AI in CMO Strategy: Transforming Marketing Leadership
- AI transformation. AI in CMO strategy is accelerating the shift from sales enablement to buyer enablement, providing tools for hyper-personalization and predictive analytics.
- Marketing revolution. AI in marketing enables CMOs to develop alternate attribution models and drive personalized experiences, redefining customer engagement.
- Generative boost. Generative AI is enhancing the productivity of marketing teams by taking over data analysis tasks, allowing professionals to focus on strategy and innovation.
A group of chief marketing officers (CMOs) say artificial intelligence (AI) is reshaping several key functions of their role — from strategy, tactics, and staffing to customer engagement and metrics. They believe embracing, understanding, and applying AI in marketing as leaders is critical to effectively using their data and channels to reach customers. The CMOs shared with CMSWire various details on those effects AI is having on the marketing C-suite:
1. AI in CMO Strategy
Michael Park, CMO at the Santa Clara, California-based digital workflow company ServiceNow, said AI is “arriving just in time” to accelerate enterprise marketing’s evolution from sales enablement to buyer enablement.
Four major goals of effective customer experience (CX) are understanding buyer pain points, mapping the buying journey, personalization and continuous improvement fueled by customer feedback, according to Park.
Park said companies enable those fundamental CX goals at larger scale and in greater depth with generative AI’s capabilities: most notably, cross-system data summarization, hyper-personalization, predictive analytics, real-time sentiment analysis and ultra-fine segmentation
Jennifer Chase, EVP and CMO at the Cary, North Carolina-based analytics software company SAS, said AI can develop biases, and it is important for the “sake of responsible marketing that marketers own the responsibility for inclusivity in AI.”
“Biased data and biased models mean biased results and mitigating that falls squarely on the shoulders of the marketing team,” Chase said.
Chase said “explainability is important,” and as such, SAS is implementing model cards — “like the ingredient list on your food but for AI” — to give both technical and non-technical marketing users a comprehensive understanding of their AI models around accuracy, fairness, interpretability and drift.
Model cards can help ensure AI algorithms are “staying on track ethically” and “inclusivity continues to be a mainstay” in marketing programs, she said.
Michelle Huff, CMO at the San Francisco-based provider of UX insights UserTesting, said the company has begun to explore and experiment with AI “across the entirety of our business.”
Huff said UserTesting is “diving deep” into understanding data protection and privacy with the overarching objective of discerning how AI can help differentiate it, achieve more with fewer resources and build experiences for customers.
“We CMOs are frequently the frontrunners in organizational innovation, contemplating how to distinguish ourselves from the rest,” Huff said. “AI can be a monumental ally in this endeavor.
“There’s a wealth of data over the years showing how organizations have leveraged technology to secure a competitive edge and fuel business growth. My strategy is to ensure that we continue to be innovators and early adopters.”
Monica Ho, CMO at the San Diego-based multilocation marketing platform SOCi, said AI’s “foresight” allows CMOs to predict market shifts, comprehend consumer patterns, and assess campaign prospects, “paving the way” for strategic resource deployment and more precise targeting.
“Consequently, CMOs gravitate toward a more customer-focused model, personalizing each interaction to cater to distinct customer needs and requirements,” Ho said.
Related Article: AI in Data Analysis and the Evolving Role of the CMO
2. AI in CMO Tactics
Park with ServiceNow said generative AI helps marketers “avoid the damage they feared in the new age of cookieless browsing.”
Park said AI-powered hyper-personalization, predictive analytics, and cross-system summarization of data allow marketers to develop alternate attribution models, drive personalized relevance, create value triggers to attract buyers to companies’ sites, and deliver such rich, supportive CX that buyers “willingly disclose their identities because they’re hungry to learn more.”
Ho with SOCi said AI’s advanced analytics provide a “tactical edge” by enabling more detailed customer segmentation by processing and analyzing vast amounts of data to identify customer patterns, behaviors and preferences.
For instance, she said marketers can use AI to cluster customers based on their browsing habits, interaction with previous marketing campaigns, sentiments expressed on social media, and product review patterns.
Mahesh Kumar, CMO at the Campbell, California-based data observability platform Acceldata, said AI can help marketers analyze customer conversations at scale to understand pain points, inform product direction, and identify objections as well as optimize digital spending and expand a company’s content.
Johann Wrede, chief experience officer at the travel and expense management company Emburse, added that customers are beginning to use generative AI to search the web and gather information.
“So we need to think about getting our message seen beyond search and social now,” Wrede said. “As marketers, we need to ensure that product information provided by AI is accurate and based on information coming from us — as opposed to being inferred or pulled from unofficial sources.”
Related Article: Finally, a Data Book for CMOs Detailing Data Monetization Strategies
3. AI in CMO Team Staffing
Park with ServiceNow said AI “supercharges” the marketing talent “we worked so hard to attract,” making our highly skilled people even more productive and effective, doing more with their resources.
When it’s properly applied, generative AI speeds and amplifies “resident excellence,” he said.
Park said skilled marketing professionals are seeing generative AI can already do many tasks that require data analysis, synthetic creativity and problem solving.
“To keep ahead, professionals know they’ve got to evolve with AI, and they are,” Park said.
Considering how many skills enterprise marketing teams now comprise — from data scientists to right-brain creatives — CMOs should adopt a “CEO mindset,” he said.
“Marketing has too many functions for the CMO to be expert in all of them, especially with the advent of generative AI,” Park said.
Huff with UserTesting said there’s a “level of urgency to delve into and experiment with AI”
“If there’s a chance that AI can help my organization achieve a 20% productivity boost on a similar budget and workforce, I don’t want to overlook it,” Huff said.
Mairead Maher, CMO at the customer and employee experience platform Poppulo, said the CMO needs to “build a culture where AI is embraced and valued.”
AI, she said, should help deliver greater efficiency and impact within teams, helping to free up valuable employees who have to invest time in mundane and repeatable production tasks.
“Resources instead can be focused on leveraging this capability with oversight, and delivering outcomes that will have greater brand differentiation and impact,” Maher said.
Maher also noted that AI brings a “new wave of technologies to master,” whether that’s to improve copy, video or image generation.
“But marketers are ready to answer this call — AI is just another pillar of our tech stack,” Maher said.
Ho with SOCi said AI can help bring some structure to the numerous tasks marketers “juggle daily.”
For AI implementation to be effective, Ho said CMOs need to prioritize AI training for marketing teams to ensure they understand the value AI brings.
Elias Terman, CMO at the Waltham, Massachusetts-based cloud and endpoint security provider Uptycs, said AI doesn’t replace his team. Instead, AI augments their capabilities, accelerating their ability to “do what they do best” — create, innovate, and connect with customers “on a human level.”
Wrede with Emburse said he believes that with AI, marketing jobs will “shift from creation and production to review and editing.”
Related Article: A Game Plan for Generative AI in Customer Experience & Marketing
4. AI in CMO Customer Engagement
Park with ServiceNow said that as customer needs change during the buying journey, AI segmentation allows marketers to deliver personalized, appropriate, and engaging customer experiences.
For instance, Park noticed event attendance and engagement increased when his organization started using AI-powered audience segmentation to target the right attendees.
AI’s personalization at scale, predictive analytics, and real-time sentiment analysis let enterprise marketers deliver “consumer-quality CX” to enterprise buyers, he said.
Park said AI’s segmentation capabilities are also being used to redefine voice of the customer (VoC) insights and develop and accelerate VoC-driven enterprise and product improvements.
Maher with Poppulo said AI is helping marketers deliver more relevant content and drive higher levels of customer engagement and conversion, impacting personalization for both online and physical experiences.
Ho with SOCi said AI chatbots are enhancing customer service and engagement by offering real-time support and immediate feedback. By operating around the clock, AI caters to customers at all hours and uses real-time behavioral insights to engage users, “refining the entire customer journey.”
Wrede with Emburse noted that as chatbots become smarter, he anticipates customers will have less patience for combing a company’s website for information — “they’ll just ask for what they want when they want it.”
“I think customers will always have a strong desire to eventually speak with a human,” Wrede said.
He also sees a trend toward in-person events for customers and prospects, as there will continue to be a desire for “human connection in business.”
5. AI in CMO Metrics
Park with ServiceNow said AI’s predictive and advanced analytics can help make KPIs themselves more accurate by assessing how campaigns are faring now and will probably fare in the future, based on historical data and current trends.
Park sees attribution and ROI analysis, which are always challenging, becoming more accurate as AI tracks customer journeys across multiple touchpoints and measures each channel’s contribution.
Kumar with Acceldata said machine learning (ML) algorithms are being used to analyze marketing metrics, such as best performing campaigns by persona, geography, and other factors.
He said AI has greatly democratized how marketing metrics can be consumed. Products now have a natural language interface to extract information. Likewise, some data and metrics integration tasks can be done using AI in a natural language
Wrede with Emburse added that in terms of metrics, “good business is good business, regardless of technology.”
“AI will give us the ability to increase our efficiency goals, but it won’t change the core KPIs that we use to measure the health of our business,” Wrede said.
He said vital marketing metrics — such as marketing originated pipeline, marketing influenced pipeline, net revenue retention, and return on marketing investment — are “here to stay.”