer AND a technology leader. They are not mutually exclusive! It was my inspiration for this framework, explaining how today’s MOps leaders are instrumental for marketing and business success.

X-Axis:  A range of skills from a focus on technology to creativity and arts

Y-Axis: A range of decision-making skills, ranging from emotional to rational approaches

The resulting grid captures four MOps archetypes or “personas.” MOps leaders exhibit characteristics across all parts of this framework and will operate in multiple quadrants, similar to Brinker’s frameworks.

Modernizers – Are most likely to be the “original” technologists, constantly modernizing their martech stack.

Orchestrators – Are the closest to Brinker’s Maestros and the focus of this article. He described this archetype in 2020 as the “Operations Orchestrator — MAESTROS who design and manage the workflows, rules, reports, and tech stacks that run the marketing department.

Psychologists – Are now increasingly responsible for “reading customers’ minds,” i.e. interpreting customers’ interest through intent data and digital engagement.

Scientists – Are constantly testing and evaluating. Experimentation is their specialty.

Orchestrators: Leaders of the band

Now that you’re familiar with the framework, let’s dig deeper into the Orchestrators!

I’ll start with a personal story. My exposure to orchestration started with 8-straight years of practice in violin and trumpet during my formative years. Each week was literally a blur of private lessons, group lessons, orchestra and/or band practice. I probably spent as much time with music directors as I did with my family.  

It was painfully obvious to those conductors when we hadn’t prepared or practiced. Moreso, we would get – literally – an “earful” from the conductor when we were not listening to the other instrument sections. If we were not coordinating our efforts and timing, the outcome was awful for anyone listening.

This orchestration metaphor is powerful because there are multiple levels for MOps leaders:

• As a project management team within marketing, and often as a conductor across external agency partners.
• As a cross-function business partner and primary contact for IT, compliance, and legal, in addition to the traditional MOps role of achieving marketing/sales alignment

Notably, all marketers have to be project managers for their own tasks/deadlines. They must be aligned with overall campaign and program timelines. 

However, as organizations scale they are more likely to have dedicated project management teams to handle coordination across the specialist teams within marketing. The orchestration responsibility may include timeline, scope, and capacity trade-offs even after campaign briefs have received approval. 

The orchestration responsibility multiplies when agency execution teams are delivering on individual tactics and media buys. Last year, Optimizely described these evolving orchestration duties as a “transformative shift and approach towards how marketing synchronizes their teams, content, channels, workflows, and data!”

I believe the shift is even more impactful, with orchestration benefits being felt beyond marketing. The highest value “program orchestration” responsibilities occur when MOps leaders are representing marketing’s interests in enterprise-wide programs with other functions within the organization, including product, compliance, and IT. Examples of orchestration duties with these other key functions can include:

• Product teams – Coordinating campaigns with major product feature/functionality launches, and managing brand standards.
• Legal/Compliance – Overseeing compliance with Can-Spam, GDPR, and CCPA, and customer preference and data privacy initiatives that may be initiated by a marketing touch-point. 
• IT/Procurement – Technology stack management, vendor evaluations and negotiations, platform integrations and data management.

All of this departmental and cross-departmental coordination requires skill sets that can be analogized as the difference between a chamber orchestra (marketing) and a full symphony. It’s the highest level of conducting across the enterprise. 

MOps leaders are holding individuals and teams to target timelines while managing the scope of a particular campaign and business initiative. They do this while also overseeing targeting of customer and prospect segments.

In order to accomplish this complex segmentation and coordination, MOps leaders are now responsible for cross-functional data – embodied by the modern martech stack imperative: integration. Integration across systems has been the #1 issue for marketers since the modern marketing tech stack started exploding in the early 2010’s, but software and solutions providers finally listened. A tipping point was reached in 2020. Marketers reported that we were finally working within an integrated, multi-system environment, according to a CDP Institute member survey analyzed here.  

Continuing with the orchestration analogy, the conductor is the integration “synchronizer,” deciding if/when the data flows across the stack. The sheet music is the data model standard showing how to map common attributes. 

However, just because we now have this more integrated environment does not mean our work is done. The instruments do not play themselves (yet!) and they require configuration and deliberate training to play effectively — both individually and in groups. 

Training was one of the top responsibilities for marketing ops leadership, ranking it in the top 5 of MOPS tasks by percentage of work, according to the 2022 MarTech Salary and Career Survey, published jointly by MarTech and chiefmartec.com (free, ungated download here). conducted by chiefmartec.

In the 2020 version of that same study, training was highlighted as one of the top two responsibilities for many of the primary marketing technologists personas, and 91% of operations orchestrators reported that training and supporting technologies were among their top priorities.

MOps leaders are never done

Finally, under the category of “MOps leaders are never done”, the last several years have also forced a whole new category of orchestration duties – a combination of conducting, training, and martech growth: marketing work management.

The largest growth (67%) over the last several years was in the category of “work management”, according to the 2022 edition of the Martech Landscape. Established entrants such as Adobe expanded with the acquisition of Workfront, while newer players like Trello and Monday gained traction.  

Although this was already a prevailing trend BEFORE the pandemic, the hybrid/remote work environment brought on by the last 2+ years forced these project management and agile-planning tools to the forefront.  The marketing work management category grew to over 1000+ tools, according to the State of Martech 2022. 

Source: State of MarTech 2022 – chiefmartec.com and Martech Tribe

MOps leaders are Maestros

In summary, modern MOps leaders are indeed Maestros. They are skilled orchestrators, conducting a symphony across multiple levels. They lead:

• Omni-channel campaigns within marketing and across business functions
• Integration across an ever-growing, integrated martech stack
• Training and deployment as one of their primary responsibilities 

Editor’s note: Part one of this series discusses MOps professionals as “optimizers”. Part three and part four discuss the role as psychologists and scientists, respectively.

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Over this four-part series, I will dive into each aspect of the framework. This first article elaborates on the framework itself and then dives into how MOps leaders are “modernizers.”

A new MOPS framework

I love new terminology and frameworks that help make sense of the world.

Therefore, I particularly appreciate leaders that create new ‘phraseology.’ At the top of the list in turning phrases into (best) practices has been Scott Brinker. Over 10 years ago, Scott wrote about the rise of the marketing technologist. While it feels obvious now, it was unfamiliar jargon at the time.

Just two years ago, Brinker revisited this by outlining the four key responsibilities of marketing technologists, summarized here. This helped so many of us as it further legitimized the role by proclaiming that you could be both a marketer and a technology leader.

This was particularly impactful because, over those 10 years, the role of marketing technologists had been formalized and typically housed within marketing operations. They were no longer lone wolves without clear organizational ownership between marketing and IT. In larger teams, there are often multiple technologists. We needed this expanded terminology and a framework to describe the varying leadership roles we had taken on as the martech landscape exploded into 8000+ tools.

I often reference this to explain the rapid evolution of MOps roles and responsibilities. It was the inspiration to pull together this framework for describing how today’s MOps leaders are instrumental in marketing and business success. I’m hoping these two frameworks can operate side-by-side to help characterize the growing shift towards recognizing marketing tech and ops leaders. And yes, this framework is an opportunistic play on the “MOps” acronym that has become the catchphrase (I am a marketer, after all).

I chose to portray the X-axis as a range of skills from technology to arts orientation. I’m sure it is not a surprise that I decided to depict technology, but my choice of the arts was also deliberate. I want to debunk that Ops leaders are not creative. We are creative, adapting processes and technologies to meet challenging customer and business needs. Much more on that aspect in the Orchestrator role in part two of this series.

For the Y-axis, I wanted to illustrate that MOps leaders have to leverage the complete range of decision-making skills, ranging from emotional to rational processes, to succeed in today’s marketplace. There is a duality to this: MOps leaders have to leverage these skills to succeed in their internal marketing roles. But, because they are also responsible for capturing the customer signals — e.g., how people evaluate products and services, it becomes a rapid combination of emotional and rational skills.

The resulting grid captures four MOps ‘personas’ in the respective quadrants. Note: MOps leaders will likely have an area of strength that they gravitate towards, but they can exhibit characteristics across all parts of this framework and be in multiple quadrants.

Modernizers

We are excited, yes — literally emotional about the rapid changes in marketing tech. We are most likely to be the ‘original’ marketing technologists, and I’ll be expanding on our challenge of constant modernization in the remainder of this article.

Orchestrators

This is the closest to Brinker’s Maestros. However, we are not just orchestrating across marketing – but we are the ones to connect marketing’s efforts across other functions.  Because of that unique cross-functional role, we are often helping connect marketing campaigns to the broader customer experience initiatives. We are the first to recommend changing the marketing strategy due to changes in customer behavior or broader market conditions.

Psychologists

Because so much customer engagement is now captured digitally, MOps teams are increasingly responsible for “reading customers’ minds” — interpreting customers’ interest and engagement with the brand. I also recognize that many would consider the mapping of the Psychologists aligns better on the emotional side, considering the role of emotion in decision-making. I did consider this, but I will expand on the unique way that MOps leaders can leverage today’s digital channels to turn emotional data into rational signals of intent in part three of this series.

Scientists

MOps leaders are constantly testing and evaluating, and we are often the team that houses the new analytics team of modern data scientists. We are also considered the ‘mad scientists’ of martech, pairing multiple tools together through ‘no code or low code’ integrations.

Now that I’ve introduced the framework, let’s dig deeper into the Modernizers. 

I’ll start with a playful quiz. You’re likely a “modernizer” if you have waited anxiously for Brinker to release his annual Martech Landscape (last released in 2020; he recently announced the latest would be released next month).

That’s one reason why I mapped the emotional axis of the framework. We’re kids waiting for presents under the holiday tree, even though we know some of the new toys will be short-lived and discarded by the new year. This is not rational. We get a marketing high by learning about new technologies pushing the envelope of marketing’s capabilities. But this emotional high is more than just technology for technology’s sake. It’s about applying technology to improve customer experiences or marketing efficiencies. Even if we are not formally rolling out the agile manifesto, we embrace multiple underlying agile principles to drive value through technology.

Let’s take a further step back and go deeper into what it means to be a modernizer.  

It’s now a mindset — a constant process of adapting to new needs and customer habits. McKinsey’s research group summarized this well, “To drive growth in the digital age, marketing needs to modernize a specific set of capabilities and mindsets. Marketing departments need to be rewired for speed, collaboration, and customer focus. It’s less about changing what marketing does and more about transforming how the work is done.”

That last part struck a chord with me. “Transforming how the work is done.” To illustrate this point, let’s look at some examples of established tactics that have been modernized, often with  MOps teams leading the modern RENOVATION of channels with new technology.

Modern MOps leaders are constantly modernizing — e.g., adapting with lessons learned and quickly applying changes to the process. In most cases, these fast adaptations respond to a change in the business process. They can also be driven by active observation of customer preferences as those change; we only have to look at the past two years of how marketing responded to the COVID pandemic for actual examples.

However, this constant adaptation is tough and tests MOps leaders’ fortitude. 

One of my favorite marketing books is Geoffrey Moore’s Crossing the Chasm. Moore describes how new technology must depend on an influx of early adopters to help cross a chasm before the technology enters the mainstream.

Here’s the catch, though, modernizers. We have to cross the chasm repeatedly. Because MOps leaders are the department’s marketing technologists, they are early adopters of new technology. But because we’re adopting these new technologies to integrate with previously “new” technologies, we are also connecting to the established system and responsible for helping others cross the chasm. We are, in fact, on both sides of the chasm at the same time. I’ve depicted this challenge in the graphic below.

In the live chat example, we had just crossed the chasm to integrate monitored live chat (B) into the website experience (A). Soon after that, multiple vendors had released AI-driven upgrades (C) that provide bot-enabled responses to customer inquiries. Indeed, the work of a MOps “modernizer” is never done.

Can’t wait for the rest of the journey? Here’s part two (orchestrators), part three (psychologists), and part four (scientists).

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