Brands, retailers, and their marketers walk a fine line when trying to reach targeted audiences. They don’t want to waste precious resources reaching out to the wrong people and, at the same time, they don’t want to be so personal that they cross over into creepy territory. James Mullany, a group director at marketing agency Beeby Clark+Meyler, insists the era of micro-targeting is over. He explains, “Opt-outs are surging, data collection is limited, and once-granular targeting options are fading.”[1] During the early years of advertising, macro customer segmentation was one way brands and retailers tried to reach potential customers (e.g., women’s wear was advertised in the social section of newspapers while shaving products were advertised in the sports section). Segmentation still has a place in advertising; however, the way brands and retailers segment is changing. Marketing expert Ankoor Dasguupta explains, “Data-driven targeting enables highly personalized marketing by analyzing customer behaviors and preferences, shifting away from traditional demographic segmentation.”[2] According to Mullany, the future of advertising is all about the algorithms. He asserts, “As detailed segmentation fades away, the stars of the algorithmic age are taking center stage.”
Algorithms and advertising
When algorithms analyze the many sources of data currently available, segmentation takes on a whole new meaning. Mullany observes that new capabilities, like generative AI, coupled with more traditional capabilities, like predictive analytics, can empower marketers “to shape and refine brand-new marketing strategies.” He writes, “We can harness the power of real-time insights to identify high-value prospects at the ideal moment. Then, we must drive deeper engagement — by speaking directly to each stakeholder’s pain points and aspirations.” Dasguupta adds, “Leveraging real-time data streams and big data technologies allows businesses to react swiftly to market dynamics and customer interactions, enhancing the customer experience.” At the same time, he cautions, “As data-driven targeting advances, prioritizing customer privacy and ethical data use is crucial for maintaining trust and ensuring responsible marketing practices.”
The type of segmentation being discussed by Mullany and Dasguupta is most-often called behavioral segmentation. The MarTech Series (MTS) staff explains, “Behavioral customer segmentation [is] a way of categorizing consumers based on their behavior, activities, and patterns of interaction with a company’s products, services, or marketing channels. … Rather than depending merely on demographic or geographic criteria, this segmentation technique focuses on understanding and classifying clients based on how they behave. Behavioral segmentation considers a variety of factors, including: website activity; purchase behavior; engagement behavior; last engagement activity; [and] loyalty behavior.”[3] Leveraging algorithms that utilize the latest behavioral data is more critical than ever in an uncertain economy. Artificial intelligence (AI) solutions, like the Enterra Consumer Insights Intelligence System™, can help organizations better understand their customers and how consumer behavior is changing. The System is part of the Enterra System of Intelligence™, a cutting-edge approach that combines the power of a human-like reasoning and trusted generative AI with glass-box machine learning and real-world optimization to drive intelligent decision-making and fuel business growth. This unique Systems of Intelligence acts as an autonomous “brain” within an organization, enabling real-world optimization and decision-making across the value chain at market speed, with the subtle judgment and expertise of an organization’s best subject matter expert or data scientist.
Understanding changing consumer behavior is not just important for maintaining market share and retaining customers, it’s important to identify and take advantage of new opportunities. Corinne Casagrande, Senior Vice President for Strategy, Planning & Research at Active International, reports, “Consumers are not behaving the way economic models say they should. … When consumers are acting weird, marketers need to open their minds to new markets.” Casagrande asks an important question: “Are you missing new segments because they don’t look like your core customer?” Algorithms can help you discover and take advantage of new opportunities. Casagrande explains it this way: “Machine learning and AI help us find lookalikes we might not consider. … Let’s test as many new opportunities as we can.”
Segmentation still has its place
Mullany insists, “It’s time to face reality: Segmentation, as we know it, is dead — and marketers need to find new, better ways of creating engagement.” The phrase “as we know it” underscores the fact that segmentation, in some form, still has its place in marketing. The MTS staff notes, “In today’s highly competitive business landscape, understanding customers and delivering personalized experiences are key factors for future success. This is where customer segmentation comes into play. Customer segmentation is a strategic approach that involves dividing a diverse customer base into distinct groups based on shared characteristics, needs, and behaviors. By segmenting customers effectively, businesses can gain valuable insights into their target audience, tailor marketing efforts, and optimize overall business strategies.”
Financial analyst Evan Tarver notes, “Companies can generally use three criteria to identify different market segments: Homogeneity, or common needs within a segment; distinction, or being unique from other groups; [and] reaction, or a similar response to the market.”[5] He adds, “The objective of market segmentation is to minimize risk by determining which products have the best chances of gaining a share of a target market and determining the best way to deliver the products to the market. This allows the company to increase its overall efficiency by focusing limited resources on efforts that produce the best return on investment (ROI).” One of the keys to successful customer segmentation is identifying how you want customers segmented. It’s trickier than you might think. Oscar White, CEO at Beyonk, explains, “Different markets and audiences can be split in different ways. Find out what is a meaningful way to segment your audience based on your positioning. For example, are you targeting different price points in the market or segments that prefer different features of a product? Use this question to split up the market to gather data and target your audience appropriately.”[6] Robert McGovern, a Sitecore Optimization Consultant at Sagittarius, asserts, “[AI} can be very effective at finding ways to group customers together that might not be overly apparent to the human eye.”[7]
Concluding Thoughts
In today’s environment, where privacy is becoming a bigger concern, first-party data collected by brands and retailers is increasing in importance. McGovern explains, “In a post-third-party-cookie world, brands that rely on middlemen to reach their customers will be increasingly at a disadvantage while brands that take their first-party data seriously and use technology like [artificial intelligence and machine learning] to utilize it will be well placed for tomorrow.” Mullany concludes, “By harnessing the power of algorithms to uncover hidden motivations and preferences, … we can craft messages that forge real connections and build trust. The crux of success in our current era lies in aligning with decision-maker values and evoking emotions. Now is the time to boldly test new tools and ideas — and push our creative boundaries. It’s how we will unlock deeper engagement and drive results.”
Footnotes
[1] James Mullany, “Segmentation Is Dead: Rethinking Micro-Targeting (And B2B Marketing) in the Algorithmic Age,” Marketing Profs, May 2024.
[2] Ankoor Dasguupta, “5 Ways Data-Driven Insights Are Reshaping Customer Segmentation,” CMS Wire, 10 April 2024.
[3] Staff, “Customer Segmentation: Tips and Best Practices,” MarTech Series, 22 June 2023.
[4] Corinne Casagrande, “During Economic Uncertainty, Embrace The New,” The Marketing Insider, 28 February 2023.
[5] Evan Tarver, “Market Segmentation,” Investopedia, 25 July 2022.
[6] Amy Danise, “14 Steps For Getting Started With Data-Driven Market Segmentation,” Forbes, 3 May 2022.
[7] Robert McGovern, “Demystifying AI For Personalization,” The Marketing Insider, 4 October 2021.
